Every second, hundreds of packages are moving, sorted, routed, and delivered with near-perfect precision. According to the Harvard Kennedy School, Amazon alone delivers 231 packages every second. That is 1.6 million packages a day in the U.S. and more than 9 billion items annually. And this is just the beginning.

Global e-commerce is accelerating at an unprecedented pace, projected to reach $6.88 trillion in 2026 and climb to $8.91 trillion by 2030. At the same time, B2B e-commerce is scaling even faster, expected to surpass $62.2 trillion by the end of the decade. Behind every one of these transactions is a physical reality: products must move, quickly, accurately, and efficiently, through factories, distribution centers, and warehouses.

This explosive growth is placing enormous pressure on material handling systems. Traditional conveyors are no longer enough. To keep pace, operations are turning to Autonomous Mobile Robots (AMRs) and smart conveyors, which are powered by HMI/SCADA systems, bringing real-time visibility, intelligent control, and adaptive automation to the backbone of modern logistics.

Because in a world where every second counts, the difference between keeping up and falling behind comes down to how intelligently you move.

From Movement to Intelligence: The Evolution of Conveyor Systems

HMI (Human-Machine Interface) has long been the real-time nerve center of conveyor operations, keeping operators informed, equipment protected, and production running predictably. For decades, it has provided critical visibility into conveyor speed, routing, and system diagnostics across manufacturing and warehousing environments.

But the landscape is changing.

Between 2026 and 2030, the global conveyor market is rapidly shifting from traditional, fixed-speed systems to smart, modular, and data-driven solutions. While the overall market is expected to grow from approximately $7–$10 billion in 2026 to over $12–$13 billion by 2030, the smart conveyor segment is expanding at a significantly faster pace, with a growth rate of around 11% CAGR. In fact, the smart conveyor market alone is projected to grow from $2.9 billion in 2025 to more than $9 billion by 2036.

This shift reflects a fundamental change in operational expectations.

Traditional conveyors were designed to move products from point A to point B efficiently, but are largely static.

Smart conveyors transform that motion into intelligent, adaptive operations. By integrating IoT sensors, AI, and real-time analytics, they continuously optimize routing, adjust speeds, and anticipate maintenance needs, without waiting for human intervention.

The impact is significant:

Intelligence & Connectivity: Smart conveyors communicate in real time, leveraging IoT and AI to track, diagnose, and coordinate across systems, while traditional conveyors rely on fixed logic and manual oversight.

Adaptability: Instead of fixed speeds and paths, smart systems dynamically respond to changing production demands, product variations, and bottlenecks.

Predictive Maintenance: Sensor-driven insights detect wear before failure occurs, reducing downtime and eliminating reactive maintenance.

Operational Visibility: Real-time data delivers full transparency into performance and product flow, far beyond checkpoint-based tracking.

Precision Handling: Advanced motion control enables smoother, more accurate handling, critical for delicate or high-value products.

While traditional conveyors still serve well in straightforward, repetitive applications, today’s operations demand more. Speed, flexibility, and data-driven performance are now essential. In this environment, smart conveyors are powered by modern HMI/SCADA systems. They are taking center stage.

Robots or Conveyors: Choosing the Right Fit for Your Operation

At the same time, autonomous mobile robots (AMRs) are rapidly reshaping material handling.

The market is projected to grow from just under $5 billion in 2024 to $14 billion by 2030, driven largely by logistics and manufacturing applications. Order fulfillment robots alone are expected to account for nearly 50% of shipments by the end of the decade, fueled by continued growth in e-commerce and warehouse automation.

So how do you decide between robots and conveyors?

It starts with understanding your operational priorities.

From a cost perspective, AMRs can be attractive for smaller, flexible deployments. However, as fleets scale, costs can increase quickly. Conveyors may require a higher upfront investment, especially for long distances or high-speed applications, but both solutions typically deliver ROI within 1 to 5 years.

The real distinction comes down to flexibility versus throughput:

AMRs excel in flexibility. They dynamically adjust workflows, transport items to different destinations, collaborate with other robots, and navigate around obstacles, all without fixed infrastructure.

Conveyors excel in throughput. High-speed systems such as shoe sorters, tilt trays, and motorized drive roller (MDR) are engineered to move thousands of items per hour with exceptional consistency and efficiency.

Robotics technology continues to advance, becoming smarter, safer, and more capable, but it can still introduce additional complexity and require specialized training. Conveyors, by contrast, remain a proven and highly reliable backbone for high-volume operations.

In reality, the most effective operations do not choose one over the other; they combine both, using conveyors for speed and volume, and AMRs to introduce flexibility and dynamic movement.

If you would like to learn more about using ADISRA SmartView with AMR robots, check out our blog here.

The Unifying Layer: HMI/SCADA

At the center of both approaches is HMI.

For AMRs, HMI serves as the operator’s interface into the robotic system, accessible through tablets, web dashboards, or mobile devices. It enables real-time monitoring, task assignment, route management, and performance analysis, while improving usability, safety, and operational efficiency.

HMIs in smart conveyor systems serve as intuitive, real-time dashboards that connect operators directly to PLCs (Programmable Logic Controllers). Through touchscreen interfaces, they enable continuous monitoring, control, and rapid troubleshooting. By providing real-time insights into package counts, system performance, and motor status, HMIs empower operators to make quick, informed adjustments that improve efficiency and keep operations running smoothly.

As automation continues to evolve, the real advantage lies not in choosing robots or conveyors, but in how intelligently you connect, control, and optimize them.

Whether you are operating fixed conveyor lines, deploying smart conveyors, or scaling AMR fleets, one requirement remains constant:

A unified control and visualization platform.

Bringing It All Together with ADISRA SmartView and InsightView

Modern material handling demands more than automation; it requires coordination, intelligence, and visibility across every system. ADISRA SmartView and InsightView deliver exactly that.

ADISRA SmartView provides a unified HMI/SCADA platform to monitor, control, and optimize your entire operation, from traditional conveyor lines to smart conveyors and autonomous mobile robot (AMR) fleets, all within a single, scalable environment.

What ADISRA SmartView Delivers

– Seamless Connectivity to IIoT and Real-Time Data

Built-in drivers connect directly to sensors such as RFID, barcode scanners, and vision systems, enabling real-time tracking of product position, size, weight, and orientation across the conveyor system.

– Built-In Intelligence for Smarter Decisions

A native rule-based expert system enables predictive maintenance by analyzing data like vibration, motor temperature, and power consumption, helping prevent failures before they occur.  It also supports intelligent automation, such as dynamic sorting based on destination, size, or weight.

– Decentralized Intelligence at the Edge

Deployable on Windows or Linux, even in headless environments, ADISRA SmartView enables local processing at conveyor segments. This allows for immediate, autonomous decisions like routing, speed adjustments, and collision avoidance without relying on a central server.

– Seamless Integration Across Systems

Easily integrates with Warehouse Management Systems (WMS), ERP platforms, and other enterprise systems, creating a connected, end-to-end automation ecosystem.

Extending Intelligence with InsightView

While ADISRA SmartView drives real-time control and local intelligence, InsightView extends that capability with enterprise-level analytics and optimization.

– Energy Management and Sustainability

InsightView includes advanced energy dashboards that optimize machine operation based on real demand. It enables scheduling of energy-intensive processes during off-peak hours, reducing costs and environmental impact while supporting sustainability goals.

– OEE and Productivity Analytics

InsightView delivers powerful Overall Equipment Effectiveness (OEE) analytics for smart conveyor systems. By leveraging data collected through ADISRA SmartView and IIoT-connected devices, it provides global visibility into performance, availability, and efficiency, without manual data collection.

– Edge-to-Enterprise Intelligence

ADISRA SmartView handles real-time data collection and local analytics at the edge, while InsightView aggregates that data across machines, lines, and facilities, delivering actionable, enterprise-wide insights.

Driving Efficiency Through Smarter Energy Use

Energy efficiency is no longer optional; it is a competitive advantage.

Smart conveyor systems, powered by ADISRA, optimize energy usage through intelligent controls and on-demand motor activation. This reduces unnecessary power consumption, minimizes component wear, and lowers operating costs, all while maintaining high throughput.

The result is a more sustainable operation with a smaller carbon footprint, without compromising performance.

Conclusion: From Automation to Intelligence

Material handling is no longer just about moving products; it is about moving them intelligently.

As conveyors become smarter and AMRs more prevalent, the real advantage lies in how well these systems are connected, optimized, and controlled. Operations that rely on disconnected tools and reactive processes will struggle to keep up with rising demand, increasing complexity, and the need for real-time decision-making.

The future belongs to operations that are unified, intelligent, and data-driven.

With ADISRA SmartView and InsightView, you gain more than visibility; you gain a platform that brings together conveyors, smart conveyors, and AMRs into a coordinated, adaptive system. From edge-level control to enterprise-wide analytics, ADISRA enables you to improve throughput, reduce downtime, optimize energy usage, and scale with confidence.

Discover how ADISRA SmartView and InsightView can transform your material handling operations into a connected, intelligent system.

Download ADISRA SmartView here, and start building a smarter, more agile operation.

Interested in improving productivity and energy management? Request an InsightView account at info@adisra.com.

If you would like to discuss your specific requirements, you can also request a private consultation and personalized demonstration here.

Join our upcoming webinar, see details below.

Is Linux part of your automation strategy?  Join us to discover how ADISRA SmartView enables industrial applications on the Linux platform.  It is the future!

ADISRA SmartView on Linux: Flexible HMI/SCADA for Modern Industrial Systems  

In a world increasingly shaped by proprietary ecosystems and large technology platforms, Linux continues to quietly grow as a powerful alternative. While Windows still dominates the desktop market with approximately 73.72% global market share, Linux is rapidly expanding across industrial systems and edge computing.

According to Research and Markets, the Linux operating system market is expected to reach $18.73 billion by 2029. In industrial automation, adoption is already accelerating. SQ Magazine reports that Linux-based PLCs represent 33.1% of newly deployed systems, and 71.9% of edge AI inference workloads run on Linux.

These trends make one thing clear: Linux is becoming a critical platform for modern industrial automation.

Join us for this upcoming webinar where we will demonstrate how to build scalable and robust HMI/SCADA applications using ADISRA SmartView on Linux.

During the session, we will cover:

– Design considerations for Linux deployments.
– Connectivity & Integration – bridging PLCs and databases.
– Security & Maintenance best practices for Linux environments
– Remote Management of your ADISRA SmartView application.
– Edge AI Integration – running an AI expert system using built in rule-based system for predictive maintenance

If Linux is part of your automation strategy, or will be soon, this webinar will show you how ADISRA SmartView enables industrial applications on the Linux platform.

Join us on 26 March 2026, at 

7:30 am PDT
9:30 am CDT (Austin, Texas) 10:30 am COT & EDT 2:30 p.m. UTC (Coordinated Universal Time)
3:30 pm CET
4:30 pm EET & SAST
9:30 pm WIB
10:30 pm – SGT

Register for the webinar here.

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC.

© 2026  ADISRA, LLC.   All Rights Reserved.

One of the things we value most at ADISRA is hearing from our customers, partners, their customers, and anyone with a curiosity about our products. Each question brings new ideas, sparks creative solutions, and helps us identify opportunities to further improve our documentation and web content.

Over time, we have observed that many of these questions are shared by others across the ADISRA community. Whether the topic involves alarm management, templates, scripting, dashboards, or trend configuration, other users are likely exploring similar challenges.

In the past, we have published several Q&A blogs, and we have been encouraged by the number of questions customers continue to send us. It is clear that many readers find this format helpful, so we created the “Dear ADISRA” Q&A series to make it easier to share answers and insights with the broader community.

We encourage you to keep the questions coming. We look forward to hearing from you (info@adisra.com).

In this edition, we will look at the following question:

Is it possible to configure the alarm screen button to blink red when a new alarm occurs, and then stop blinking once the alarm screen opens? The goal is to clearly notify the SCADA operator that a new alarm has been generated.

ADISRA provides a sample application for ADISRA SmartView version 4.1.5.1 that demonstrates this functionality. The application uses a Service that checks the number of active, normalized, and acknowledged alarms every second. This means the example not only detects newly activated alarms, but also monitors alarms that have been normalized or acknowledged, ensuring the operator is notified whenever the alarm state changes.

When the Alarm screen is opened, the application reads and stores the “last visualized” alarm values. While the Alarm screen is closed, these “last visualized” tags are not updated, while the tags monitored by the Service continue to update continuously.

By comparing these values, the system can detect differences between the current alarm states and the last visualized values, which triggers the blinking alarm notification to alert the operator that something has changed in the alarm system.

Below is a short video demonstrating how the application works.

In this application:

• We created 10 tags to simulate alarms within the system.
• The application includes two screens. The main screen displays the alert notification for new alarms, while the second screen contains the Alarm Object.

The image below illustrates the scripts implemented in the On Open and On While events to retrieve the current active alarm information. To accomplish this, we used the SVAlarms system function.

The purpose of this approach is to capture and store the current alarm values while the Alarm screen is open. When the Alarm screen is closed, the application stops updating these stored values. This allows the system to compare the stored values with the continuously updated alarm data and determine whether any alarm state changed while the screen was closed.

We created a service called “MonitorAlarms” that uses the same system functions described above. The values returned by these functions are written to a separate set of tags, allowing the system to continuously monitor and compare changes in alarm status.

The second service, “DetectNewAlarms,” compares the two groups of tags, those updated through the OnWhile script and those updated by the MonitorAlarms service, to identify any differences. This comparison allows the application to detect when new alarms or changes in alarm state occur.

The Example of Alarm Indicator blinks sample application is available here.

How can users filter, sort, and dynamically adjust the display of alarms in ADISRA SmartView? For example, can operators sort alarms by priority or date, configure relative or absolute time ranges for alarm history, apply column-based filters, and use tags to control the displayed alarm range dynamically?

ADISRA SmartView provides flexible filtering capabilities to help users focus on the most relevant alarm and event information. The Filter function allows users to control which rows are displayed in the Alarm/Event or MultiTagViewer objects by specifying property values.  By applying these filters, users can refine the displayed data to highlight specific alarm conditions, events, or operational states, making it easier for operators to quickly identify and respond to important system information.

The Alarm Object also includes several built-in filtering and organization features. For example, users can easily sort alarms by priority or date, helping operators quickly identify the most critical or most recent alarms.

There is also an option to configure the alarm history range using either relative or absolute time settings. Additionally, users can add tags to adjust the time range dynamically, so the displayed alarm history updates automatically based on system conditions or user-defined parameters.

In alarm filtering, even when using an absolute filter, you can place an @ symbol in front of the date to indicate that the value should be treated as an expression rather than a fixed date.

When @TagName is used, it tells the system to reference the current value of that tag dynamically. Instead of treating the entry as static text or a constant value, ADISRA SmartView evaluates the tag at runtime and applies its current value. This approach allows filters and configurations to adapt automatically as the tag values change.

You can also apply filters by specifying the values you want to display within a particular column, allowing the alarm list to be refined based on selected criteria.

An Alarm & Event History demo illustrating how to apply alarm filtering is available here.

How can ADISRA SmartView templates be used to organize displays and dynamically present different system states or equipment information?

ADISRA SmartView provides a flexible approach to visualization through predefined display templates and the ability to create custom templates tailored to each project’s needs. This allows engineers to design applications that are both structured and scalable.

For example, when organizing a facility such as a multi-floor building, users can create independent screens that are easily accessed through navigation buttons (e.g., Floor 2, Floor 3, Floor 4). This approach helps organize indicators and operational information clearly and intuitively.

When the goal is to visualize different system states based on variable values, ADISRA SmartView provides tools such as the SmartMessage object. This object allows multiple states to be associated with a single tag, enabling users to define:

– Specific text messages

– Text colors

– Background colors

– Visual animations (such as blinking)

– Distinct visual styles for each condition

In addition, ADISRA SmartView supports both Template Objects and Screen Templates.

A Template Object is a reusable component that can be placed multiple times on the same screen. These objects support indirect object tags, allowing each instance to operate with different tags while maintaining the same design and logic.

For more information about Template Objects, please watch the following video.

A Screen Template, on the other hand, functions as a generic screen that can be dynamically opened with different parameters. By using indirect screen tags, the same screen structure can display information for different devices, equipment, or contexts.

For more information on Screen Templates, please refer to the following whitepaper.

This template-based architecture enables developers to build more scalable, organized, and easier-to-maintain HMI/SCADA applications, while significantly reducing engineering time and improving consistency across the project.

If you are interested in learning more about templates, we offer a blog on the topic here, as well as a one-hour webinar that explores both Template Objects and Screen Templates in greater detail, available here.

How can ADISRA SmartView save and restore trend configurations, including pen settings and scale ranges, so operators can maintain their preferred visualization settings?

ADISRA SmartView provides flexible scripting capabilities that allow users to save and restore trend configurations, ensuring that operator preferences remain consistent across sessions.

In the example shown above, the application demonstrates how trend pen configurations are automatically saved and reloaded as changes are made. This includes adjustments such as pen thickness, color, and scale settings. Additionally, the application includes an option to modify the minimum and maximum scale values for two float-tag pens, which are also stored in the configuration.

a) SaveConfig

The SaveConfig button executes a script that captures both the manual changes made directly in the trend object (such as pen color and thickness) and the minimum and maximum scale values defined for the two float pens.

All of this information is stored in a configuration file named trendconfig.json, located in the Application folder. This approach ensures that all visualization preferences are preserved for future use.

b) LoadConfig

When the page loads, the application checks whether the trendconfig.json file exists. If the file is found, the configuration is automatically loaded, restoring the previously saved pen settings and scale values.

The JSON file is saved in the Application folder.

This file stores all configuration settings, including pen properties such as thickness, marker style, and color, as well as minimum and maximum values and other related parameters.

This method allows operators to return to the same trend visualization settings each time the application is opened, improving usability and maintaining consistency in data analysis.

To download this example, see the Example Features section under the title “Save and Load Trend Configuration,” available here. 

Conclusion

This concludes our first Dear ADISRA blog, and we hope you found it informative and helpful.

If you have a question you would like us to address in a future Dear ADISRA post, please send it to info@adisra.com. Your question may be featured in one of our upcoming blogs.

If you have not yet downloaded the latest release of ADISRA SmartView V4.1.5.1, you can do so here. If you are new to ADISRA SmartView and would like to see it in action, we would be happy to schedule a private demonstration. Please request one here.

Finally, we invite you to join us for our upcoming webinar on developing ADISRA SmartView applications for Linux. Additional information and registration details are provided below.

Please join us for our webinar entitled:

ADISRA SmartView on Linux: Flexible HMI/SCADA for Modern Industrial Systems  

In a world increasingly shaped by proprietary ecosystems and large technology platforms, Linux continues to quietly grow as a powerful alternative. While Windows still dominates the desktop market with approximately 73.72% global market share, Linux is rapidly expanding across industrial systems and edge computing.

According to Research and Markets, the Linux operating system market is expected to reach $18.73 billion by 2029. In industrial automation, adoption is already accelerating. SQ Magazine reports that Linux-based PLCs represent 33.1% of newly deployed systems, and 71.9% of edge AI inference workloads run on Linux.

These trends make one thing clear: Linux is becoming a critical platform for modern industrial automation.

Join us for this upcoming webinar where we will demonstrate how to build scalable and robust HMI/SCADA applications using ADISRA SmartView on Linux.

During the session, we will cover:

– Design considerations for Linux deployments.
– Connectivity & Integration – bridging PLCs and databases.
– Security & Maintenance best practices for Linux environments
– Remote Management of your ADISRA SmartView application.
– Edge AI Integration – running an AI expert system using built in rule-based system for predictive maintenance

If Linux is part of your automation strategy, or will be soon, this webinar will show you how ADISRA SmartView enables industrial applications on the Linux platform.

Join us on 26 March 2026, at 

7:30 am PDT
9:30 am CDT (Austin, Texas) 10:30 am COT & EDT 2:30 p.m. UTC (Coordinated Universal Time)
3:30 pm CET
4:30 pm EET & SAST
9:30 pm WIB
10:30 pm – SGT

Register for the webinar here.

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC.

© 2026  ADISRA, LLC.   All Rights Reserved.

Industrial cybersecurity has entered a more exposed, strategic phase, shaped by the hard lessons manufacturing organizations learned throughout 2025. A recent article from Manufacturing Business Technology, titled “Number of ICS/OT Cyber Incidents Raises Alarms” (November 20, 2025), highlights just how serious the situation has become.

According to the report:

– 21.5% of organizations experienced a cyber incident that impacted their Industrial Control Systems (ICS) or Operational Technology (OT).

– 37.9% of those incidents were linked to ransomware attacks, demonstrating how aggressively attackers are targeting industrial environments.

– 40.3% of incidents resulted in operational downtime, directly affecting production and business continuity.

These numbers reinforce a growing reality: cybersecurity is no longer just an IT concern. For manufacturers, it has become a critical operational issue that directly impacts safety, uptime, and profitability.

Manufacturing Has Become the Primary Target

The scale of the threat becomes even clearer when looking at broader industry data. According to the latest IBM X-Force report, the manufacturing sector accounted for 27.7% of all cyberattacks in 2025, the highest share among all industries analyzed.

The report also highlights the global nature of these attacks:

– Asia-Pacific: 68% of manufacturing-related attacks

– North America: 23%

– Europe: 5%

– Latin America: 2%

Many of these incidents involved malware designed to disrupt operations or enable financial extortion, representing 45% of observed attacks. Cybercriminals increasingly recognize that operational disruption in manufacturing environments can quickly translate into financial leverage.

Why Small-to-Mid-Market Manufacturers Are Increasingly at Risk

For small-to-mid-market manufacturers, the challenge is becoming even more significant. Cyber attackers are no longer focusing only on large enterprises with deep pockets. Increasingly, they are using automation and artificial intelligence to target small-to-midsize businesses (SMBs) at scale.

Recent security research from the Data Breach Observatory confirms this shift. Their findings show that four out of five small businesses have experienced a recent data breach, highlighting how frequently SMBs are now being targeted. In fact, SMBs were the primary target of hackers in 2025, accounting for 70.5% of the data breaches identified in the report. Companies with between 1 and 249 employees were the most vulnerable to cybersecurity incidents throughout the year.

While industries such as retail and media/entertainment experienced the highest number of attacks, SMB manufacturers are also increasingly exposed, particularly as their operations become more digitally connected.

At the same time, manufacturing plants are rapidly increasing connectivity as they adopt technologies such as:

– AI-driven analytics
– Cloud platforms
– Integrated MES and OT systems
– Connected HMI/SCADA environments

These technologies provide clear benefits by improving operational efficiency, visibility, and decision-making. However, they also expand the potential attack surface inside the plant.

Every new connection between a machine, an HMI/SCADA system, an analytics platform, or an enterprise application represents another potential entry point for cyber threats.

The implication is clear: as manufacturers pursue AI-enabled initiatives and smarter digital operations, connectivity increases, and with it comes greater exposure.

Industrial cybersecurity can no longer be treated as an afterthought. It must be designed into the architecture of modern automation systems from the start, ensuring that operational innovation does not introduce unacceptable risk.

What Can We Learn from 2025?

It is difficult to say that any organization can completely avoid a cybersecurity incident. However, there are practical steps manufacturers can take to reduce their risk and strengthen their operational resilience significantly.

Some of the most important lessons from 2025 include the following cybersecurity practices that manufacturers, especially small-to-mid-market organizations, should implement to strengthen their defenses:

– Improve visibility and network segmentation.

Manufacturers must maintain clear visibility into their OT environments and segment critical systems so that a breach in one area does not spread across the entire operation. The Purdue Model remains a useful framework for industrial environments because it emphasizes segmentation, defense-in-depth, and risk management across multiple layers of the control architecture (see the blog by Fortinet).  The use of firewalls on external endpoints and between segments is critical for preventing unauthorized access and extracting data from the manufacturing plant. 

– Identify and manage connected assets.

Organizations should maintain an accurate inventory of all connected equipment, including PLCs, HMIs, servers, engineering workstations, and network devices. Mapping these assets helps organizations understand what is connected to the network and identify potential vulnerabilities. Unused network ports, services, and interfaces should be disabled to reduce the overall attack surface.

– Implement secure remote access.

Remote connectivity is often necessary for system integrators, vendors, and maintenance teams, but it must be tightly controlled. Organizations should use dedicated secure remote access solutions that support strong authentication, session logging, monitoring, and granular, time-limited access for external users.

– Inspect inbound files and connected devices.

Files, USB drives, laptops, and external devices entering the plant environment should be scanned and verified before being allowed to connect to operational systems.

– Secure wireless networks.

Wi-Fi networks should be encrypted, hidden when possible, and protected with strong passwords and proper network access controls to prevent unauthorized access to plant systems.

– Enable multi-factor authentication (MFA).

Multi-factor authentication significantly reduces the risk of unauthorized access by requiring an additional verification step, such as a one-time passcode, hardware security key, or biometric login.

– Maintain strong password hygiene.

Organizations should enforce strong password policies, avoid password reuse across accounts, and monitor for compromised credentials. Password management tools and dark web monitoring services can help identify exposed credentials before they are exploited.

– Implement a 3-2-1 backup strategy.

Maintain three copies of critical data, stored on two different media types, with at least one copy kept offline or offsite. Regular, automated backups ensure that operations can be restored in the event of ransomware or other disruptive attacks.

– Train employees regularly.

Conduct ongoing cybersecurity training and simulation exercises to help employees recognize phishing attempts, social engineering attacks, and emerging threats, including AI-generated phishing emails and deepfakes.

For additional guidance, the Cybersecurity & Infrastructure Security Agency (CISA) provides practical cybersecurity resources and recommendations specifically designed to help small businesses strengthen their security posture.

Securing SCADA and HMI Systems: A Holistic Approach

SCADA (Supervisory Control and Data Acquisition) and HMI (Human-Machine Interface) systems play a critical role in the daily operations of many small- to mid-market manufacturing plants. These systems provide visibility into processes, enable operators to interact with equipment, and help maintain stable, efficient production.

As the cybersecurity lessons from 2025 demonstrate, industrial environments are becoming increasingly attractive targets for cyberattacks. Because HMI and SCADA platforms sit at the center of plant operations, they must be designed and deployed within a secure automation architecture.

However, protecting these systems cannot rely solely on the security features of a single software platform. Effective protection requires a holistic approach across the entire operational technology (OT) environment, including network segmentation, secure remote access, asset visibility, strong authentication, disciplined operational practices, and employee awareness.

For manufacturers, cybersecurity must be designed into the architecture of modern automation systems from the beginning, ensuring that increased connectivity, AI-driven analytics, and digital transformation initiatives do not introduce unacceptable operational risk.

At ADISRA, cybersecurity is a key design consideration in our software platforms, helping manufacturers deploy secure and scalable industrial visualization and analytics solutions.

Try ADISRA SmartView: Download a free trial of our HMI/SCADA software on our website here.

Explore InsightView and KnowledgeView: Request a temporary account at info@adisra.com to experience our OEE analytics and predictive maintenance platforms.

Visit our website at: www.adisra.com

If you are interested in learning more about ADISRA SmartView, we invite you to attend our upcoming webinar. Additional details are provided below.

ADISRA SmartView on Linux: Flexible HMI/SCADA for Modern Industrial Systems  

 In a world increasingly shaped by proprietary ecosystems and large technology platforms, Linux continues to quietly grow as a powerful alternative. While Windows still dominates the desktop market with approximately 73.72% global market share, Linux is rapidly expanding across industrial systems and edge computing.

According to Research and Markets, the Linux operating system market is expected to reach $18.73 billion by 2029. In industrial automation, adoption is already accelerating. SQ Magazine reports that Linux-based PLCs represent 33.1% of newly deployed systems, and 71.9% of edge AI inference workloads run on Linux.

These trends make one thing clear: Linux is becoming a critical platform for modern industrial automation.

Join us for this upcoming webinar where we will demonstrate how to build scalable and robust HMI/SCADA applications using ADISRA SmartView on Linux.

During the session, we will cover:

– Design considerations for Linux deployments.
– Connectivity & Integration – bridging PLCs and databases.
– Security & Maintenance best practices for Linux environments
– Remote Management of your ADISRa SmartView application.
– Edge AI Integration – running an AI expert system using built in rule-based system for predictive maintenance

If Linux is part of your automation strategy, or will be soon, this webinar will show you how ADISRA SmartView enables industrial applications on the Linux platform.

Join us on March 26th, at

7:30 am PDT
9:30 am CDT
3:30 pm CET
4:30 pm EET
9:30 pm WIB
10:30 pm – SGT

Register for the webinar here.

We look forward to seeing you there.

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of

© 2026  ADISRA, LLC.   All Rights Reserved.

Advanced manufacturers are facing a turning point in their workforce. Skilled trades require years to master, yet experienced workers are retiring faster than they can be replaced. The proportion of manufacturing employees over age 55 has more than doubled in the past two decades, accelerating the loss of deep institutional expertise.

The result is more than a labor shortage. It is a knowledge gap.

As veteran employees leave, critical “tribal knowledge”, the unwritten expertise that keeps operations running smoothly, often leaves with them. Manufacturers are increasingly turning to AI-enabled knowledge management tools to address this challenge. Industry analysts project that more than half of manufacturers will adopt AI-driven tools by 2027 to help reskill workers and preserve expertise.

But this raises a deeper question:

What is the most effective way to capture and operationalize tribal knowledge, structured rule-based expert systems, or emerging agentic AI models?

AI Generated

Understanding the Differences: Generative AI, Agentic AI, and Rule-Based Expert Systems

Generative AI excels at content creation. It produces text, images, code, and summaries in response to prompts. While powerful for communication and analysis, it is not inherently designed to preserve structured operational expertise or enforce decision logic on the plant floor.

Agentic AI focuses on execution. It represents a class of autonomous systems designed to act independently to pursue defined goals. Rather than simply generating responses, agentic AI can plan, sequence, and carry out multi-step tasks across connected systems and workflows. It evaluates conditions, determines appropriate actions, and executes them with minimal human intervention, shifting AI from passive assistance to active operational participation.

A rule-based expert system formalizes tribal knowledge by translating expert reasoning into executable if–then–else logic embedded directly within the control and monitoring environment. Rather than depending on individual memory or informal knowledge transfer, proven best practices are codified into structured rules that evaluate real-time data, trigger guided actions, and ensure consistent, repeatable responses across operations.

Because the logic is transparent and deterministic, it can be tested, audited, and refined over time. The expertise of senior personnel becomes embedded in the system itself, scalable across machines, lines, and facilities, ensuring operational continuity even as the workforce changes.

The strategic question for manufacturers is not about content creation. It is about operational reliability: should tribal knowledge be captured through deterministic rule-based frameworks, adaptive agentic systems, or a thoughtful combination of both?

AI generated

The Advantages of Rule-Based Expert Systems

A rule-based expert system captures human expertise by translating domain knowledge into structured, executable logic, typically in the form of conditional rules such as if–then-else statements. Instead of relying on informal mentoring or individual memory, expert reasoning becomes embedded directly into the system itself.

When applied to the challenge of preserving tribal knowledge, rule-based expert systems offer several distinct advantages:

Deterministic and Reliable

Rule-based systems produce the same output for the same input every time. This determinism makes them highly reliable in industrial environments where safety, compliance, and operational consistency are critical.

Transparency and Explainability

Every decision can be traced back to a specific rule. The system can clearly show why a recommendation or action was triggered, which supports auditing, validation, and regulatory requirements.

Operational Stability and Predictability

Because the logic is predefined, outcomes follow a traceable sequence of states. There is no ambiguity in how conclusions are reached, reducing uncertainty in high-stakes environments.

No Runtime Learning Required

The expertise is already codified. The system does not need to “learn” or reinterpret data during execution, making performance stable and predictable.

Consistency Across Teams and Facilities

The same rules are applied uniformly across machines, lines, and sites, eliminating human variability and ensuring standardized procedures.

Targeted Scope and Rapid Response

For well-defined problems, rule-based systems operate efficiently without processing massive datasets.

Ease of Maintenance

Individual rules can be updated, refined, or expanded without redesigning the entire system. As processes evolve, the knowledge base can evolve with them.

AI Generated

The Challenges of Rule-Based Expert Systems

While rule-based expert systems offer stability and transparency, they are not without limitations. Understanding these constraints is essential when determining where they fit within a broader industrial intelligence strategy.

Rigidity and Limited Adaptability

Rule-based expert systems operate strictly within the boundaries of their predefined logic. If a situation falls outside programmed conditions, the system cannot adapt or infer a solution. This makes them highly reliable within defined parameters but less flexible in novel or rapidly evolving scenarios.

Knowledge Acquisition Requires Upfront Effort

Capturing tribal knowledge is not automatic. It requires deliberate collaboration with subject matter experts to translate real-world decision-making into structured, executable rules. This upfront effort can be time-intensive, especially when critical expertise is undocumented or distributed across multiple individuals.

However, tools matter. In ADISRA SmartView, the intuitive graphical tree-structure design (shown below) simplifies rule creation and organization. This structured visual approach makes entering, editing, and managing rules straightforward, reducing complexity while preserving the integrity of expert knowledge.

Manual Rule Creation

Unlike machine learning systems that derive patterns from large datasets, rule-based expert systems rely on explicit rule authoring. Developing and validating those rules requires deliberate engineering and domain expertise.

Scalability and Rule Complexity

As rule bases grow, they can become increasingly complex. Without careful design and governance, systems may experience “rule sprawl,” where overlapping, redundant, or conflicting rules accumulate. Over time, this can create maintenance challenges and technical debt if not properly managed.

Brittleness in Unstructured Environments

Because intelligence is limited to what has been explicitly encoded, rule-based expert systems can struggle with abstract patterns, ambiguous inputs, or unforeseen edge cases. They excel at well-defined operational problems but are less suited to environments that require interpreting highly unstructured data.

Governance and Lifecycle Management

Maintaining large rule sets requires structured oversight. Version control, validation processes, and centralized governance are critical to preventing uncontrolled growth and preserving system integrity.

AI Generated

Agentic AI: The Next Evolution in Autonomous Intelligence

As manufacturers explore solutions beyond deterministic logic, attention is shifting toward agentic AI, an emerging class of systems designed to operate with greater autonomy.

Agentic AI represents an evolution beyond traditional generative AI models. While generative AI focuses primarily on producing content in response to prompts, agentic systems are designed to perceive conditions, reason through options, and act toward defined goals. These systems can operate semi-autonomously or fully autonomously, integrating with software platforms, data sources, and workflows to complete multi-step tasks with limited human intervention.

Unlike chat-based tools that respond reactively, agentic AI is proactive. It can monitor environments, evaluate changing conditions, make decisions based on objectives, and trigger actions across connected systems.

For manufacturers, this introduces a new dimension of intelligence; one that moves beyond codified logic and toward adaptive, goal-driven execution.

AI Generated

The Advantages of Agentic AI

Agentic AI introduces a different type of capability; one centered on autonomy, adaptability, and continuous learning. Where rule-based systems rely on predefined logic, agentic systems are designed to observe, reason, and act within dynamic environments.

When applied to the challenge of capturing tribal knowledge, agentic AI offers several compelling advantages:

Active, Real-Time Observation

Rather than relying solely on documented procedures, agentic systems can observe workflows in real time. By analyzing multimodal inputs, such as voice interactions, screen activity, logs, and operational data, they can extract expertise directly from how experienced personnel perform their work.

Continuous Operation

Unlike human experts, AI agents can operate 24/7. They can monitor systems, document workflows, and analyze patterns continuously without interruption, expanding the window for knowledge capture.

Handling Ambiguity and Novelty

Where fixed rule sets perform best in well-defined conditions, agentic AI can evaluate multiple signals, logs, and variables to assess what is most likely occurring, even in situations that were not explicitly preprogrammed.

Automatic Knowledge Codification

Agentic AI can transform informal, unwritten expertise into structured digital work instructions or playbooks. As processes evolve, these digital artifacts can be updated dynamically rather than remaining static.

Self-Refining Intelligence

Because these systems learn from ongoing interactions and feedback, they can improve over time, building a continuously evolving knowledge base that becomes more robust with use.

Adaptability to Change

If procedures are modified, systems updated, or new operational constraints introduced, an agentic model can adjust guidance and notify relevant teams, keeping institutional knowledge aligned with current realities.

AI Generated

The Challenges of Agentic AI

While agentic AI introduces powerful capabilities in autonomy and adaptability, it also presents meaningful risks, particularly in industrial environments where safety, compliance, and reliability are non-negotiable.

Difficulty Capturing Tacit and Intuitive Knowledge

Tribal knowledge is often subtle, situational, and deeply contextual. It lives in conversations, instincts, and years of lived experience. While agentic systems can observe workflows and analyze data, they may struggle to fully capture the reasoning behind decisions, the “why” rather than just the “what.” Nuance can be lost in translation.

Non-Deterministic Behavior

Unlike rule-based expert systems, agentic AI is probabilistic. The same prompt or situation may produce different outcomes unless tightly constrained. This variability can make auditing, validation, and regulatory compliance more complex.

Risk of Hallucinations and Data Distortion

Agentic systems can generate plausible but incorrect outputs, sometimes referred to as hallucinations. In operational contexts, this could mean recommending inappropriate action or incorrectly confirming that a task was completed. When tacit knowledge is externalized into structured outputs, important nuances can also be distorted.

Reliability Concerns in Complex Environments

In large-scale or safety-critical deployments, accuracy and consistency become paramount. Without strong validation layers, outputs may require human review, limiting full autonomy.

Data Quality and “Knowledge Contamination”

If agents learn from incomplete, outdated, or incorrect data sources, the resulting guidance may embed those flaws. Poor data hygiene can propagate bias or misinformation across workflows.

Maintenance and Lifecycle Management

Agentic systems require ongoing supervision. Models must be updated, permissions reviewed, and workflows tested regularly to ensure alignment with evolving operational realities.

AI Generated

A Hybrid Model: Deterministic Guardrails with Adaptive Intelligence

Rather than treating rule-based expert systems and agentic AI as competing technologies, manufacturers can unlock greater value by integrating them within a structured architecture.

Agentic systems introduce autonomy and adaptability, but they must be deployed responsibly. Effective implementation requires defined permissions, approval workflows, action thresholds, logging, validation procedures, and continuous oversight. Without disciplined governance, even minor configuration changes can cascade across interconnected systems, creating unintended operational risk.

This is where a rule-based expert system becomes foundational. It establishes the guardrails. By encoding validated operational knowledge into deterministic logic, it ensures safety, compliance, and procedural consistency. It clearly defines what must always occur, what must never occur, and how approved responses should be executed under known conditions. In safety-critical industrial environments, this structured and predictable framework is not optional; it is essential.

Agentic AI, layered above or alongside that framework, can provide adaptive capabilities. It can observe workflows, analyze patterns, detect anomalies, and recommend actions in scenarios that extend beyond predefined rule boundaries. It can assist with data gathering, workflow orchestration, and contextual interpretation across systems.

In this hybrid architecture:

• The rule-based system governs execution.
• The AI layer augments insight.
• Deterministic logic enforces operational integrity.
• Adaptive models surface emerging patterns and recommendations.

Machine learning models can contribute predictive and analytical intelligence to this structure. These models can identify trends, detect anomalies, and forecast outcomes based on historical data. However, their outputs should be evaluated within a governed framework. When integrated properly, predictive models inform decisions, while rule-based logic ensures those decisions remain aligned with operational standards.

This layered approach transforms tribal knowledge into structured, enforceable logic, while still allowing the system to evolve as new data, patterns, and operational realities emerge.

The result is not rigid automation. It is controlled intelligence.

Conclusion: From Knowledge Loss to Knowledge Architecture

Manufacturing is at a crossroads.

As experienced workers retire, the industry faces more than a staffing challenge; it risks losing decades of institutional expertise. Tribal knowledge, once passed through mentorship and repetition, must now be captured intentionally and embedded into digital systems.

Generative AI may assist with documentation.

Agentic AI may enhance adaptability and orchestration.

But rule-based expert systems remain uniquely suited to institutionalizing validated operational logic in a transparent, auditable, and repeatable way.

The most resilient strategy is not choosing between them. It is deliberately architecting intelligence; combining deterministic guardrails with adaptive insight.

Manufacturers who treat knowledge capture as a structured design decision, not a reactive technology experiment, will be best positioned to maintain productivity, protect safety, and accelerate innovation in the years ahead.

If you are exploring how to embed tribal knowledge into your HMI/SCADA architecture as you prepare for AI-driven evolution, now is the time to evaluate your approach.

Download ADISRA SmartView here or request a personalized demonstration to see how structured expert systems and evolving AI capabilities can work together inside a modern industrial automation platform here.

Our next ADISRA webinar is coming up on March 26th at 9:30 AM CST.

We will be sharing more details soon, so keep an eye on your inbox.

We look forward to having you join us. You can register here to stay updated on the upcoming webinar topic.

If this blog raised questions about safeguarding tribal knowledge in your organization, please send them to info@adisra.com.

Or if you are evaluating how to architect intelligence responsibly within your control systems, request a private demonstration here. 

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of

© 2026  ADISRA, LLC.  

It is rare to witness so many major global celebrations converging at once. Fat Tuesday brings Carnival and Mardi Gras to life, while the Lunar New Year begins and Ramadan approaches, creating a remarkable and meaningful overlap of traditions, cultures, and faiths around the world.

Because each of these observances follows a different calendar system, their alignment is uncommon. The 2026 convergence is especially notable, shaped by three distinct timekeeping methods: the Islamic lunar calendar (Ramadan), the Chinese lunisolar calendar (Lunar New Year), and the Gregorian-based Christian calendar that determines Easter and, in turn, Mardi Gras. The Lunar New Year begins on the second new moon after the winter solstice. Easter falls on the first Sunday after the full moon or after the vernal equinox. Ash Wednesday occurs 46 days before Easter, and Mardi Gras is celebrated the Tuesday before Ash Wednesday. Ramadan begins with the sighting of the crescent moon, and in 2026, it starts on the evening of February 17.

Across Brazil, Latin America, New Orleans, Asia, the Middle East, and beyond, communities are celebrating, reflecting, preparing, and renewing, all within the same week.

At first glance, these holidays may seem unrelated. They arise from different histories, cultures, and spiritual traditions. Yet when viewed more closely, they share powerful themes: rhythm, renewal, discipline, and community.

And within those shared themes are lessons that translate surprisingly well to the world of Human Machine Interface (HMI) and Supervisory Control and Data Acquisition (SCADA) software, where timing, structure, adaptability, and human connection all play critical roles in building systems that are both resilient and responsive.

Carnival & Mardi Gras: Orchestrated Complexity

The vibrant, often chaotic-seeming atmosphere of Carnival and Mardi Gras is not accidental. It is the result of year-round, meticulous, and highly structured planning. What appears spontaneously is a controlled, engineered, and rehearsed spectacle that transforms entire cities into massive performance spaces.

Behind every parade is:

– Careful planning
– Precise timing – Coordinated choreography
– Structured execution

What appears to be chaos is actually a highly disciplined orchestration.

There are powerful lessons to be learned from Carnival and Mardi Gras when designing HMI/SCADA applications and industrial automation systems.

Structured Orchestration in Industrial Automation

Structured orchestration, whether on a parade route or a plant floor, relies on hierarchical, modular, and real-time control to optimize complex processes.

On a production floor, hundreds or thousands of operations occur simultaneously. Motors start and stop. Valves open and close. Conveyors synchronize with fillers. Sensors generate data. Alarms trigger. Operators respond.

Without structure, this becomes unmanageable, but with proper architecture, it becomes synchronized performance.

The same principles that guide precise parade choreography apply directly to plant floor automation and the design of high-performance HMI/SCADA systems, where synchronization, timing, and coordinated execution determine operational success.

Modular Automation & Reusability

Just as a parade is composed of coordinated units, dance groups, floats, musicians, production systems are built from modular components: conveyors, fillers, cappers, mixers, and packaging stations.

Effective orchestration requires decoupled, reusable modules that can operate independently yet coordinate seamlessly.

In HMI/SCADA design, modularity means:

– Reusable templates
– Standardized symbols
– Encapsulated logic
– Scalable object libraries

ADISRA SmartView was built around this very principle. Its template-driven architecture encapsulates graphics, scripts, tags, and behaviors into reusable, self-contained objects. These templates can be developed and tested independently, then deployed across multiple projects, significantly reducing engineering time while ensuring standardization and consistency throughout the application.

Just as parade organizers do not redesign every float from scratch each year, automation engineers should not rebuild every screen element manually. Modular design drives efficiency and scalability.

For more information on the ADISRA SmartView template design, we invite you to join our webinar on February 26th at 9:30 AM CST. You can register for the session here.

Hierarchical & Decentralized Control

Carnival parades operate within layered coordination. There is central planning at the city level, leadership within each samba school or krewe, and autonomous execution at the performer level.

Industrial automation mirrors this layered structure.

– Enterprise-level systems oversee plant-wide performance.
– SCADA systems coordinate lines and processes.
– HMI and PLCs execute localized machine control.

This hierarchical model balances strategic oversight with decentralized, autonomous execution.

ADISRA SmartView is built to support a layered industrial architecture. It scales seamlessly from edge and machine-level visualization to full SCADA deployments, while integrating with enterprise systems. Whether operating on a local HMI panel, a centralized SCADA server, or connected to InsightView for OEE analytics or KnowledgeView for predictive intelligence, ADISRA SmartView preserves structured control while enabling localized flexibility and autonomy at the edge.

A well-designed automation system, like a well-run parade, requires both coordination and independence.

Real-Time Data Visualization & Operator Clarity

Even the most elaborate parade must be visible and understandable to its audience. Spectators see movement, color, and flow in a coherent, engaging format.

On the plant floor, the “audience” is the operator.

Effective orchestration requires clear, contextual, real-time visibility into system states. Operators must instantly understand:

– Equipment status
– Process health
– Alarm conditions
– Production metrics
– Historical trends

This is where HMI/SCADA principles become critical.

ADISRA SmartView prioritizes intuitive visualization that can be deployed across multiple form factors, from mobile devices and web clients to large-format ANDON displays. Its graphics engine, extensive symbol libraries, and trend objects enable engineers to present PLC data in a clear, contextual, and actionable format. With real-time trending, configurable refresh rates, comprehensive alarm management, and structured navigation, operators receive meaningful insight without being overwhelmed by noise.

Just as parade choreography ensures performers stay in sync, structured visualization ensures operators remain in control.

The deeper lesson from Carnival and Mardi Gras is this:

Large, dynamic systems can be vibrant and powerful, but only when they are structured.

The same is true for modern industrial automation.

As manufacturing environments grow more connected, with increasing integration of edge devices, cloud analytics, and predictive systems, the need for orchestration becomes even more critical.

An HMI/SCADA platform must:

– Support modular and reusable development
– Integrate with third-party packages
– Provide real-time visibility
– Enforce structured control and governance
– Adapt to evolving technology cycles

ADISRA SmartView was built around these principles. It enables engineers to design applications that are not just functional, but orchestrated, where data flows cleanly, systems scale predictably, and operators have clarity in real time.

Lunar New Year: The Year of the Fire Horse: Speed, Transformation, and Intelligent Automation

The Lunar New Year marks the beginning of a new cycle. Homes are cleaned to clear away the old. Accounts are settled. Families gather to reset and prepare intentionally for what lies ahead.

The 2026 Lunar New Year ushers in the Year of the Fire Horse, a rare 60-year cycle associated with intense energy, high momentum, bold innovation, and rapid transformation. The Fire Horse is not cautious. It is decisive. It moves forward with speed and confidence.

For plant floor automation and HMI/SCADA software, the symbolism is striking.

This is a year that calls manufacturers to move from passive monitoring to active, intelligent, rapid-response systems.

It is a reminder that modern industrial environments cannot afford hesitation.

Below are key automation lessons inspired by the Fire Horse, and how modern HMI/SCADA platforms like ADISRA SmartView align with that momentum.

High-Velocity Automation & Intelligent Speed

The Fire Horse symbolizes relentless forward motion.

In manufacturing, machine speeds increase. Production cycles compress. Market demand accelerates. Operators must react faster than ever before.

Traditional HMI dashboards that simply display static values are no longer sufficient. In today’s industrial environments, performance demands more than passive visualization. Modern systems must deliver:

– Real-time data acquisition
– Fast refresh rates
– High-performance trending
– Event-driven alerts
– Integrated rule-based expert system intelligence

Operators should be making informed decisions in milliseconds, not waiting minutes for delayed updates or offline reports.

ADISRA SmartView supports configurable trend refresh rates, real-time alarm management, and scalable data handling across edge and server deployments. Combined with its rule-based expert system capabilities, ADISRA SmartView can move beyond passive visualization to proactive guidance, detecting abnormal conditions and triggering intelligent responses before downtime occurs.

The Fire Horse reminds us: momentum must be supported by intelligent systems.

Transformation: Breaking from Legacy Constraints

The Year of the Fire Horse is sometimes referred to as a “double fire” year, symbolizing the breaking down of outdated structures to make way for stronger, more efficient foundations.

In industrial automation, transformation often means confronting legacy systems that:

– Limit scalability
– Create production bottlenecks
– Restrict integration
– Complicated maintenance
– Lack cybersecurity structure

Many facilities continue to rely on aging HMI platforms that were never designed for today’s connected, data-driven environments.

Transformation does not require chaos; it requires structured modernization.

ADISRA SmartView was designed with modular templates, scalable architecture, and broad driver support to ease migration from legacy systems. Its reusable templates and symbol libraries reduce redevelopment time while enabling modernization without a complete system overhaul.

The Fire Horse energy is not reckless disruption; it is strategic evolution.

In automation, this means modernizing thoughtfully, replacing inefficiency with structured intelligence.

Data-Driven Decision Making & “Red Envelope” Precision

In Lunar New Year traditions, red envelopes symbolize intention and purpose,  deliberate action with clear value.

The Year of the Horse rewards bold, decisive, and calculated action over hesitation.

For HMI design, this means empowering operators with precise, actionable data at the moment of need.

Industrial environments are no longer just monitored; they are optimized in real time.

This requires:

– Edge computing integration
– IIoT connectivity
– Localized analytics
– Structured alarm prioritization
– Context-aware visualization

Operators should not wait for management reports to address issues. They should have immediate access to the information needed to prevent downtime, improve throughput, and maintain quality.

ADISRA SmartView enables this precision by combining real-time visualization with database connectivity, rule-based expert system, and scalable deployment from machine-level HMI panels to enterprise-level SCADA systems. Its architecture supports distributed intelligence, allowing actionable insights to be delivered directly at the machine level.

Precision is not about more data.
It is about the right data at the right moment.

The Fire Horse teaches us that decisive action, powered by clarity, creates momentum.

Ramadan: Discipline, Reflection, and Reconnection with purpose

Ramadan is the ninth month of the Islamic lunar calendar and is regarded by Muslims worldwide as a holy month of fasting, reflection, prayer, and community. It commemorates the period when the Quran is believed to have been revealed to the Prophet Muhammad.

At its core, Ramadan emphasizes focus, simplicity, discipline, and intentional action. These principles, though spiritual in nature, translate remarkably well into the design of modern HMI and SCADA systems.

In many ways, Ramadan offers a blueprint for building more resilient, more thoughtful industrial platforms.

Discipline and Reflection

Ramadan represents a period of discipline and reflection. It is structured and purposeful. It encourages accountability, awareness, and self-evaluation.

In industrial automation, discipline is not optional; it is foundational.

Technology without governance introduces risk. As systems become more connected and data-rich, facilities must carefully manage:

– Alarm fatigue – Cybersecurity threats
– Unauthorized access
– Configuration drift
– Uncontrolled updates

The most advanced features mean little if they are not implemented within a structured framework.

Strong automation systems incorporate:

– Role-based security
– Comprehensive audit trails
– Controlled change management procedures
– Structured deployment processes
– Secure remote access

Discipline is not about restriction; it is about resilience.

Modern HMI/SCADA platforms must provide the guardrails that prevent small oversights from becoming operational disruptions. ADISRA SmartView, for example, supports role-based user access, structured alarm management, secure database connectivity, and built-in intelligence tools, enabling organizations to innovate without sacrificing governance.

Ramadan reminds us that reflection strengthens systems. Periods of evaluation create stronger foundations.

Industrial platforms must enable teams to pause, assess performance, analyze trends, and make informed adjustments. Reflection is what transforms raw data into strategy.

Data Minimalism and Focus: Reducing Noise

Fasting during Ramadan encourages clarity, reducing distractions and focusing on what truly matters.

In HMI/SCADA design, this translates directly into reducing visual and informational noise.

Too often, dashboards become cluttered with excessive data points, redundant alarms, and unnecessary visual elements. When operators are overloaded with information, decision-making slows, and errors increase.

Effective HMI/SCADA design prioritizes:

– Clear, contextual KPIs
– Immediate and actionable alarms
– Structured navigation
– Logical grouping of data
– High-performance visualization

A clean interface enables faster, more accurate decisions, mirroring the clarity of a focused mind.

ADISRA SmartView’s template architecture allows engineers to standardize layouts and maintain visual consistency across applications. Real-time trends, configurable refresh rates, structured alarm displays, and a rule-based expert system for intelligent alarm management ensure that operators see what matters, when it matters.

Clarity is not achieved by showing more.
It is achieved by showing what is essential.

Preparedness and Resilience

Ramadan also teaches endurance and resilience. Through structured discipline, individuals build strength and stability.

Industrial systems must be designed with the same philosophy.

Production environments inevitably encounter abnormal conditions, equipment failures, process deviations, and network disruptions. The question is not whether challenges will arise, but whether the system is prepared to respond intelligently.

Resilient HMI/SCADA design includes:

– Clear, prioritized alarm management
– Logical exception handling
– Real-time trend visibility
– Expert System Predictive maintenance
– Structured escalation workflows

Operators should not respond to alarms with panic; they should respond with clarity and confidence.

ADISRA SmartView supports structured alarm configuration, database logging, and a rule-based expert system that can detect anomalies and guide corrective actions. By combining visualization with intelligent response mechanisms, systems become proactive rather than reactive.

When Rhythm Meets Intelligence

It is rare to see Carnival, Lunar New Year, and Ramadan align in the same week. Three different calendars. Three distinct traditions. Three powerful expressions of culture, faith, and renewal.

Yet beneath the surface, they share something deeper.

They are all built on rhythm.

Carnival teaches us that even the most vibrant and dynamic systems require orchestration. What appears spontaneous is structured. What feels chaotic is disciplined. The lesson for industrial automation is clear: scalable, modular, well-architected systems transform complexity into synchronized performance.

The Year of the Fire Horse calls for momentum and transformation. It reminds us that speed without intelligence is reckless, but speed powered by clarity creates progress. Modern manufacturing demands real-time insight, intelligent response, and platforms that evolve as rapidly as the markets they serve.

Ramadan brings us back to discipline and reflection. It reinforces that resilience comes from structure, governance, and intentional design. In HMI/SCADA systems, clarity, security, and focus are not optional; they are foundational.

Together, these global observances remind us that powerful systems, whether cultural or industrial, are never accidental. They are built with intention.

Move beyond static dashboards and build intelligent, scalable automation systems. Download ADISRA SmartView and start designing with structure, speed, and clarity. Get ADISRA SmartView here.

If you would like a personalized demonstration, you can request one here.

If you have any specific questions or would like to speak with our team directly, please email us at info@adisra.com.

And do not forget to attend our upcoming webinar on February 26th at 9:30 AM CST. A description of the webinar and the registration link are provided below.

Smarter HMI/SCADA Applications by Design: Reusable Templates and Run-Time Configuration

Most HMI/SCADA projects succeed, or fail, before the first screen is ever built.

Early architectural decisions determine how well a system scales, how consistent it is for operators, and how difficult it becomes to maintain over time. In this webinar, you will see how template-driven design transforms HMI/SCADA into a flexible, reusable architecture rather than a one-off project.

Learn how reusable templates, runtime configuration, and low-code techniques dramatically reduce engineering effort while enabling systems that adapt to changing requirements.

Through a live walkthrough using ADISRA SmartView, we will show how templates encapsulate graphics, data bindings, and behavior into reusable components, and how they can be deployed, configured, and even modified at run time without returning to design mode.

Join us on February 26th, 2026, at 9:30 CST to discover how template-driven design creates scalable, maintainable, and future-ready HMI/SCADA applications.

Date: Thursday, 26 February 2026   – Please note the new date!  

7:30 a.m. PST (CA)

9:30 a.m.  CST  (Austin, TX)

10:30 a.m. COT   &  EST 

3:30 p.m. UTC/GMT     

4:30 p.m. CET   

5:30 p.m.  EET & SAST 

10:30 p.m. WIB (Jakarta)

11:30 p.m.  MYT

You can register for the webinar here.

Please reserve your spot and join us live.  We look forward to seeing you!

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC.

© 2026  ADISRA, LLC.   All Rights Reserved.

2025 was a record-breaking year for ransomware attacks, with incidents increasing by 45% over the past year alone. U.S.-based small and mid-sized manufacturers were hit especially hard, particularly those in general manufacturing and machinery sectors. In fact, 41% of IT and cybersecurity professionals report heightened anxiety and stress about future attacks.

Given this landscape, it is no surprise that cybersecurity is top of mind for many of our customers. Based on the questions we have been receiving, we decided to dedicate this Q&A blog to addressing some of the most common security concerns and clarifying how to protect industrial environments more effectively.

Q: With cybersecurity top of mind across the industry, are there any recent Microsoft Windows security updates that ADISRA SmartView users should be aware of?

In 2025 and beyond, Microsoft Windows remains the dominant operating system in industrial automation. It continues to power the vast majority of Human Machine Interfaces (HMIs), SCADA systems, engineering workstations, and many edge and industrial PCs deployed across manufacturing, energy, water/wastewater, and infrastructure environments.

Although support for Windows 10 ended in October 2025, the ecosystem is actively transitioning to Windows 11 IoT Enterprise and Windows Server 2025. We want to inform our customers about important security updates that may affect industrial systems.

Microsoft Secure Boot certificates originally issued in 2011 begin expiring in June 2026. Microsoft is deploying updated 2023 certificates to maintain protection against emerging boot-level threats. While most systems will receive these updates automatically, some industrial or embedded devices may require OEM firmware updates to apply the new certificates correctly.

Secure Boot is a critical protection mechanism that ensures devices start with only trusted, cryptographically verified software. It protects the earliest stage of the boot process, before Windows even loads, from rootkits and boot-level malware.

If updated certificates are not installed:

• Systems will continue to boot and operate normally.
• Standard Windows updates will still install.
• However, the device will no longer receive new protections for the early boot process, including updates to the Boot Manager, Secure Boot databases, and revocation lists.

For industrial environments that prioritize long equipment lifecycles, this is particularly important. Systems that are not properly updated could become increasingly exposed to low-level threats over time.

Additional Windows Vulnerabilities to Be Aware Of

Cyber threats continue to evolve, and Microsoft regularly patches vulnerabilities affecting core Windows components. Two notable categories include:

1. Windows Shell Security Feature Bypass Vulnerabilities

The Windows Shell (Explorer) provides the graphical interface, including the taskbar, desktop, Start menu, and file-handling mechanisms. Certain vulnerabilities have allowed attackers to bypass Windows SmartScreen and other security controls if a user is tricked into interacting with a malicious file or shortcut.

In these cases, an attacker must convince a user to open or interact with a specially crafted file. Once executed, malicious code could run without the typical warning prompts.

This highlights an important reality for industrial systems: social engineering and phishing remain major risk vectors, especially when engineering workstations have internet access.

2. MSHTML (Trident) Framework Vulnerabilities

Microsoft’s MSHTML framework, also known as the Trident rendering engine, is deeply integrated into Windows. Originally developed for Internet Explorer, it remains embedded in modern Windows versions (including Windows 11) for backward compatibility and IE Mode in Microsoft Edge.

Because of its deep integration and legacy footprint, MSHTML continues to be a frequent target for exploits.

Attackers may attempt to:

– Trick users into opening specially crafted HTML files
– Exploit shortcut links or rendering behavior
– Cause the system to execute content as code instead of data

Microsoft continues to issue patches for these vulnerabilities, but systems that are not regularly updated remain at risk.

Because ADISRA SmartView runs on Microsoft Windows platforms, system security depends on maintaining current operating system updates, firmware updates, and cybersecurity best practices.

We strongly recommend that customers:

• Verify Secure Boot certificate updates are applied
• Coordinate with OEM hardware providers for firmware updates
• Maintain current Windows security patches
• Follow proper IT/OT network segmentation guidelines

Industrial software is only as secure as the operating system and hardware that support it. Proactive updates help ensure long-term reliability and protection.

Q: How is user “inactivity” defined in ADISRA SmartView’s security settings? Does inactivity mean no mouse movement, no clicks on objects, or no interaction at all? If a user is simply viewing a graphic screen without actively clicking or entering data, will the system consider that inactive and automatically log them out?

Pressing the Settings button opens the Security Settings window, where administrators can configure security rules for users who connect to the project’s runtime environment. This includes settings that apply to Viewers, password policies for users defined in the Users & Profiles window, and other configurable security parameters.

Within these settings, you can define automatic logout behavior based on user inactivity.

In ADISRA SmartView, inactivity is measured by the lack of user interface activity, including mouse movement. When the mouse stops moving, the inactivity timer begins counting. If no activity occurs within the configured timeout period, the user can be automatically logged out.

The system tag @InactiveTime provides visibility into this process by displaying the current inactivity counter value in real time.

Q: Does ADISRA SmartView support both encryption at rest (such as Transparent Data Encryption in SQL Server or MySQL) and encryption in transit (SSL/TLS), and if so, can SSL/TLS parameters like “Encrypt” and “TrustServerCertificate” be configured in the database connection settings?

Yes. ADISRA SmartView supports both encryption at rest and encryption in transit, provided these features are enabled and configured at the database level.

Encryption at Rest

Encryption at rest, such as Transparent Data Encryption (TDE) in Microsoft SQL Server or InnoDB encryption in MySQL, is managed entirely by the database server. Since this encryption is transparent to the client application, no special configuration is required within ADISRA SmartView. The connection string remains unchanged.

Encryption in Transit (SSL/TLS)

For encryption in transit, ADISRA SmartView allows you to configure SSL/TLS parameters directly in the database connection settings.

When configuring a database connection, you can click the Advanced button to manually modify the connection string. Here, you may add parameters such as:

• Encrypt=true
• TrustServerCertificate=true or TrustServerCertificate=false

Configuration behavior:

• If Encrypt=true and TrustServerCertificate=true are set, the connection is encrypted, but certificate validation is not enforced.
• If Encrypt=true and TrustServerCertificate=false are set, the SQL client relies on the operating system’s certificate store. In this case:

• The SQL Server must be configured with a valid SSL certificate.
• The client machine must trust the certificate authority (CA) that issued the certificate.

This approach gives users the flexibility to align database security with their organization’s cybersecurity policies and compliance requirements.

Q: Can ADISRA SmartView enforce controlled access and signature authorization in a closed system?

Yes. ADISRA SmartView supports the implementation of a “closed system” as defined in 21 C.F.R. Part 11, where access is restricted to authorized individuals responsible for electronic records.

Security can be implemented using:

– The built-in ADISRA SmartView security system
– Integration with an LDAP domain security server

Key controls include:

– Unique user names and passwords
– Profile-based permissions (who can act vs. who can e-sign)
– Configurable password policies
– Automatic logoff after inactivity
– Lockout after repeated failed login attempts
– Logoff after failed e-sign attempts

CheckBox: This option enables or disables the requirement for an electronic signature before the object can be interacted with or its action executed.

Importantly, object-level security allows you to define:

– Who can perform an action?
– Who is authorized to electronically sign that action?

This separation of duties supports strong internal controls and aligns with FDA 21 C.F.R. Part 11, Subparts B (Controls for Closed Systems) and C (Electronic Signatures).

For more information on ADISRA’s FDA 21 CFR Part 11 capabilities, please review the two documents linked below.

Conclusion

Cybersecurity is no longer a background IT issue; it is a core operational requirement for industrial organizations. From Secure Boot certificate updates and Windows patch management to database encryption and FDA 21 C.F.R. Part 11 controls, today’s HMI/SCADA environments must be designed and maintained with security in mind.

ADISRA SmartView provides built-in capabilities to support secure architecture, controlled access, electronic signatures, and encrypted database connectivity. However, true protection requires a partnership between software, operating systems, hardware vendors, and IT/OT policies.

Industrial software is only as secure as the ecosystem surrounding it. Proactive updates, proper configuration, and disciplined security practices are essential to protecting uptime, compliance, and operational integrity.

We are committed to helping our customers build secure, scalable, and compliant industrial systems.

You can download ADISRA SmartView here.

If you would like to schedule a private demo with ADISRA to discuss your specific requirements, please click here.

If you have any specific questions or would like to speak with our team directly, please email us at info@adisra.com.

And do not forget to attend our upcoming webinar on February 26th at 9:30 AM CST. A description of the webinar and the registration link are provided below.

Smarter HMI/SCADA Applications by Design: Reusable Templates and Run-Time Configuration

Most HMI/SCADA projects succeed, or fail, before the first screen is ever built.

Early architectural decisions determine how well a system scales, how consistent it is for operators, and how difficult it becomes to maintain over time. In this webinar, you will see how template-driven design transforms HMI/SCADA into a flexible, reusable architecture rather than a one-off project.

Learn how reusable templates, runtime configuration, and low-code techniques dramatically reduce engineering effort while enabling systems that adapt to changing requirements.

Through a live walkthrough using ADISRA SmartView, we will show how templates encapsulate graphics, data bindings, and behavior into reusable components, and how they can be deployed, configured, and even modified at run time without returning to design mode.

Join us on February 26th, 2026, at 9:30 CST to discover how template-driven design creates scalable, maintainable, and future-ready HMI/SCADA applications.

Date: Thursday, 26 February 2026   – Please note the new date!  

Time: 9:30 a.m.  CST  

10:30 a.m. COT   

3:30 p.m. UTC/GMT     

4:30 p.m. CET   

5:30 p.m.  EET & SAST 

10:30 p.m. WIB (Jakarta)

11:30 p.m.  MYT

You can register for the webinar here.

Please reserve your spot and join us live.  We look forward to seeing you!

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC. 

The design phase is the most critical and most vulnerable stage of any HMI/SCADA project. Architectural decisions made early directly influence scalability, usability, and long-term maintainability. A well-designed system can evolve as requirements change; a poorly designed one quickly becomes rigid, costly, and difficult to modify.

In HMI/SCADA applications, design extends far beyond screen layout. It defines data models, reusable templates, navigation structures, alarm and trend strategies, and how operators interact with real-time data. These foundational decisions determine whether an application can be standardized, reused, and efficiently deployed across multiple machines, production lines, or facilities.

Modern HMI/SCADA platforms that support template-based development allow engineers to create reusable graphical components and functional objects that represent common equipment and processes. By encapsulating behavior, data bindings, and visualization into templates, development teams dramatically reduce engineering effort while ensuring consistency and reliability across the entire application.

Leveraging templates is one of the most effective ways to reduce development time, both initially and over the system’s lifetime. Templates accelerate project delivery and simplify future expansion, modification, and maintenance. Fully embracing template-driven design is a defining characteristic of experienced HMI/SCADA professionals and a key factor in building systems that scale efficiently over time.

To achieve this level of reuse and scalability, templates must be a core architectural construct, not an afterthought. ADISRA SmartView was designed with this principle in mind, embedding templates at its core. This approach enables engineers to encapsulate visualization, behavior, and configuration into reusable components that support long-term system evolution.

Template-Driven Design and Run-Time Configuration in ADISRA SmartView

ADISRA SmartView enables template-driven HMI/SCADA development through the Templates document, where engineers define reusable objects composed of any combination of available graphic elements. Each template encapsulates visualization, data bindings, and behavior into a single, reusable unit. Once configured, templates can be inserted into graphic documents to rapidly deploy multiple instances or exported for reuse in other ADISRA SmartView projects.

Templates are applied using the Template object, which allows users to select system-provided templates or those created within the project. When a template is inserted, the associated object tags defined in the template configuration are automatically created and bound. This automation ensures consistency while reducing manual configuration and engineering errors. The Template object resides in the Advanced Objects category and is placed directly onto a graphic screen.

To further enhance flexibility, ADISRA SmartView includes a Dashboard object that enables templates to be added dynamically at runtime. The Dashboard acts as a container for runtime-configurable templates, allowing users to insert, reposition, and save template instances while the application is running. These configurations persist across runtime restarts, enabling the creation of adaptable operator interfaces without modifying the original design.

The Dashboard provides three runtime controls:

• Save, which preserves the current layout 
• Move, which enables or disables repositioning of templates
• Add Template, which opens the Templates window for inserting additional templates

Beyond these controls, templates can also be managed directly at runtime using simple right-click actions. Users can right-click a template to edit or remove it, click to select and reposition it, and resize it as needed. An object function is also available to clear all templates from the Dashboard when required.

Runtime configuration in ADISRA SmartView extends far beyond graphics. Engineers and operators can make dynamic changes to alarms, trends, recipes, reports, driver configurations, database connectivity, and more, without returning to design mode. This flexibility enables truly adaptive HMI/SCADA applications that evolve seamlessly as operational requirements change.

A powerful example of this capability is ADISRA SmartView’s Low-Code Template, which demonstrates how runtime configuration can significantly simplify system customization and deployment. If you are interested in exploring this approach, contact us at info@adisra.com to learn more or request access to the Low-Code Template.

Like the Template object, the Dashboard is located in the Advanced Objects category and is placed directly onto a graphic screen.

In addition to user-defined templates, ADISRA SmartView includes a built-in library of preconfigured templates that are ready for immediate use. These templates can be used as-is or customized to meet specific application requirements, providing a fast, standardized starting point while maintaining consistency and accelerating development.

Why Templates Matter: Best Practices for Scalable HMI/SCADA Design

Templates are a foundational element of modern HMI/SCADA project design. When used correctly, they enable teams to build applications that are faster to develop, easier to maintain, and far more adaptable to change. In ADISRA SmartView, templates are not merely a convenience; they are a core mechanism for scalability, consistency, and long-term efficiency.

At their core, templates provide encapsulation: the bundling of graphics, scripts, variables, and logic into a self-contained unit. Each template can be developed, tested, and validated independently of the application it is used in. This makes templates reliable building blocks that can be reused across screens, projects, and even organizations.

Templates are also inherently extensible. A base template can serve as a standard and be lightly modified to create variations without starting from scratch. This approach encourages standardization while preserving flexibility when application-specific customization is required.

Because templates are reusable and shareable, they support a consistent corporate look and feel across machines, production lines, and facilities. When needed, templates can also be secured to prevent unauthorized reuse or modification.

From a maintenance perspective, templates dramatically simplify long-term support. Updates are made at the template level and automatically propagate to all instances that use the template. This reduces duplication, minimizes application size, and eliminates repetitive manual updates.

The productivity gains are substantial. Templates reduce initial development time by allowing engineers to build once and reuse many times. More importantly, they reduce future engineering effort as systems evolve. HMI/SCADA projects are rarely static; requirements change, equipment is added, and interfaces must adapt. Template-based projects are far easier to extend and maintain over time.

Templates also reduce errors by standardizing components instead of recreating similar objects from scratch. In ADISRA SmartView, templates are web-ready, enabling consistent design and behavior across desktop, mobile, and web-based interfaces.

AI Generated

Planning Templates into Your Design Strategy

To fully realize the benefits of templates, they must be planned from the start. During the design phase, evaluate the functions your application must perform and the information it must display. Any repeated element, such as pumps, valves, alarm indicators, trends, or data tables, is an opportunity to use a template.

One of the most effective approaches is component-based templating. A component represents a functional object within the HMI/SCADA application, ranging from simple controls to complex equipment graphics or data visualizations. By creating component templates, these elements can be defined once and reused throughout the project.

When a change is required, engineers update the master template, and the change is automatically reflected across all instances. Over time, building and maintaining a library of component templates becomes a powerful accelerator, enabling faster development while maintaining consistency, quality, and control.

A project built on templates is not only faster to deliver but also easier to scale, simpler to maintain, and better prepared for future requirements. In modern HMI/SCADA development, templates are not optimized; they are best practices.

Conclusion

Template-driven design is the foundation of scalable, maintainable HMI/SCADA systems. By planning templates into your architecture from the very beginning, you reduce engineering effort, improve consistency, and create applications that can evolve alongside your operations.

If you are designing a new HMI/SCADA application, or rethinking an existing one, now is the time to evaluate how templates can simplify development and future-proof your system. Explore ADISRA SmartView’s template and runtime configuration capabilities and start building applications that scale with confidence rather than complexity. 

Download ADISRA SmartView today and experience how simple it is to build reusable templates and configure them dynamically at runtime.

Interested in a personalized demo tailored to your application? Schedule a one-on-one session with our team here.

Save the Date – Webinar Coming Soon

Join us on February 24, 2026, at 9:30 AM CDT for our next live webinar.

Additional details will be sent shortly.

You can register here for the webinar.

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC.

© 2026  ADISRA, LLC.   All Rights Reserved.

Industrial automation has reached an inflection point. What were once standalone SCADA and HMI systems have evolved into intelligent, connected platforms that now sit at the center of modern operations. Today, these systems are no longer just visualizing data; they enable faster decisions, deeper insight, and more resilient production environments.

At the core of this transformation is the ability to capture, analyze, and act on operational data in real time. Modern SCADA and HMI platforms provide continuous visibility into processes, assets, and resource flows, turning raw signals into actionable intelligence. Operators can instantly detect deviations, engineers can diagnose issues as they emerge, and management teams can track performance against key operational metrics with confidence.

This shift from reactive monitoring to proactive, data-driven decision-making is redefining how manufacturers operate. Downtime is reduced, throughput is optimized, and organizations gain the agility needed to compete in an increasingly dynamic industrial landscape.

The latest release of ADISRA SmartView builds directly on this momentum, introducing new capabilities that enhance usability, connectivity, performance, and deployment flexibility, while reinforcing ADISRA SmartView’s role as a modern foundation for intelligent industrial applications.

Connectivity Enhancements That Strengthen the Industrial Data Backbone

In 2026, connectivity within HMI/SCADA platforms is no longer a supporting feature; it is the foundation for operational intelligence, system scalability, and Industrial IoT (IIoT) integration. High-speed, secure, and flexible connectivity is essential to eliminate data silos and deliver real-time visibility across assets, systems, and locations. Modern industrial operations depend on unified data flows that enable faster response, higher reliability, and more resilient decision-making across distributed environments.

To support this reality, the latest release of ADISRA SmartView introduces meaningful enhancements to industrial driver connectivity, expanding platform flexibility, strengthening cybersecurity, and improving operational robustness across both Windows and Linux deployments.

Expanded Beckhoff TwinCAT ADS Connectivity

TwinCAT ADS (Automation Device Specification) is a core, proprietary communication technology from Beckhoff Automation that serves as the software backbone for Beckhoff industrial PCs. As this segment continues to grow rapidly, ADISRA has expanded its TwinCAT integration to better support modern deployment architectures.

ADISRA SmartView now supports a configurable TwinCAT TCP/IP router, enabling TwinCAT communication without requiring a local TwinCAT installation. In addition, the TwinCAT ADS driver has been updated to fully support Linux environments, providing functional parity with Microsoft Windows. These enhancements simplify system architecture, reduce dependency constraints, and support flexible edge and server-based deployments.

Enhanced Security for Siemens TIA Connectivity

Siemens Totally Integrated Automation (TIA) Portal provides a unified engineering environment for programming and managing Siemens PLCs and drives. Recognizing the increasing importance of cybersecurity in industrial systems, ADISRA has upgraded its Siemens TIA driver to support Transport Layer Security (TLS).

This update enables encrypted, certificate-based communication, aligned with modern Siemens TIA Portal versions, protecting data in transit and ensuring authenticated device communication. The result is a more secure integration between Siemens controllers and ADISRA SmartView, helping safeguard industrial networks against evolving cyber threats.

Driver Worksheet Usability Improvements

This release also introduces enhancements to driver worksheets that improve usability and operational efficiency:

– Sorting and filtering on driver sheets

New sorting and filtering capabilities allow users to navigate complex driver configurations more efficiently. This reduces cognitive load, accelerates troubleshooting, and improves overall system maintainability in large or highly distributed environments.

– Configurable driver start delay (milliseconds)

A configurable start delay aligns driver initialization with device startup timing. This prevents premature polling of PLCs or RTUs, reducing connection errors, false alarms, and resource contention, particularly in large systems or deployments with slower-booting hardware.

While these connectivity and driver enhancements strengthen ADISRA SmartView’s technical foundation, usability and visual clarity remain equally critical. The latest release also delivers targeted graphic enhancements that improve the overall user experience.

Improvement to the Symbol and Graphic Libraries for Faster, More Intuitive Engineering

Symbols and graphics have been foundational to HMI/SCADA systems since their transition from text-based terminals to PC-driven graphical interfaces. Over time, symbol libraries have become essential to efficient application development, enabling standardized visualization, reducing engineering effort, and improving operator situational awareness through consistent, reusable graphical objects. Pre-engineered symbols such as pumps, valves, motors, and gauges allow engineers to rapidly build screens that reflect real-time process conditions while supporting clear, intuitive operation.

As with all aspects of ADISRA SmartView, symbol and graphic capabilities continue to evolve based on real-world customer feedback. In ADISRA SmartView V4.1.5.0, several targeted enhancements have been introduced to improve usability, accelerate development, and streamline day-to-day engineering workflows.

– Enhanced Symbol Search and Filtering

ADISRA SmartView now includes a filter capability in the Symbols dialog that supports case-insensitive, partial-text searches, dynamically filtering both folders and individual symbols. This enhancement significantly reduces the time required to locate specific graphical elements within large symbol libraries. By eliminating manual navigation through deeply nested folders, engineers can build and modify screens more efficiently, reducing development time and improving overall productivity in complex industrial applications.

– Streamlined Image Handling for Faster Screen Development

ADISRA SmartView now supports pasting images directly into the Graphics workspace, automatically creating Image objects with proper file handling and optional resize behavior. This enhancement removes manual import steps and ensures images are managed consistently within the application.

By enabling direct image pasting with intelligent handling, ADISRA SmartView significantly accelerates screen development and reduces engineering effort. Engineers can quickly incorporate equipment photos, layout diagrams, and floor maps into high-fidelity overview screens while maintaining image quality, predictable sizing, and efficient resource management, resulting in clearer visualization and more intuitive operator interfaces.

– Enhanced Dynamic Fill Control with Scaled Tag Ranges

ADISRA SmartView now allows tags used in Dynamic Fill to be configured with explicit minimum and maximum values for ellipse objects, supporting angular, vertical, and horizontal orientations. This enhancement provides greater control over how live data is visually represented on graphics.

By scaling raw tag values into meaningful visual ranges, this feature transforms low-level machine data into intuitive, real-time indicators, such as tank levels, pressure ranges, or capacity utilization. Operators gain faster comprehension of process conditions, while engineers benefit from cleaner configuration and more accurate visual mapping. The result is improved situational awareness, safer operation, and more confident, data-driven decision-making.

– Enhanced Dynamic Fill Control with Scaled Tag Ranges

ADISRA SmartView now allows tags used in Dynamic Fill to be configured with explicit minimum and maximum values for ellipse objects, supporting angular, vertical, and horizontal orientations. This enhancement provides greater control over how live data is visually represented on graphics.

By scaling raw tag values into meaningful visual ranges, this feature transforms low-level machine data into intuitive, real-time indicators, such as tank levels, pressure ranges, or capacity utilization. Operators gain faster comprehension of process conditions, while engineers benefit from cleaner configuration and more accurate visual mapping. The result is improved situational awareness, safer operation, and more confident, data-driven decision-making.

Several additional enhancements requested by users are also included in ADISRA SmartView V4.1.5.0.

– Improved Trend Refresh Control for High-Speed Visibility

While SCADA graphics provide a snapshot of current conditions, trending delivers critical context by visualizing how processes change over time. Trend displays allow operators and engineers to identify patterns, detect anomalies, and anticipate potential issues before they impact operations.

ADISRA SmartView now includes a configurable refresh rate for Trend objects, with a minimum supported interval of 200 milliseconds. This enhancement allows trend displays to update up to five times per second, delivering high-fidelity visualization of fast-changing processes without compromising system performance.

By giving users control over trend refresh behavior, ADISRA SmartView enables more accurate diagnostics, faster response to transient events, and better insight into dynamic process behavior, particularly in applications involving high-speed equipment, energy monitoring, or rapidly fluctuating process variables.

– Faster Diagnostics with One-Click Access to DataWatcher

ADISRA SmartView now includes a shortcut button in the Remote Management Tool that opens DataWatcher, ADISRA SmartView’s built-in diagnostic and debugging utility, using the currently connected IP address. This enhancement eliminates the need for manual navigation and IP re-entry when troubleshooting remote systems.

In real-world deployments, especially across distributed plants or remote sites, rapid diagnosis is critical. One-click access to DataWatcher allows engineers and support teams to immediately inspect live tag values, communication status, and data integrity at the source. By reducing the time required to initiate diagnostics, this feature accelerates issue resolution, minimizes downtime, and improves the efficiency of remote support and maintenance operations.

– More Efficient Event Analysis with Flexible Message Filtering

ADISRA SmartView now supports filtering events by message content using partial-text matches, enabling faster and more flexible event searches. This enhancement allows users to quickly locate relevant event records without needing exact message text or rigid filter criteria.

In real-world HMI/SCADA environments, event logs capture time-stamped records of system activity, such as operator actions, configuration changes, and equipment state transitions, and serve as a critical source for auditing, diagnostics, and operational review. As event histories grow, manually scanning or narrowly filtering logs becomes time-consuming and error-prone.

Partial-message filtering dramatically reduces the time required to investigate incidents, validate operator actions, or support compliance reviews. Engineers and operators can rapidly isolate meaningful events, understand what occurred and when, and move from investigation to resolution more quickly and with greater confidence, without disrupting active operations.

Conclusion

Industrial operations continue to demand more from their HMI/SCADA platforms, greater connectivity, stronger security, faster diagnostics, and tools that reduce engineering effort without sacrificing performance. ADISRA SmartView V4.1.5.0 delivers on these expectations with targeted enhancements driven directly by real-world customer feedback.

From expanded Beckhoff and Siemens connectivity to improved driver usability, enhanced graphics workflows, faster trending, and streamlined diagnostics, this release strengthens ADISRA SmartView’s role as a modern, flexible foundation for intelligent industrial applications across Windows, Linux, edge, and distributed environments.

Download ADISRA SmartView V4.1.5.0 today to experience these improvements firsthand and see how they can simplify development, improve visibility, and accelerate decision-making in your next industrial project.

If you would like to see these new features in action, you can request a private demonstration here tailored to your specific use case or join us for the next ADISRA live webinar on Thursday, January 29, 2026.

During the webinar, we will demonstrate the new capabilities introduced in ADISRA SmartView V4.1.5.0, along with additional features commonly requested by customers and partners.

Webinar time:
9:30 a.m. CST
10:30 a.m. COT
12:30 p.m. BRT
3:30 p.m. UTC/GMT
4:30 p.m. CET
5:30 p.m. EET
11:30 a.m. MYT (Friday, January 30, 2026)

You can register for the webinar here. 

The Linux Foundation and the Linux Foundation logo design are registered trademarks of The Linux Foundation.  Linux is a registered trademark of Linus Torvalds.

Tux, the Linux kernel penguin mascot, was created by Larry Ewing in 1996 [lewing@isc.tamu.edu] using the GIMP [www.gimp.org] and is not owned by The Linux Foundation.

Microsoft, Windows, Windows 10X, Windows 11, and Windows Designs are trademarks of the Microsoft group of companies.

Siemens and Siemens TIA (TIA Portal): TIA Portal® is a registered trademark of Siemens Aktiengesellschaft.

Beckhoff®, TwinCAT®, TwinCAT/BSD®, TC/BSD®, EtherCAT®, EtherCAT G®, EtherCAT G10®, EtherCAT P®, Safety over EtherCAT®, TwinSAFE®, XFC®, XTS® and XPlanar® are registered and licensed trademarks of Beckhoff Automation GmbH.

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC.

© 2026  ADISRA, LLC.   All Rights Reserved.

As we move through 2026, the acceleration of artificial intelligence is fundamentally reshaping the global technology landscape, and nowhere is that transformation more visible than in data centers. AI models are growing larger, more complex, and dramatically more power-hungry, driving unprecedented demand for compute capacity, electrical infrastructure, and intelligent energy management. To keep pace, the world has entered a historic data center expansion phase. Increasingly, industry analysts measure this growth not by the number of facilities constructed, but by total installed capacity in gigawatts, a far more revealing indicator of the scale ahead.

This data center boom extends well beyond the technology sector. Real estate developers, utilities, governments, and environmental stakeholders are all deeply invested in the outcome. For some policymakers, data centers represent strategic, even geopolitical infrastructure. Others raise urgent concerns about grid stability, energy availability, and environmental impact. Today, more than 10,500 data centers operate across 174 countries, and that global footprint continues to expand rapidly.

By 2030, global demand for data center capacity is expected to nearly triple. Over the remainder of the decade, companies worldwide are projected to invest close to $7 trillion in building new facilities and upgrading existing ones. Power consumption alone illustrates the magnitude of this shift: global data center electricity usage is forecast to reach 219 gigawatts within five years, enough energy to power roughly 180 million U.S. homes.

According to McKinsey, keeping pace with AI-driven compute demand will require approximately $6.7 trillion in capital investment by 2030. Of that total, $5.2 trillion will be directed toward data centers capable of supporting AI workloads, while another $1.5 trillion will go toward facilities running traditional IT applications. These figures underscore the scale of the transformation underway, and why power efficiency, operational intelligence, and energy optimization have become mission-critical priorities.

Looking further ahead, Deloitte projects that power demand from AI data centers in the United States alone could increase more than thirtyfold by 2035, rising from just 4 gigawatts in 2024 to approximately 123 gigawatts. At the same time, Big Tech hyperscalers are racing to construct gigawatt-scale AI data centers, with multiple facilities expected to exceed 1 GW of capacity by 2026, each consuming power comparable to that of a nuclear reactor. Yet infrastructure realities are beginning to constrain AI ambitions. A projected 19-gigawatt gap between new data center demand and available grid capacity threatens to slow deployments and expose inefficiencies across power and cooling systems.

https://action.deloitte.com/insight/4718/ai-data-centers-jolt-power-demand

AI data centers themselves represent a new class of infrastructure. They are designed to support ultra-high-density compute environments, advanced cooling technologies, high-performance networking, and sophisticated management platforms capable of efficiently handling extreme power and thermal loads. As Bloomberg described it, 2024 marked the beginning of a “data center gold rush,” with leading technology companies investing as much as $200 billion in a single fiscal year to keep pace with surging AI demand.

As data centers grow in scale, density, and operational complexity, energy management can no longer be treated as a secondary concern or a post-process reporting function. Operators require continuous, real-time visibility into power consumption, thermal conditions, and infrastructure performance, along with the ability to analyze trends, identify inefficiencies, and take action before constraints impact availability, reliability, or cost. ADISRA SmartView and InsightView address this need through an integrated energy management approach that combines on-premise HMI/SCADA for real-time monitoring and control with cloud-based analytics, enabling smarter decisions, optimized energy usage, and resilient data center operations at scale.

ADISRA SmartView: Real-Time Power and Environmental Control at the Data Center

ADISRA SmartView provides real-time monitoring, control, and optimization of power and environmental conditions across data center infrastructure. Temperature and humidity directly impact equipment reliability, performance, and lifecycle. Elevated temperatures increase thermal stress on servers and networking equipment, while improper humidity levels can cause condensation, corrosion, or electrostatic discharge. Continuous monitoring and closed-loop control are therefore essential to maintaining stable operating conditions.

ADISRA SmartView integrates real-time temperature and humidity sensors to enforce defined operating envelopes and respond immediately to deviations. Alarms, control actions, and rule execution are driven by live data, enabling corrective action before environmental thresholds are exceeded and reducing the risk of equipment failure.

Environmental control decisions directly influence energy efficiency. Adjusting cold-aisle temperature setpoints through ADISRA SmartView rule-based expert system alters the cooling load distribution across chillers, cooling towers, heat exchangers, and pumps, often producing nonlinear efficiency effects. ADISRA SmartView incorporates ambient conditions through its OpenWeather API, using real-time, historical, and forecast weather data to dynamically adjust cooling strategies and optimize energy consumption.

Power system stability is equally critical. ADISRA SmartView monitors electrical parameters across utility feeds, UPS systems, power distribution units (PDUs), and backup generators to ensure continuous operation. Real-time power analytics enable early detection of anomalies such as voltage sags, surges, frequency deviations, and load imbalances. When abnormal conditions are detected, ADISRA SmartView can trigger alarms, execute control logic, or initiate automated responses to minimize operational impact.

Power disturbances caused by grid instability, lightning, or equipment faults are identified through continuous monitoring and evaluated using ADISRA SmartView’s built-in expert system. This enables rapid response to power quality issues and reduces the likelihood of unplanned outages or equipment damage.

Server health monitoring is integrated into the same operational framework. ADISRA SmartView continuously tracks CPU utilization, memory usage, storage performance, and network throughput. Rule-based logic identifies abnormal behavior, sustained overloads, or failure precursors. For example, sustained CPU utilization above defined thresholds can trigger alerts or initiate workload redistribution to prevent thermal or performance degradation.

While HMI/SCADA control provides the immediacy required to maintain stable and efficient data center operations, long-term optimization requires a broader analytical perspective. Patterns in energy consumption, cooling efficiency, and infrastructure performance emerge over time and across facilities, insights that cannot be fully realized at the site level alone. By extending operational data from ADISRA SmartView into the cloud, InsightView enables advanced energy analytics, multi-site visibility, and data-driven optimization at scale.

Download ADISRA SmartView here. 

InsightView Energy Module: Cloud-Based Analytics for Scalable Data Center Energy Optimization

To extend operational intelligence beyond the facility, ADISRA SmartView securely publishes selected real-time and contextual data to the cloud, where InsightView’s energy module applies advanced analytics, long-term trending, and cross-site comparison. Together, ADISRA SmartView and InsightView form a unified energy and operations platform, linking deterministic, real-time control at the data center edge with cloud-scale analytics required to operate high-density AI infrastructure reliably and efficiently.

InsightView is designed to analyze energy and operational performance, and can be used for AI data center infrastructure, providing deep visibility into power consumption, cooling efficiency, utilization patterns, and system behavior over time. Intuitive, customizable dashboards enable operators to monitor key performance indicators, including power utilization trends, thermal stability, and energy intensity, at the rack, row, room, or facility level.

Built as a cloud-native platform, InsightView enables centralized visibility across multiple data centers, availability zones, or campuses. Its software-as-a-service (SaaS) delivery model simplifies deployment, reduces operational overhead, and supports rapid scaling as AI capacity expands. Continuous updates ensure operators benefit from evolving analytics capabilities without disrupting operations.

InsightView’s energy management module is optimized for environments where power availability is a limiting factor. It supports demand-aware energy analysis, enabling operators to align compute workloads, cooling strategies, and energy-intensive operations with real-time conditions and grid constraints. By identifying opportunities to shift or optimize loads, InsightView helps reduce peak demand exposure, control operating costs, and improve overall energy efficiency without compromising performance.

The platform continuously collects and analyzes energy data from multiple sources, including electrical feeds, cooling systems, and facility infrastructure, combining real-time telemetry with historical context. This enables the detection of anomalies, the identification of inefficiencies, and the early recognition of emerging risks, supporting proactive decision-making in power-constrained AI environments.

As rising power demand, sustainability requirements, and grid limitations reshape the future of AI infrastructure, effective energy management is becoming a strategic capability rather than an operational afterthought. InsightView enables data center operators to move from reactive monitoring to data-driven energy optimization, supporting resilient operations, higher utilization of available power, and long-term scalability in the era of AI-driven computing.

Request a temporary InsightView account at info@adisra.com. 

Conclusion

AI-driven data centers are pushing power, cooling, and infrastructure limits faster than traditional operational models can adapt. As rack densities increase and energy availability becomes a defining constraint, success is no longer measured by how quickly facilities can be built, but by how intelligently they can be operated.

ADISRA SmartView and InsightView deliver an integrated energy management architecture designed for this new reality. By combining deterministic, real-time HMI/SCADA control at the data center edge with cloud-based analytics and multi-site visibility, operators gain the insight required to optimize power usage, improve cooling efficiency, and scale AI infrastructure without sacrificing reliability or cost control.

As AI continues to accelerate, energy and operational intelligence will define the next generation of data center leaders. Now is the time to move beyond reactive monitoring and adopt an intelligent, data-driven approach to energy management.

Ready to Try ADISRA SmartView?

You can download the software here and explore the powerful features of ADISRA SmartView at your own pace.

Interested in a personalized demo tailored to your application? Schedule a one-on-one session with our team here.

If you would like an InsightView account to test the energy management module, request one at info@adisra.com. 

If you would like to learn more about ADISRA SmartView, we invite you to attend our live webinar:

Live Webinar: Unlock the Next Level of Industrial Efficiency with ADISRA SmartView

As industrial organizations look ahead to 2026, many are reassessing how efficiently their operations truly perform. Aging HMI/SCADA systems, siloed data, and rigid architectures often restrict visibility, slow decision-making, and make scaling more complex than necessary. Achieving modern efficiency requires more than incremental improvements; it demands a flexible, future-ready platform built for today’s industrial environments.

Join the ADISRA team for a live webinar demonstrating how ADISRA SmartView enables system integrators, OEMs, and industrial operators to streamline development, unify operational data, and confidently scale industrial applications.

In this session, you will learn how ADISRA SmartView supports:

• Simple, secure, and scalable architectures for edge and control room applications
• Rapid application development using reusable templates and runtime configuration
• Seamless data collection from multiple hardware devices through built-in drivers, eliminating data silos
• Stronger, data-driven decision-making with integrated trending, logging, and analytics

Whether you are modernizing existing systems or designing next-generation industrial applications, this webinar will provide practical insights to help you move beyond legacy limitations and achieve measurable efficiency gains.

Date: Thursday, January 29, 2026

Time:
9:30 a.m. CST
10:30 a.m. COT
12:30 p.m. BRT
3:30 p.m. UTC/GMT
4:30 p.m. CET
5:30 p.m. EET
11:30 a.m. MYT (January 30, 2026)

Please reserve your spot and join us live here.

Register here:

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC.

© 2026  ADISRA, LLC.   All Rights Reserved.

As we enter 2026, manufacturing and industrial leaders are navigating a landscape shaped by converging forces: accelerated adoption of artificial intelligence, ongoing geopolitical uncertainty, increasing sustainability requirements, and renewed focus on industrial policy and supply-chain resilience. These pressures are not theoretical; they are directly influencing how plants are designed, operated, and modernized.

The past few years have delivered remarkable advances in industrial automation. But the most meaningful shift is not the technology itself; it is how automation is becoming more practical, accessible, and deployable at scale. What was once limited to highly customized, resource-intensive projects is now available to a much broader range of manufacturers, operators, and system integrators.

At the same time, labor constraints persist, production demands continue to increase, and operations are under pressure to respond faster while supporting greater variability and customization. Automation is no longer a “nice to have.” Its value is already proven across factories, warehouses, laboratories, utilities, agriculture, and critical infrastructure worldwide. The challenge in 2026 is no longer whether to automate, but how to deliver measurable value quickly and reliably across distributed operations.

This is where ADISRA’s approach comes into focus. Through platforms such as ADISRA SmartView, InsightView, and KnowledgeView, ADISRA enables organizations to move beyond visualization toward intelligent, data-driven operations, combining real-time edge intelligence, cloud-based analytics, and practical AI without unnecessary complexity.

A single breakthrough or standalone solution does not define the automation trends shaping 2026. Instead, they reflect the convergence of AI, edge computing, IoT, data integration, and cybersecurity, working together to deliver scalable, secure, and actionable intelligence. The following predictions highlight the technologies and architectural shifts ADISRA expects to see in 2026 and how they translate into real operational value across industries and company sizes.

Prediction #1: AI Will Redefine Industrial Automation and Operator Interfaces in 2026

Artificial Intelligence is no longer an emerging concept in industrial automation—it is becoming foundational. As we enter 2026, AI continues to reshape how operators interact with systems, how decisions are made, and how value is extracted from industrial data. Two areas driving this transformation are AI agents and Large Language Models (LLMs), supported by rapid advances in predictive analytics, IoT analytics, and edge intelligence.

AI Agents: From Concept to Autonomous Execution

After gaining credibility as an enterprise technology in 2024, AI agents moved swiftly from hype to evaluation in 2025 and are now transitioning into real-world adoption. An AI agent is an intelligent software system capable of sensing its environment, reasoning about conditions, planning actions, and acting autonomously to achieve defined objectives.

Key characteristics of AI agents include:

Autonomy – AI agents operate independently, making decisions and taking action without constant human oversight. Decisions may be driven by predefined rules, learned behaviors, or real-time data analysis.

Learning capability – AI agents improve over time by learning from outcomes. This learning can be achieved through machine learning or reinforcement learning, in which agents adjust their behavior based on rewards or penalties.

Goal-oriented behavior – AI agents are designed to achieve specific objectives, breaking complex goals into manageable sub-goals. Human operators can intervene at any stage to provide feedback or redirect outcomes.

Environmental perception – AI agents ingest and analyze data from multiple sources to identify trends, anomalies, and optimization opportunities.

In industrial settings, AI agents are increasingly positioned to support operators by continuously monitoring systems, identifying issues early, and recommending or executing corrective actions.

Large Language Models: A New Interface to Industrial Systems

In parallel, generative AI powered by Large Language Models has matured rapidly. LLMs are deep-learning systems built on transformer architectures and trained on massive datasets to understand and generate human language. They enable tasks such as summarization, reasoning, translation, and natural language interaction with software systems.

At their core, LLMs are large statistical prediction engines that generate text by predicting the most likely next word in a sequence. What makes them transformative is their ability to capture context, nuance, and intent, something traditional rule-based or keyword-driven systems cannot do at scale.

For industrial automation, LLMs represent a fundamental shift in how humans interact with technology. Instead of navigating complex menus or scripts, operators can increasingly interact with systems using natural language, making advanced analytics and diagnostics more accessible to a broader workforce.

AI in Industrial Automation: What Continues to Evolve in 2026

As AI adoption accelerates, several areas will continue to shape industrial automation software:

Predictive analytics

Traditional reactive approaches are no longer sufficient for modern, complex production environments. Predictive analytics enables manufacturers to anticipate equipment failures, optimize production schedules, improve product quality, and strengthen supply chains. By combining historical data, statistical models, and machine learning, predictive analytics helps organizations move from reactive to proactive operations.

IoT and edge analytics

Industrial AI investment is growing rapidly, with IoT analytics playing a central role. Connected devices generate enormous volumes of heterogeneous data every day. The actual value of IoT lies in transforming this raw data into actionable insights.

Edge analytics, processing data at or near its source, continues to gain traction in 2026, enabling faster decisions, reduced latency, and improved reliability. Applications range from manufacturing and energy to smart agriculture, where real-time analytics optimize irrigation, monitor soil conditions, and improve crop yields.

From Rules to Learning: The ADISRA Approach

ADISRA SmartView, equipped with a built-in rule-based expert system, provides a practical and intuitive entry point into industrial analytics. Users can focus on defining rules, modeling expert knowledge, and driving outcomes without the complexity typically associated with advanced analytics platforms. Predictive maintenance can be achieved through expert system logic that maximizes uptime and extends equipment life.

Beyond predictive maintenance, ADISRA SmartView delivers real-time analytics at the edge, supporting applications such as immediate operational insights, anomaly detection, security monitoring, and real-time standards compliance.

While ADISRA SmartView handles deterministic, real-time diagnostics at the edge, KnowledgeView adds a cloud-based layer of intelligence powered by machine learning. KnowledgeView continuously learns from large datasets, uncovering subtle fault patterns that may not trigger immediate alarms but signal emerging issues.

Looking Ahead

In 2026, industrial automation software will no longer simply display data; it will interpret it, contextualize it, and recommend actions.  AI will reduce operator workload through continuous real-time monitoring, enhance decision quality, and enable more resilient and adaptive industrial operations.

Ready to explore ADISRA SmartView? Download and test it here:

Need a temporary KnowledgeView account? Request access at: info@adisra.com

Prediction #2: Edge, IoT, and AI Will Converge to Power Real-Time Industrial Intelligence

In 2026, the convergence of Edge Computing and the Internet of Things (IoT) will become a cornerstone of industrial automation strategies. Rather than sending all data to centralized cloud platforms, organizations are increasingly processing data locally, at or near its source, to enable faster decisions, lower latency, reduced bandwidth usage, and improved security.

Edge computing is a distributed computing model that moves applications and analytics closer to data-generating devices such as sensors, cameras, and industrial equipment. As connected devices proliferate, accelerated by 5G and high-speed networks, this approach enables real-time insights that cloud-only architectures cannot deliver.

IoT refers to networks of physical devices embedded with sensors and software that continuously generate large volumes of operational data. In industrial environments, this includes assets such as turbines, pumps, motors, production lines, and mobile equipment. When combined with edge computing, IoT data can be filtered, analyzed, and acted upon immediately, with only critical insights or summaries sent to the cloud for long-term analysis and storage.

Industrial IoT and Edge AI

Industrial IoT (IIoT) extends IoT capabilities to complex and high-value manufacturing assets. Sensors are increasingly deployed not only on primary equipment, but also on vulnerable or failure-prone components, helping engineers identify root causes, performance bottlenecks, and early signs of degradation.

The next evolution is Edge AI, where intelligence is embedded directly into edge devices. Machine learning models running at the edge analyze continuous data streams in real time, enabling faster responses and greater system autonomy. This approach supports applications such as predictive maintenance, quality inspection, anomaly detection, and adaptive process control—without relying on constant cloud connectivity.

According to MarketsandMarkets, the global industrial edge market is expected to grow from USD 21.19 billion in 2025 to USD 44.75 billion by 2030, driven by rapid digitization, increased IoT adoption, and the demand for real-time, on-site data processing.

From Edge Intelligence to Cloud Collaboration

On the edge, intelligence is becoming more advanced, with AI integrated directly into hardware and runtime platforms. ADISRA SmartView supports this transition by running headless on both Windows and Linux platforms, enabling real-time analytics and AI-driven decision-making directly at the edge.

As data models grow more complex, industrial architectures are increasingly hybrid. Real-time AI operates close to the data source. At the same time, cloud-based platforms, augmented with machine learning and Large Language Models, analyze larger historical datasets to uncover deeper patterns and long-term insights. This collaborative edge-to-cloud approach delivers the best of both worlds: immediate intelligence at the edge and strategic learning in the cloud.

In 2026, the integration of Edge, IoT, and AI will shift industrial automation from reactive monitoring to proactive, intelligent operations, laying the foundation for faster decisions, higher resilience, and more autonomous systems.

Prediction #3: Data Integration Becomes the Backbone of AI-Driven Industrial Systems

2026 marks a pivotal shift in how organizations approach data integration. What was once viewed as a technical requirement is now recognized as a strategic foundation for AI, automation, and real-time decision-making.

The data integration market is growing rapidly as enterprise data environments become more complex. According to MarketsandMarkets, the global data integration market reached approximately USD 17.1 billion in 2025 and is projected to exceed USD 47.6 billion by 2034. Complementing this outlook, Precedence Research forecasts growth from USD 17.58 billion in 2025 to USD 33.24 billion by 2030, underscoring strong and sustained market momentum.

This complexity stems from the rise of multi-cloud, hybrid cloud, edge, and on-premises infrastructures, all of which require seamless, scalable data connectivity. Organizations have come to realize that integrating data is the only realistic way to unlock its full value. When data is unified, businesses can derive accurate, timely insights and act with confidence.

Why Data Integration Is Accelerating

Several forces are driving this shift:

– AI-ready data infrastructure requirements, where high-quality, contextual data is essential

– Multi-cloud and hybrid strategies that fragment data across environments

– Agentic AI systems that require real-time access to trusted data

– Government initiatives such as the U.S. Federal Data Strategy, India’s National Data Governance Framework, and the EU Data Act, which emphasize interoperability and accessibility

As a result, data integration has evolved into the backbone of modern AI systems, enabling autonomous decision-making and faster responses to changing market conditions.

The Persistent Challenge: Data Silos

Despite increased investment, data silos remain one of the most significant barriers to digital transformation. Many organizations face a paradox: while accelerating the adoption of generative AI and automation, disconnected data initiatives unintentionally create new silos rather than eliminate old ones.

Modern data integration platforms address this challenge through:

– Unified data access that connects disparate systems into a single view

– Real-time synchronization to keep data consistent across platforms

– API-led connectivity that makes data available to applications and AI agents

– Data virtualization that enables access without moving or duplicating data

What This Means for Industrial Automation

In industrial environments, HMI, SCADA, and PLC systems are no longer treated as isolated components. Platforms such as ADISRA SmartView, with built-in support for industrial and IT protocols and straightforward database connectivity, provide a simple and effective way to consolidate data from disparate machines and systems.

The 2026 reality: SCADA systems are evolving from passive polling engines into real-time data publishers, feeding analytics platforms, AI agents, and enterprise systems with contextualized operational data.

Data integration is no longer optional; it is the connective tissue that enables intelligent, adaptive, and AI-driven industrial operations.

Prediction #4: Cybersecurity Becomes a Core Pillar of Operational Resilience

As we enter 2026, it would be remiss not to highlight cybersecurity as a defining challenge for both industrial and enterprise systems. The threat landscape is rapidly evolving into a far more complex battlefield, marked by increasingly sophisticated attack vectors and the rise of agentic AI capable of autonomous decision-making. In this environment, cybersecurity is no longer just an IT concern; it is a fundamental component of organizational resilience, requiring proactive strategies that span IT, OT, edge, and cloud infrastructures.

Market forecasts reinforce the urgency of this shift. According to Future Market Insights, the industrial cybersecurity market is valued at approximately USD 26.0 billion in 2025 and is projected to more than double, reaching USD 55.1 billion by 2035. Similarly, Global Market Insights estimates the market at USD 21.7 billion in 2025, with growth accelerating from USD 23.3 billion in 2026 to over USD 51.1 billion by 2035. Together, these forecasts highlight sustained, long-term investment in securing industrial and operational technology environments.

By 2026, industrial cybersecurity will be defined by the escalation of AI-driven attacks and an urgent shift toward integrated, resilient security architectures built directly into OT networks. Organizations will move away from fragmented IoT and OT security tools in favor of unified cybersecurity platforms that provide a single, real-time view across IT, OT, and IoT environments, spanning the edge, plant floor, and cloud.

Adversaries are already leveraging AI to accelerate vulnerability discovery, automate attacks, conduct sophisticated social engineering, and deploy self-evolving malware that can evade traditional, perimeter-based defenses. In response, defenders are increasingly deploying AI agents and automation within Security Operations Centers to enable machine-speed detection, triage, and response capabilities that are becoming essential as industrial environments grow more interconnected and digitally dependent. This shift is further accelerated by escalating ransomware attacks on operational technology, mounting financial impact, rising global data breach costs, cybercrime projected to reach USD 10.5 trillion annually, and intensifying regulatory pressure.

Governments and regulators are moving from guidance to enforcement, including mandates such as the EU’s NIS2 Directive and directives from CISA that require secure-by-design engineering, Zero Trust adoption in OT environments, and greater executive accountability. At the same time, nation-state actors and cybercriminal groups are increasingly targeting critical infrastructure such as energy, manufacturing, transportation, and water systems while exploiting software and service supply-chain vulnerabilities to scale attacks downstream. Together, these forces are driving rapid growth in the industrial cybersecurity market and fundamentally reshaping industrial architecture, making cybersecurity a core operational requirement alongside safety, reliability, and uptime.

Conclusion: Turning Predictions into Action in 2026

As these predictions make clear, 2026 is not about a single technology leap; it is about architectural maturity. AI, edge computing, IoT, data integration, and cybersecurity are converging into cohesive industrial systems that deliver measurable value faster and at greater scale. The winners will not be those who chase every new tool, but those who build secure, intelligent, and adaptable foundations that can evolve with the pace of change.

Industrial automation is moving beyond visualization and isolated analytics. Systems must now interpret data, contextualize conditions, and recommend or execute actions, all while operating reliably across distributed environments and under increasing regulatory and security pressure.

This is precisely where ADISRA is focused. Through ADISRA SmartView, InsightView, and KnowledgeView, ADISRA enables organizations to adopt AI and advanced analytics in practice, starting with rule-based intelligence at the edge and extending to cloud-based learning and optimization when and where it makes sense.

In 2026, success will not be defined by how much data you collect, but by how quickly you can turn insight into action, safely and at scale.

The future of industrial automation is intelligent, connected, and resilient.

ADISRA is ready to help you build it.

Download and test ADISRA SmartView here:

Request a temporary account for InsightView and KnowledgeView access by sending an email to: info@adisra.com

Have a project in mind? Let’s connect. Click here to schedule a personalized demonstration.

ADISRA®, ADISRA’s logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC.


Copyright
© 2026 ADISRA, LLC. All Rights Reserved.

Following our recent webinar on “From the Shop Floor to the Cloud: Maximizing OEE Everywhere”, many attendees asked insightful questions about how InsightView fits into modern manufacturing strategies. As demand for OEE software continues to grow, driven by smart manufacturing initiatives, real-time performance requirements, and the need to reduce downtime, manufacturers are evaluating how best to deploy OEE at scale across machines, plants, and enterprises.

Today, North America leads the OEE market, accounting for approximately 38% of global revenue, while Asia-Pacific is the fastest-growing region due to rapid industrialization and smart-factory initiatives. At the same time, on-premise OEE deployments still account for more than half of the market, reflecting ongoing requirements for data security, customization, and legacy system integration. These trends highlight why hybrid and cloud-based OEE platforms are gaining traction.

In this blog, we address the most common questions raised during our webinar and provide clear, practical answers about InsightView. Whether you are just beginning your OEE journey or looking to expand visibility beyond the plant floor, this Q&A is designed to help you understand how InsightView can support smarter, data-driven decisions.

From OEE Metrics to Actionable Insights

Understanding OEE at this level is essential, but the real value comes from how effectively it is measured, analyzed, and acted upon. While the OEE score itself provides a powerful snapshot of manufacturing performance, it is only the starting point. To drive meaningful improvement, manufacturers must look beyond the headline number and examine the operational data that feeds it.

This is where modern OEE platforms make a measurable difference. By continuously capturing runtime data, downtime events, production counts, and quality results, OEE systems transform raw machine data into actionable insights. Instead of reacting to problems after the fact, teams gain visibility into loss patterns as they emerge, whether it is frequent short stops affecting performance, recurring changeovers impacting availability, or quality issues concentrated at startup.

Equally important is context. OEE data must be analyzed across shifts, lines, products, and facilities to uncover trends that are not visible at the machine level alone. A single asset may appear efficient in isolation, while plant-wide or multi-site data reveals systemic issues tied to scheduling, maintenance practices, or operator workflows. This broader view enables organizations to prioritize improvements that deliver the greatest operational and financial impact.

For a more in-depth discussion of the metrics behind OEE and the Six Major Losses, we invite you to explore the following previous blog posts.

• Beyond the Rearview Mirror: How AI is Transforming OEE and the Future of Manufacturing
• Maximizing Dairy Plant Performance: A Hybrid OEE Strategy From Machine to Cloud
• OEE in 2025 from KPI to AI-Driven Optimization
• Tackling the Six Major Losses to Maximize OEE in 2025
• Optimizing Manufacturing Performance Leveraging OEE and the Six Major Losses for Plant and Multi-site Efficiency with Cloud Integration

As manufacturers expand from single-machine monitoring to plant-wide and enterprise-level performance management, questions naturally arise:  Where should OEE data live? How do cloud and on-premises systems work together? How can OEE scale across multiple sites without adding complexity?

In the next section, we answer these questions directly, drawing from the most common topics raised during our recent webinar, to explain how InsightView helps manufacturers operationalize OEE, from real-time visibility to actionable intelligence.

InsightView: Your Questions Answered

Since I missed the webinar, can you give me a quick overview of InsightView?

InsightView is a powerful yet intuitive analytics platform from ADISRA designed to transform production data into meaningful performance insights. It interprets machine and process data to measure productivity, providing key indicators such as Overall Equipment Effectiveness (OEE) and visibility into the Six Major Losses that impact operational performance.

Highly flexible and customizable, InsightView allows users to build dashboards tailored to their specific monitoring needs, whether tracking individual machines, production lines, or multiple facilities, making it easier to understand machine status, identify losses, and drive continuous improvement.

To catch up on what you missed, you can access the webinar video replay here and download the presentation slides here.

Click the navigation menu in the top-left corner of the page (1). When the menu opens, select the “Companies” tab (2), then click the “Add/Edit” button (3). Click the “+” button in the bottom-right corner of the page (4). A window will appear. Enter the company name (required), display name (the name shown in the navigation menu), and a short company description (5). When finished, click “Save.”

My company has multiple locations. Does InsightView support multi-site operations?

Yes. InsightView is designed to support companies with multiple locations, making it easy to organize, monitor, and analyze performance across sites from a single platform.

You begin by defining your company and adding individual sites using a simple, menu-driven interface. Each site can be configured with a site name, display name, description, and geographic location. By assigning latitude and longitude values, InsightView can accurately place each site on a map, enabling intuitive navigation and quick access to site-level performance data.

Once sites are defined, you can further structure each location by creating areas and assigning the assets to be monitored. This hierarchical approach, company, site, area, and asset, allows InsightView to scale naturally as your organization grows, while maintaining clear visibility from individual machines all the way up to enterprise-level performance.

Open the navigation menu (1). Select the company (2), site (3), and area (4) by clicking their names. Click the “Assets” tab (5), then click the “Add/Edit” button (6). Click the “Tags” button (7) for the selected asset. A window will appear.

Once my assets are defined, how does InsightView connect to data and calculate OEE?

After an asset’s location and structure are defined, the next step is telling InsightView where to retrieve the data that drives analytics and OEE calculations. In InsightView, these data points are referred to as tags, and they are typically sourced from an external database.

Users begin by configuring one or more database connections at the company or site level. InsightView supports a wide range of industrial and enterprise database servers, including SQL Server, PostgreSQL, MySQL, Oracle, and others, enabling seamless integration with existing data architectures. Once a database connection is defined and saved, it becomes available as a trusted data source for the application.

With the database in place, tags are then mapped to each asset. Tag mapping defines which database values represent runtime events, production counts, quality results, ideal rates, shifts, and batch information. InsightView separates this into two logical areas:

– General Tag Mapping, used for monitoring any asset-related data
– OEE Mapping, which links the specific tags required to calculate OEE and the Six Major Losses

The OEE Mapping includes downtime events, production output status (good, reject, startup reject), ideal production rates, planned quantities, shift timing, and batch details. By mapping these tags to the appropriate database tables and timestamps, InsightView can accurately calculate Availability, Performance, Quality, and loss categories for each shift, each batch, or across longer time horizons.

This structured, database-driven approach allows InsightView to work with real production data already being collected, eliminating the need for duplicate data entry while ensuring consistent, scalable OEE calculations across machines, lines, plants, and multiple sites.

Does InsightView support real-time data, historical analysis, or both?

InsightView supports both real-time monitoring and historical analysis, allowing manufacturers to move seamlessly from immediate visibility to long-term performance improvement. As new data is written to the database, InsightView continuously retrieves and processes the latest values, keeping dashboards and KPIs up to date with current operating conditions.

At the same time, InsightView stores and analyzes historical data to reveal trends over time, across shifts, batches, days, or more extended production periods. This enables users to identify recurring downtime patterns, performance degradation, quality issues, and opportunities for optimization that may not be visible in real time alone.

By combining real-time insight with historical context, InsightView helps teams shift from reactive firefighting to proactive decision-making. Operators gain instant awareness of what is happening now. At the same time, engineers and managers can analyze past performance to prevent future losses, improve scheduling, refine maintenance strategies, and drive continuous improvement across sites.

Does InsightView support real-time data, historical analysis, or both?

InsightView supports both real-time monitoring and historical analysis, allowing manufacturers to move seamlessly from immediate visibility to long-term performance improvement. As new data is written to the database, InsightView continuously retrieves and processes the latest values, keeping dashboards and KPIs up to date with current operating conditions.

At the same time, InsightView stores and analyzes historical data to reveal trends over time, across shifts, batches, days, or more extended production periods. This enables users to identify recurring downtime patterns, performance degradation, quality issues, and opportunities for optimization that may not be visible in real time alone.

By combining real-time insight with historical context, InsightView helps teams shift from reactive firefighting to proactive decision-making. Operators gain instant awareness of what is happening now. At the same time, engineers and managers can analyze past performance to prevent future losses, improve scheduling, refine maintenance strategies, and drive continuous improvement across sites.

How are dashboards and KPIs customized for different roles in InsightView?

InsightView is designed with role-based visibility in mind, recognizing that operators, engineers, plant managers, and executives all need different levels of information to make effective decisions. Using highly configurable dashboards, InsightView allows KPIs and visualizations to be tailored to each role without changing the underlying data model.

For operators and supervisors, dashboards typically focus on real-time status, such as machine state, current OEE, downtime events, and production counts, providing immediate visibility into what is happening on the shop floor. These views help teams respond quickly to issues as they occur.

Engineers and continuous improvement teams often require deeper analytical insight. Their dashboards may emphasize historical trends, loss breakdowns, root-cause analysis, and comparisons across shifts, batches, or assets. This level of detail supports data-driven troubleshooting, process optimization, and performance benchmarking.

At the management and executive level, InsightView dashboards aggregate data across lines, plants, or sites. High-level KPIs such as OEE trends, availability losses, throughput, and quality performance are presented in a concise, visual format that supports strategic planning and informed decision-making, without overwhelming users with unnecessary detail.

Because all dashboards draw from the same trusted data sources, InsightView ensures consistency across roles while still delivering the correct information to the right people at the right time. This flexibility allows organizations to align daily operations with long-term business objectives, all within a single ADISRA platform.

How do I access OEE dashboards, reports, and downtime tools in InsightView?

Accessing InsightView’s analytics and management tools begins by selecting the asset you want to analyze. Using the navigation menu, users choose a company, site, area, and then the specific asset they wish to monitor. This hierarchical structure ensures that all analytics and reports are always viewed in the correct operational context.

Once an asset is selected, InsightView provides quick access to key tools through an intuitive control bar. From there, users can open Advanced Analytics dashboards, including OEE Overview, Real-Time OEE, and Six Major Losses—along with OEE reports and Downtime Management. This makes it easy to move between real-time monitoring, historical analysis, and downtime tracking without leaving the selected asset view.

By anchoring analytics and reporting to a specific asset, InsightView ensures accuracy, consistency, and clarity, allowing users at every level to quickly access the insights they need to monitor performance, investigate losses, and take action.

From OEE Visibility to Actionable Insight

Overall Equipment Effectiveness is powerful when it moves beyond a single score and becomes a shared, actionable view of performance across machines, plants, and the enterprise. Throughout this Q&A, we have shown how InsightView helps manufacturers turn production data into meaningful insights, connecting assets, databases, analytics, dashboards, and roles into a single, scalable OEE platform.

Whether you are monitoring a single production line or managing performance across multiple sites, InsightView offers the flexibility small-to-mid-market manufacturers need to access powerful analytics without the cost or complexity of building and maintaining their own infrastructure. Delivered through the cloud, InsightView provides secure, company-isolated data access while offering the scalability to grow alongside your business.

The result is faster decision-making, clearer accountability, and a practical, cost-effective path to continuous improvement.

Ready to see InsightView in action?

Watch the full webinar replay to explore InsightView, schedule a private demonstration or training course here, or request a temporary account at info@adisra.com to experience InsightView firsthand. Discover how you can turn OEE data into measurable operational gains and drive continuous improvement across your organization.

ADISRA®, ADISRA’S logo, InsightView®, and KnowledgeView® are registered trademarks of ADISRA, LLC. 

© 2025  ADISRA, LLC.   All Rights Reserved.