With sizes as small as 55mm wide, these drives provide the needed motor speed control without taking up large amounts of panel space.
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39 | ON THE COVER: Control Engineering recognizes Engineering Leaders Under 40 class of 2025. Get to know those powering progress in automation, controls and instrumentation. Courtesy: Control Engineering
INSIGHTS
8 | Repairing paint on an automotive line with robots, machine vision; Draft guidelines offer new edge in software security; Study highlights ROI and AI applications in edge, private wireless; Energy-efficient new vision system offers unique eco benefits; Automation education: recent, upcoming events
16 | Everything you need to know about telecom design
20 | How to simplify panel-building with Single Pair Ethernet
22 | PID spotlight, part 21: Noise: Can I tune around it? 25 | Why is AI popular but difficult to implement in industry?
26 | Expectations, reality and AI in industrial process modeling 30 | Advantages of multi-axis servo drives in the world of automation
32 | How distributed energy resources empower smart grids
36 | Machine safeguarding and why you need to prioritize it now
39 | COVER: Powering Progress: Meet the 2025 Engineering Leaders Under 40
INNOVATIONS
46 | More New Products for Engineers at www.controleng.com/products
Powerful spindle motors for machine tools, motion controls; Advanced industrial platform: Powerful, scalable, open; New tower lights for smarter industrial signaling; Process sensor for explosive areas; Smart power supplies with standard and IO-link options
47 | Back to Basics: Cybersecurity
91% of critical infrastructure firms report OT cybersecurity breaches, Forrester study finds.
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Insights for automation professionals
Control Engineering experts cover automation, control, and instrumentation technologies for automation engineers who design, integrate, implement, maintain, and manage control, automation, and instrumentation systems, components, and equipment to do their jobs better across process and discrete industries.
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INSIGHTS
u Control Engineering hot topics-August 2025 (A) www.controleng.com/control-engineering-hot-topics-august-2025
u Powering the electric future: Technology, policy and the path ahead (B)
u Eight best automation platform applications awarded
u Research investment aims to streamline lab automation (C) www.controleng.com/research-investment-aims-to-streamline-lab-automation
u AI and tech trends to support growth through 2026 www.controleng.com/ai-and-tech-trends-to-support-growth-through-2026
u Shell modernizes refinery control with software-defined automation www.controleng.com/shell-modernizes-refinery-control-with-software-defined-automation
u Pack Expo Las Vegas: A first look at the machines shaping the future of packaging
u New testbed applies composability framework and AI evaluation www.controleng.com/new-testbed-applies-composability-framework-and-ai-evaluation
WEBCAST
u How to select the right controller type for the automation application (D) www.controleng.com/selecting-the-right-controller-type-for-the-automation-application
ANSWERS
u PID spotlight, part 20 www.controleng.com/control-systems
u Roundtable: Emerging technologies, industrial networks, Industry 4.0 www.controleng.com/roundtable-emerging-technologies-industrial-networks
u How to accelerate automation using simulation, digital twins www.controleng.com/how-to-accelerate-automation-using-simulation-digital-twins
u Why thoughtful integration beats quick AI fixes in MES www.controleng.com
u How to prevent industrial drive corrosion: 5 strategies (E) www.controleng.com/how-to-prevent-industrial-drive-corrosion-5-strategies
(C)
(A)
Courtesy: Emerson and AspenTech
Courtesy: Mark T. Hoske, Control Engineering at SPS Atlanta 2025
Courtesy: Festo
Courtesy: Control Engineering webcasts
Courtesy: ABB Drive Products (B)
Repairing paint on an automotive line with robots, machine vision
uGeneral Motors and three automation providers, 3M, Encore / Inovision Inc. and Fanuc America, explained how integrated technologies are achieving robotic paint repairs on a moving high-volume automotive paint shop, at Automate 2025, by the Association for Advancing Automation (A3). The application, called the first of its kind, was described at the conference in Detroit, May 12-16. The related show had more than 875 exhibitors, more than 40,000 registrants, and more than 140 conference sessions on robotics, machine vision, artificial intelligence and other industrial automation topics. The application session called “The final frontier of automation in a high-volume automotive paint shop: Robotic paint repair on a moving line,” discussed integration of robotics, motion control, machine vision and abrasive technologies, as described by:
• Ryan Odegaard, global director paint, General Motors
In addition to knowledge about the application, materials and abrasives, robotics and motion, integration and vision expertise was needed covering multiple areas of detection and correction, explained Gary Gagne, product development manager, Encore / Inovision Inc., at the Automation 2025 session, “The final frontier of automation in a high-volume automotive paint shop: Robotic paint repair on a moving line.” Courtesy: Mark T. Hoske, Control Engineering, WTWH
• Marcus Pelletier, global director R&D, 3M Co.
• Tom VanderPlas, senior staff engineer, paint, Fanuc America
• Gary Gagne, product development manager, Encore / Inovision Inc.
Odegaard said the finishing system for Cadillacs may create certain imperfections that require understanding the inspection process to catch everything. Visual classification of paint quality with humans is subjective. But data is needed to prevent future imperfections. The process matters. Repairing paint on a high-volume moving automotive paint line is revolutionary, he said. The software measures results, validates and correcting assumptions ahead of time, Pelletier said. It’s low code or no code software. The robot moves and bends as needed in real time, with the robot controller every 10 milliseconds instruction for precise control. Tooling sensors provide feedback to modify trajectories as needed, Pelletier said. It’s a multivariable process for appropriate speed and motion control.
VanderPlas at Fanuc brought improved robotic technologies to the application. A modular rail system moves a 6-axis robot to keep robot synchronized with the moving automobile, up to 1,500 mm/sec for a 1,200 kg robot. Advanced tracking offers precision. Painting experience is applied to sanding also. An encoder connected to a conveyor supplies 500 pulses per inch to controllers and programmable logic controllers, to provide line tracking from the robot to conveyor. Streamed motion provides robot control via an external controller. Gagne at Encore / Inovision worked on the integration and vision expertise for detection and correction, locating and determining imperfection properties. Defect
Study highlights ROI and AI applications in edge, private wireless
Nokia, in collaboration with GlobalData, has released Nokia 2025 Industrial Digitalization Report. The study found that 87% of organizations adopting on-premise edge and private network reported achieving return on investment within one year, with applications that incorporate AI. In addition, 81% of industrial enterprises reported reduced setup costs, with more than half noting savings of 11% or more. Ongoing costs also lower for 86% of companies, with 60% r indicating savings of at least 11%.
The report draws on insights from 115 industrial enterprises across manufacturing, energy, logistics, mining, and transportation in Australia, Germany, Japan, United Kingdom and United States.
This is important because manufacturing, processing and other facilities using automation often are seeking ways to expand communications among devices, systems, automation, controls and instrumentation to improve efficiency and throughput in secure and cost-effective ways. ce
Edited
by Puja Mitra, WTWH Media, for Control Engineering, from a Nokia news release.
classification and machine learning works with a large database of defects and properties, processing 10GB of images in 60 seconds. Simulation builds models in 3D space. Vision offers correction robot motion and automatic path generation, imperfection repair coordination, advance tracking calibration and 3M’s repair recipe generation. More details and photos are available from Control Engineering. www.controleng.com/repairing-paint-on-an-automotive-line-with-robots-machine-vision ce
Mark T. Hoske is editor-in-chief, Control Engineering, WTWH Media, mhoske@wtwhmedia.com.
‘
Draft guidelines offer new edge in software security
uThe U.S. Department of Commerce’s National Institute of Standards and Technology (NIST) is working with industry partners through a consortium to improve software security and reduce vulnerability to cyber threats. The Software Supply Chain and DevOps Security Practices
NIST is developing guidelines to support security throughout the software development life cycle.
’
Consortium is part of NIST’s implementation of White House Executive Order (EO) 14306, Sustaining Select Efforts to Strengthen the Nation’s Cybersecurity and Amending Executive Order 13694 and Executive Order 14144. As directed by the order, the consortium will develop guide-
NIST Consortium and draft guidelines focus on improving software development security. Courtesy: NIST
lines based on NIST’s Secure Software Development Framework (SSDF) to support secure software practices.
Led by NIST’s National Cybersecurity Center of Excellence (NCCoE), the consortium includes 14 member organizations. The group’s objective is to develop guidelines to support security throughout the software development life cycle, including planning, testing, deployment, operation and maintenance. ce
Edited by Puja Mitra, WTWH Media, for Control Engineering, from a NIST news release. www.controleng.com/draftguidelines-offer-new-edge-in-softwaresecurity
Energy-efficient new vision system offers unique eco benefits
Leverage the cloud to maximize industrial data analytics value: 6 ways
As industries digitize, softwareas-a-service (SaaS) platforms for industrial analytics offer manufacturers six strategic advantages.
1. Cost-effectiveness: SaaS removes the need for heavy capital investments in on-premises servers, storag, and IT personnel.
2. Scalability and flexibility: SaaS platforms grow with needs.
3. Automatic updates and maintenance
4. Accessibility and collaboration: Cloud-based analytics platforms can be accessed with an internet connection.
5. Security and compliance can include encryption, intrusion detection, access control and audit logs.
6. Centralization and consistency for complex organizations. ce
-Paolo Braiuca leads the Life Sciences practice at Seeq
AUTOMATION EDUCATION
Recent events
• Fabtech, SPS Atlanta 2025, Inductive Automation Ignition Community Conference, Weftec, Pack Expo Las Vegas, RoboBusiness. Watch for more at www.controleng.com.
Upcoming events
• A3 International Robot Safety Conference, Nov. 3-5, Houston
A recently developed, energy-efficient artificial vision system, designed using brain-like computing principles and incorporating honey-based materials, may offer a more sustainable approach to electronic component design. Engineers from the University of Glasgow, in collaboration with researchers from São Paulo State University (UNESP) and Hong Kong Metropolitan University, have developed a system that uses organic, biodegradable and recyclable materials to detect and retain color data while operating with minimal power consumption.
The team’s system, called an Electrolyte-Gated Organic Field-Effect Transistor (EGOFET), integrates three core functions —light sensing, information processing, and memory storage — into a single unit designed to emulate aspects of visual perception. It also retains data without power, a characteristic known as non-volatility. ce
Page 42 of the Control Engineering July/August edition incorrectly spelled the company name for Migatron in the product write-up: "New ultrasonic sensor supports use in hazardous locations."
Latest automation mergers, August 2025
Bundy Group, an investment bank and advisory firm that specializes in the automation segment, listed 16 August 2025 mergers and acquisitions and capital placement activities, involving Ametek, Applied Industrial Technologies, Comau and STMicroelectronics, among others. See more online.
Comau acquired Automha, July 31
Comau, provider of Industry 4.0-enabled automation systems, products and services including robotics, has completed the full acquisition of Automha S.p.A. and its global subsidiaries, strengthening its position as a leading Italian automation hub. The deal leverages strong synergies between the two companies to drive added value for customers and shareholders worldwide. Automha will continue operations and opportunities under Comau’s ownership.
STMicroelectronics buys NXP’s MEMS sensors business, July 24
STMicroelectronics has acquired NXP Semiconductors’ MEMS sensors business, enhancing its global sensors portfolio. The acquisition will strengthen ST’s position in automotive safety and industrial applications while complementing its existing MEMS technology. The move is expected to expand opportunities in automotive, industrial and consumer markets.
Ametek acquired Faro Technologies, July 21
Ametek, a technology provider that includes automation, testing and energy products and services, completed its acquisition of Faro Technologies Inc. for approximately $920 million in cash, resulting in the delisting of Faro’s common stock from Nasdaq. The transaction strengthens Ametek’s position as a glob-
al provider of industrial technology solutions with annual sales of around $7.0 billion.
Accenture buys Systema, July 1
Accenture acquired Systema, a Dresden-based provider of software solutions and consulting services for manufacturing automation. Systema has expertise in semiconductors and high-tech industries. ce
Clint Bundy is managing director, Bundy Group. Edited by Mark T. Hoske, editor-inchief, Control Engineering, WTWH Media, mhoske@wtwhmedia.com.
Online
controleng.com u
Manufacturing sector shows little growth in Q2 amid uncertainty
RESEARCH by market intelligence firm Interact Analysis reported that manufacturing growth has been flat, with minimal change since Q1. The findings are part of the company’s latest update to the Interact Analysis Manufacturing Industry Output Tracker (MIO Tracker). Low growth and limited investment are likely linked to uncertainty over rapidly changing U.S. trade policies. Some analysts had predicted that new tariffs could trigger a recession, but this has not occurred to date. In 2025, global manufacturing output projected to grow 2%, with most growth in China and the United States, while Europe is expected to see a modest decline. Understanding current, past, and projected market conditions is important in a complex sector. This report measures
the total value of manufacturing production across more than 102 industries and 45 countries, including 18 years of historical data covering a full business cycle from before the recession to the present. The country data is organized around a common taxonomy to support consistent comparisons, and the report includes five-year forecasts. ce
Edited by Puja Mitra, WTWH Media, for Control Engineering, from an Interact Analysis news release.
Uncertainty around U.S. tariffs seems to be dampening growth in the global manufacturing industry. Courtesy: Interact Analysis Manufacturing Industry Output Tracker (MIO Tracker) https://bundygroup.com Search on Bundy at www.controleng.com for more merger and acquisition news. http://controleng.com/latest-automation-mergersjuly-2025-graybar-siemens-voliro/
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Joe Martin, president and founder Martin Control Systems, www.martincsi.com
Rick Pierro, president and co-founder Superior Controls, www.superiorcontrols.com
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WTWH Media Contributor Guidelines Overview
Content For Engineers. WTWH Media focuses on engineers sharing with their peers. We welcome content submissions for all interested parties in engineering. We will use those materials online, on our Website, in print and in newsletters to keep engineers informed about the products, solutions and industry trends.
* Control Engineering Submissions instructions at https://www.controleng.com/connect/how-to-contribute gives an overview of how to submit press releases, products, images and graphics, bylined feature articles, case studies, white papers and other media.
* Content should focus on helping engineers solve problems. Articles that are commercial in nature or that are critical of other products or organizations will be rejected. (Technology discussions and comparative tables may be accepted if nonpromotional and if contributor corroborates information with sources cited.)
* If the content meets criteria noted in guidelines, expect to see it first on the website. Content for enewsletters comes from content already available on the website. All content for print also will be online. All content that appears in the print magazine will appear as space permits, and we will indicate in print if more content from that article is available online.
* Deadlines for feature articles vary based on where it appears. Print-related content is due at least three months in advance of the publication date. Again, it is best to discuss all feature articles with the content manager prior to submission. Learn more at: https://www.controleng.com/connect/how-to-contribute
How to continuously improve careers in automation, controls
Control Engineering Engineering Leaders Under 40 provide great reminders that career development requires measurement, logical decisions and acting upon that knowledge by applying the control loop.
The 2025 class of Engineering Leaders Under 40 provides career inspiration from early- to mid-career professionals in automation, controls and instrumentation. Careers in automation can be enhanced by applying control theory to automation, controls, energy, infrastructure and other industries. Apply the control loop to your career: Take measurements, decide what needs to be done and do it. Here’s a sampling of career development advice; see more in this issue and online.
Measure what you’re doing
Michael Fazzini, director of operations, Actemium Avanceon mentors and advocates for creative problem-solving to drive transformation in control systems integration.
Emulation tools and Industry 4.0 adoption help digital transformation demonstrated Sharath Kumar Kanniyappan, senior controls engineering supervisor at Honeywell Intelligrated.
Actuate: Even small steps add up
When performing advanced control systems upgrades or when helping students improve in cross-country, Brady Darrough, automation engineer at Huffman Engineering, knows that measurements help ensure improvements over time.
Chris Edwards, CEO, Sensory Robotics, is changing how sensors are applied to motion-controls by replacing traditional safety devices with reconfigurable, vision-based systems for robotics.
Hannah Bonaguidi, project manager at Catalyx, skilled in process automation and analytical technologies, reminds us that quick, clear directions can improve guidance in unfamiliar and rapidly changing circumstances.
Decide what needs doing, optimize
Projects in modern manufacturing improve when blending control system expertise with big-picture strategy, as demonstrated by Johnnie Burness, engineering manager – factory systems and test at Verdagy.
Danny Dylong, director, manufacturing, The RoviSys Co. is building a dynamic and people-focused engineering culture for automation projects worldwide in markets such as aerospace, electric vehicles and defense.
Jason Cary, senior manufacturing engineer, ContiTech USA LLC, boosts performance by sharing knowledge in safety, throughput and quality across facilities.
Mena Francis, project manager, Applied Control Engineering, applies device manufacturing, GAMP and ISO/Food and Drug Administration (FDA) standards to drive measurable improvements in process performance while mentoring future engineers and championing continuous learning.
Positive feedback loop: Keep applying what you know
Even when things seem a little overwhelming, think again applying incremental improvements over time to continually improve. Congratulations to the 2025 class of Engineering Leaders Under 40. ce
Learn more from the Engineering Leaders Under 40 class of 2025.
https://www.controleng.com/leaders-under-40/
Mark T. Hoske Control Engineering
Josh Bryant, PE; CDM Smith; Boston
Everything you need to know about telecom design
Integrating multiple technologies supports high-speed and secure communication across local area networks (LANs) and wide area networks (WANs).
In our increasingly connected world, smart technology is everywhere, meaning telecom design is more important than ever. Most new devices have a communication or data collection component. Telecom design should be included in most modern engineering projects.
KEYWORDS: System integration, telecommunications ONLINE www.controleng.com/ industrial-networking CONSIDER THIS Control system network enclosures may be improved by considering telecommunication design. Online controleng.com u
FIGURE 1: There are many similarities in the design of control system network cabinets and telecommunications cabinets. Control system network cabinets can utilize many telecommunications design concepts to protect and improve the capabilities of the control system. Images courtesy: CDM Smith
Telecommunications design provides reliable, scalable and secure data transmission. The applications range from industrial buildings to largescale campuses. Understanding the basics of telecommunications design can provide engineers with the knowledge they need to improve their designs by ensuring they include a communication infrastructure that will meet the requirements of the current application as well as tomorrow’s communication needs.
One important application of telecommunications design is control system design. Technology advances have vastly expanded the performance capabilities of control systems; but these systems rely on their communication networks. To keep up with these advances, the telecommunications network must also evolve. Consider how key telecommunications topics can improve control system design.
What is telecom design?
At its core, telecommunications design is the planning of systems that transmit information over distances via electrical or optical signals. Such infrastructure can transmit data from many different sources and systems, including voice and data, electronic security and building management systems. The success of any communication system is measured by its speed, reliability, capacity and scalability.
Telecommunications design is governed by several different industry standards. Key industry standards to be aware of are those published by Building Industry Consulting Service International (BICSI). The BICSI guidelines are considered the
“gold standard” of telecommunications design and adherence to these standards is critical for achieving an effective design. In addition to published standards, BICSI also offers certifications for design professionals, such as the Registered Communications Distribution Designer (RCDD) and the Data Center Design Consultant (DCDC) certification.
What are the fundamentals of telecom design?
Every telecommunications design consists of the data being transferred, the transmission media and the main nodes that transfer data. The main components of these systems may vary, but there are a few design characteristics that must be considered in every application.
Data transfer fundamentals
Data transfer is the movement of information from a source to a destination across a network. The design of data transfer entails selecting appropriate transmission media (fiber optic, copper or wireless), choosing proper networking topologies (star, bus, ring or mesh) and specifying bandwidth requirements.
Key data transfer concepts include the following:
• Bandwidth: The maximum rate of data transfer, typically measured in megabits per second (Mbps) or gigabits per second (Gbps).
• Latency: The time it takes for data to travel from a source to its destination.
• Protocols: The protocol determines how data are formatted and transmitted. Typical protocols include Ethernet, TCP/IP and Modbus.
• Network topographies: The arrangement of devices and connections within a network that defines how data flows between nodes. Topologies such as a mesh or ring network provide redundant paths that increase the system’s reliability.
• Cybersecurity: The protection against interception and unauthorized access to the network. The network infrastructure should consider the use of firewalls, physical security, intrusion detection and secure authentication protocols to safeguard data integrity and confidentiality.
Structured cabling
Cable types used for telecommunications design include fiber optic and copper. A typical cabling system will include these types in a different form factors. While not comprehensive, the following is
a widely adopted list of cable types that form the basis of most modern telecommunications designs.
• Horizontal cabling: Runs from telecommunications rooms to individual outlets or equipment within a building. Copper cable (CAT5e, CAT6 and CAT6A) is the most common horizontal cable. For optimal performance, copper cable runs are limited to approximately 300 feet.
• Vertical or backbone cabling: Connects telecommunications rooms and entrance facilities across floors and buildings. Copper cable is also
2: A telecommunications space layout should be designed to accommodate telecommunications cabinets, cable routing and all necessary electrical and security equipment.
FIGURE 2: Telecom cabinets are used to organize structured cabling using fiber and copper patch panels, network switches and cable management.
FIGURE
ANSWERS
FIGURE 3: Proper grounding and bonding of control systems, as is required for telecommunications systems, can protect the system and ensure a common grounding point.
Insightsu
TELECOM DESIGN INSIGHTS
uUnderstanding the fundamentals of telecom design can help engineers meet the requirements of their applications.
uTelecom design is governed by several different industry standards.
uAppropriate telecom design can enable engineers to design systems that work across a variety of applications.
the most common vertical cable for vertical cabling within a building. If the backbone cable is installed between buildings, fiber optic cable (single-mode or multimode) should be used.
• Patch cables: Facilitates organized and flexible connections (copper or fiber optic) across patch panels in a telecommunications cabinet or rack.
• Outside plant (OSP) cable: Connects a building or site to an outside network, typically via buried conduit or run on aerial poles. This cable should be designed to withstand environmental conditions. Armored or shielded single-mode fiber optic cable is typically used.
Telecom space design
The telecommunications room is the main hub of a communication network that facilitates the transfer of system data. There is a dedicated space for the telecom rack or cabinet, network switches, cable distribution and proper grounding of the network. The critical considerations when designing a telecommunications space include:
• Layout and clearances: The space should be sufficiently sized (based on the building telecom load) to meet BICSI standards and provide proper clearance around the telecom cabinets for maintenance. The layout should consider dedicated space for any electrical and heating, ventilating and air-conditioning equipment as well as expansion.
• Rack or cabinet configuration: Racks and cabinets should have standard 19-inch frames to accommodate industry standards for rack-mounted equipment. The number of racks or cabinets must account for sufficient switches and patch panels to support the load and expansion.
• Pathways: Cable trays, conduits and raceways must be planned to distribute cables from the racks or cabinets. Power and data cables should be separated to minimize electrical interference.
• Grounding and bonding: A telecommunications grounding busbar must be installed and bonded to a building’s main grounding electrode system using a grounding conductor. Metal components of the telecommunications system should be bonded to the grounding busbar to protect the system and ensure a common grounding point.
• Security: Restricted access to the telecommunications room should be included in the design to prevent unauthorized individuals from accessing the sensitive equipment and data.
Telecom design, control systems
Control systems, used to monitor and control industrial processes, are composed of field devices and controllers connected by a network of communication infrastructure. Control designs often rightfully focus on equipment such as programmable logic controllers (PLCs), human machine interfaces (HMIs) and instrumentation. This equipment can only function properly if the communication network that connects them is designed properly. Often, the personnel working on control system design are not well-versed in telecommunications design; this presents an opportunity to improve control systems by applying the lessons of telecommunications design. See more online about:
• Optimization of network design
• Structured cabling
• Layout and installation.
Applying telecommunications principles to control system architectures can contribute to safer and more efficient industrial operations. ce
Josh Bryant, PE, is an automation engineering with CDM Smith. Edited by Sheri Kasprzak, managing editor of Automation & Controls, WTWH Media, skasprzak@wtwhmedia.com.
ANSWERS
Kelly Passineau, Rockwell Automation
How to simplify panel-building with Single Pair Ethernet
New Ethernet-based connection options can reduce wiring complexity and shorten the panel-building process.
Digita lization may have transformed many aspects of industrial automation, but Single Pair Ethernet (SPE) can assist with control panels, which remain stubbornly unchanged. Despite advances in smart devices and networked systems, most in-cabinet components are still hardwired, requiring hours of manual labor and hundreds of individual connections. That’s changing, thanks to new Ethernet-based technologies that are streamlining panel design and deployment.
Using SPE technology, original equipment manufacturers (OEMs) and integrators can connect in-cabinet components over a single flat ribbon cable. This eliminates the need for many hardwired connections, creating a cleaner and more modular panel.
LEARNING OBJECTIVES
Understand how Single Pair Ethernet (SPE) technology simplifies control panel design by reducing wiring complexity and accelerating build times.
Recognize the operational benefits of connecting in-cabinet components to a network for improved diagnostics and predictive maintenance.
Evaluate how simplified control panel wiring supports sustainability, space efficiency and ease of adoption.
But the benefits go far beyond aesthetics and streamlined wiring. SPE enables faster cabinet builds, easier diagnostics and more compact, sustainable designs — while extending Ethernet/ internet protocol (IP) deeper into the control architecture for OEMs and integrators.
Single Pair Ethernet offers a simpler way to connect
Busy in-cabinet control wiring for components like motor starters, relays, push buttons and panel operators creates challenges across the life of a cabinet. For starters, it must be customized to each machine’s functions and each end user’s control requirements. For every new machine, panel schematics must be created to outline how every component will be connected to do its job per application requirements.
Traditional panel wiring is time-consuming and error-prone. Each wire must be cut, stripped, labeled and terminated, often taking up to six minutes per connection. Multiply that by hundreds of connections and the labor hours add up fast. Worse yet, connections can loosen during shipping and each wire becomes a potential failure point once the panel is in service.
The challenges continue after a cabinet is deployed. Extensive hard wiring can create large cabinets that take up precious floor space in a production environment that can’t be locally or remotely monitored on a network.
Connecting in-cabinet components with SPE addresses all these challenges. Now, complex discrete wiring — including potentially needing several wires just to connect one component — can be consolidated into single connections on a simple piece of media.
This creates a few powerful outcomes for OEMs and integrators, as well as their customers.
How SPE enables faster cabinet design
Using a single ribbon cable to connect in-cabinet components eliminates extensive control wiring. And components can be quickly snapped onto this ribbon without any special tools. While SPE technology doesn’t eliminate all panel wiring — component power is still hardwired — it can make a noticeable impact. Field tests have shown that replacing control wiring with SPE can reduce wiring time by up to 80%. SPE technology also helped participants in the tests reduce testing time by up to 50% and engineering time as much as 30%.
This not only accelerates panel assembly for OEMs, integrators and end-users, but also eases the burden on engineering teams already stretched thin by labor shortages.
Programming and configuring components can also be simplified when they’re connected using
SPE. For example, they can benefit from the “premiere integration” offered in some suppliers’ design software. With this enhanced integration, in-cabinet components will look the same as a supplier’s other technologies in the software. Custom add-on profiles can also be used in the software to ease the programming of these components.
Ways SPE opens better insights for the end user
For end users, SPE opens the door to deeper visibility into their automation infrastructure. In-cabinet components that were once isolated can now be monitored like any other networked device. This means more granular diagnostics, better predictive maintenance and faster rootcause analysis.
Imagine detecting a motor starter drawing excess current before it fails — or accessing fault logs remotely to troubleshoot an issue without dispatching a technician. With SPE, these capabilities become standard.
OEMs also benefit from this increased transparency. Remote access to diagnostic data allows them to support customers more effectively, reduce service costs and strengthen long-term relationships.
Building more sustainable designs with SPE
The simpler in-cabinet connections made possible with SPE technology can significantly reduce the amount of wiring used in panels. That translates into less copper and plastic being used, resulting in more environmentally friendly cabinets. In one case, SPE technology eliminated more than 500 feet of wiring from a panel, resulting in a 20% reduction in size and a one-third reduction in
‘For end users, SPE opens the door to deeper visibility into the automation infrastructure.
weight. Smaller, lighter panels are not only more eco-friendly, but they also are less costly to ship and can provide valuable space savings in production environments.
Creating an easy path to adoption
Despite its transformative potential, SPE is easy to implement. OEMs and integrators who have participated in early field trials reported minimal learning curves and rapid adoption. The technology is also developed in compliance with global cybersecurity standards like International Electrotechnical Commission (IEC) 62443 to protect in-cabinet component data like how other data in an automation infrastructure is safeguarded.
The control panel is long overdue for a digital-era upgrade. With Single Pair Ethernet and EtherNet/IP in-cabinet solutions, OEMs and integrators can reduce complexity, accelerate deployment and deliver smarter, more connected systems to their customers.
The only question for OEMs and integrators now is how much longer they’re willing to let fully hardwired panels slow them down. ce
Kelly Passineau is a product manager at Rockwell Automation. Edited by Sheri Kasprzak, managing editor of Automation & Controls, WTWH Media, skasprzak@wtwhmedia.com.
Insightsu
SINGLE PAIR ETHERNET INSIGHTS
uSingle Pair Ethernet can empower simpler control panel design by reducing wiring complexity and shortening build times.
uUsing a single ribbon cable to connect in-cabinet components eliminates extensive control wiring.
uProgramming and configuring components can also be simplified when they’re connected using SPE.
Ed Bullerdiek, process control engineer, retired
PID spotlight, part 21: Noise: Can I tune around it?
I have a noisy process. How does that affect my PID controller? Can I tune my controller like I always do, or do I have to change tuning because of the noise?
In the real world process noise is everywhere, and it cannot be ignored. Process noise adversely affects how a proportional-integral-derivative (PID) controller works. If it is very severe, we must take measures to minimize process noise, and unfortunately these measures also adversely affect PID controller performance.
FIGURE 1: PID controller gain response to white noise. Tuning constants are K = 1.0, Ti = 0 repeats/minute, Td = 0 minutes. White noise limited to +/- 5%. Parallel PID control algorithm. All images courtesy: Ed Bullerdiek, retired control engineer
In this and the next two installments we are going to cover how noise:
• Affects controller gain, integral and derivative response.
• Affects open, closed and heuristic controller tuning methods.
• Can be managed by signal filtering. We will also examine the impact filtering has on controller tuning and performance.
What is noise in process plants?
The two types of noise we typically run into in industrial process plants are:
• White noise: Noise that doesn’t have a pattern. Statistically white noise has low autocorrelation, which is a fancy way to say you cannot predict the next value from the current value or that it has no trend.
• Cyclic noise: Noise that contains one or a collection of waves, typically a sine wave. These can be caused by vibrating pipes, motors, cycling equipment, etc. If cyclical noise is your main problem a moving average filter may be a better solution than the typical first order (low pass) filter.
The one common property of noise in a process control context is it is fast relative to the actual process response. We would like our PID controller to ignore it, but unfortunately if it is measured the controller is going to respond whether it needs to or not. Understanding how a PID controller responds to process noise will help us develop the best approach to managing noise. This can include filtering and tuning tweaks as well as the judicious use of advanced PID features.
Understand how controller gain, integral and derivative respond to process noise.
Know how to tune a controller to accommodate process noise while retaining controller response and understand the tradeoffs.
Know the quick filter setting guideline.
CONSIDER THIS
A PID controller responds to whatever it sees regardless of whether it is real or just noise. What must we do to ensure the controller responds to the signal and doesn’t respond to the noise?
How does noise affect controller gain?
In Figure 1 we see how white noise is passed through to the controller output (OP) by the controller gain (K – gold line). The amplitude of OP swings depends on the controller gain; higher gain results in larger swings. If the process is slow like this one the excess valve movement doesn’t materially affect the process. It does, however, accelerate valve wear. If the process were faster the excessive valve movement could set up a positive feedback cycle that would increase the apparent noise and potentially affect controller stability.
Figure 2 explores what can happen when a fast process has (in this case) cyclic noise that is near the loop’s resonant frequency. Shortly after the +/5% cycle starts at the 1 minute mark the feedback quickly increases the swing to approximately +/9%. Depending on the approach to resonant frequency the swings could become very pronounced. You will need to pay careful attention to managing noise when this happens.
With respect to controller tuning if there is unmitigated noise controller gain will often be lowered to reduce the impact of process noise on the process. This may negatively impact controller performance.
Noise affect on controller integral?
Integral because of its nature is largely immune to fast process noise. In Figure 3 if you were to only look at the controller output (OP) you would be hard pressed to say that there was any process noise at all.
Figure 4 shows us that even when a fast process has comparably fast integral tuning, even cyclic noise is only slightly reflected in the controller output. As noted in the controller gain section, unmitigated noise may lead to reducing controller gain
FIGURE 2: PID controller gain response to cyclic noise. Tuning constants are K = 1.0, Ti = 0 repeats/minute, Td = 0 minutes. Cyclic noise +/- 5% on 20 second cycle. Parallel PID control algorithm.
FIGURE 3: PID controller integral response to white noise. Tuning constants are K = 0, Ti = 0.5 repeats/minute, Td = 0 minutes. White noise limited to +/- 5%. Parallel PID control algorithm.
to manage stability. Integral’s immunity to noise allows us to speed up integral to help make up for reduced controller gain – with the tradeoff that integral is slower to respond to disturbances and can produce overshoot and controller oscillations.
ANSWERS
FIGURE 4: PID controller integral response to cyclic noise. Tuning constants are K = 0, Ti = 1.0 repeats/minute, Td = 0 minutes. Cyclic noise +/- 5% on 20 second cycle. Parallel PID control algorithm.
FIGURE 5: PID controller derivative response to white noise. Tuning constants are K = 0, Ti = 0 repeats/minute, Td = 0.05 minutes. White noise limited to +/- 5%. Parallel PID control algorithm.
Noise affect on controller derivative
Figure 5 illustrates why derivative is rarely used, and why conventional wisdom often counsels against its use. Derivative greatly amplifies process noise. In this case a quite modest derivative tuning constant of 0.05 minutes converts a +/- 5% white noise signal into a controller output response peaking at +/- 25%. Obviously in the real world no control valve can respond this fast, but it just might shake itself apart trying.
There’s no point in putting up a figure showing derivative response to cyclic noise. It’s just going to show more of the same; a relatively small noise band gets multiplied by a modest derivative constant.
In summary, process noise is passed through by gain, mostly has no effect on integral, and is multiplied by derivative. From a practical standpoint this means that a noisy process will be tuned with less gain, more integral, and will never have derivative. Since controller gain is our primary tool for disturbance suppression, and derivative can be deployed to help, reducing controller gain and eliminating derivative will permit disturbances to create bigger and longer-lasting process upsets.
Notes: how to adjust tuning with noise
Process noise causes excessive controller output movement and in the worst cases can cause excessive cycling of a process. Controller tuning can be modified to minimize the impact of noise by eliminating derivative, lowering controller gain and speeding up integral. This will slow down controller response, especially if the controller would benefit from the application of derivative. A simple low pass filter can be used to minimize noise, but adding a filter is the equivalent of adding another lag to the process. This will increase apparent process deadtime, which may require slowing the controller down. Regardless, it may still allow more aggressive tuning by tamping down the process noise. ce
Ed Bullerdiek is a retired control engineer with 37 years of process control experience in petroleum refining and oil production. Send comments and questions to freerangecontrol@ameritech.net. Edited by Mark T. Hoske, editor-in-chief, Control Engineering, WTWH Media, mhoske@wtwhmedia.com.
Why is AI popular but difficult to implement in industry?
Professional industry knowledge and experience must be transferred into algorithmic constraints to ensure that artificial intelligence models align with real-world requirements.
The global manufacturing industry’s attention is focused on artificial intelligence (AI), hoping that this technological revolution can break through efficiency bottlenecks and reshape the industrial landscape. Industrial AI presents two fragmented sides. One is the hot scene driven by capital. The other is a perplexed gaze of engineers in industrial enterprises. Why is industrial AI implementation progressing slowly?
The gap between the “ideal and reality” of industrial AI largely stems from essential differences from commercial AI, which is rapidly applied and often breaking boundaries. Wang Kuanxin, an industrial AI expert at Supcon, said the data format in the industrial field, known as the B-end, differs from the C-end. The development of industrial AI must be based on massive industrial data, especially data with strong temporal characteristics, while deeply integrating industry knowledge, experience and physical mechanisms, to find a unique innovation path.
“Many large models from the commercial field simply have been migrated to the industrial field, mainly focusing on surface applications, such as information acquisition and question-and-answer knowledge. While these applications have improved the efficiency of knowledge acquisition, they have yet to address core industrial pain points, such as intelligent control, quality improvement and efficiency enhancement, and energy conservation and emissions reduction,” Wang Kuanxin said.
Algorithms, computing power and data are widely recognized as the three core elements of AI. For industrial AI, the importance of the “scenario” dimension has been elevated to an unprecedented level, forming the “four pillars” that drive implementation with the first three elements. This stems from a fundamental characteristic of industrial applications: high fragmentation and differentiation. Different industries, and even different sub-sectors within the same
industry, have vastly different production processes, core physical/chemical mechanisms, production equipment and pain points that need to be addressed. This scenario specificity that severely constrains the scalable replication and rapid adoption of industrial AI technology. Unlike commercial AI solutions, which can be relatively generic and deployed quickly, industrial AI faces the challenge of “customization” in each sub-sector and even specific production lines. Attempting to solve all industrial problems with a generic model or platform is simply not feasible.
Algorithms with industry knowledge
For technical architecture and core algorithms, industrial AI demonstrates uniqueness. While the outside world focuses on the “computing power competition” of AI, the industrial sector has different priorities. Compared to commercial scenarios, industrial data is significantly smaller in scale, so the reliance on computational power is not as high. However, the unique characteristics of industrial data—such as temporal nature, low signal-to-noise ratio and multiscale—dictate that industrial AI algorithms must be deeply integrated with industry knowledge. Otherwise, it would be difficult to uncover the intrinsic connections and potential value within industrial data.
Wang Kuanxin said that in process industries, the “implicit knowledge” such as the physical mechanisms of equipment operation and the laws of chemical reactions is beyond the grasp of general AI models. In discrete industries where most processes are “visible and tangible,” this implicit knowledge must be analyzed and explored through process simulation, raising the professional barriers for addressing such issues. ce
Stone Shi is executive editor-in-chief, Control Engineering China. Edited by Mark T. Hoske, editorin-chief, Control Engineering, WTWH Media, mhoske@wtwhmedia.com.
FIGURE: In process industries, the “implicit knowledge” such as the physical mechanisms of equipment operation and the laws of chemical reactions is completely beyond the grasp of general AI models. Courtesy: Control Engineering China
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KEYWORDS: Industrial AI, process manufacturing AI, discrete manufacturing AI
CONSIDER THIS Are your AI efforts delivering industry-level expertise? ONLINE
See two more sections with this article online:
-Breaking the double shackles of industrial data
-Hidden barrier: Industrial sector knowledge is required
http://www.cechina.cn https://www.controleng. com/international-editions More from Control Engineering on AI is available. https://www.controleng. com/AI-machine-learning
ANSWERS
Greg White, Imubit
Expectations, reality and AI in industrial process modeling
How AI is challenging traditional assumptions in process control and unlocking new value from plant data.
IOnline controleng.com
LEARNING OBJECTIVES
Understand the limitations of traditional process modeling and advanced process control (APC) — particularly the reliance on linear assumptions, simplified gain matrices and narrow data windows.
Learn how AI-based optimization (AIO) uses deep learning and historical plant data to model complex, nonlinear interactions and uncover previously hidden optimization opportunities.
Recognize the importance of operator trust and explainability tools in the successful implementation of AI-driven models within industrial control environments.
CONSIDER THIS
How much untapped value might exist in your plant’s historical data, and are traditional modeling methods leaving optimization opportunities on the table that AI-based approaches could uncover.
ndustrial process modeling lies at the heart of modern optimization in the complex process industries. It seeks to describe how a large number of process variables interact — often in nonlinear, dynamic and site-specific ways — to enable operators to move toward optimal operating states. From a mathematical perspective, this entails solving a multivariable optimization problem in a multi-dimensional solution space.
To make this tractable, traditional approaches simplify the system by evaluating two-variable relationships — defining “gains” between independent and dependent variables. For example, increasing the overhead temperature on a distillation column typically results in more heavy components in the overhead product, a positive gain. These expected relationships, grounded in first principles and taught using theory-based tools like McCabeThiele diagrams, serve as the building blocks of traditional model-based control systems.
In practice, these gain relationships are codified into gain matrices. They allow control engineers to predict how outputs will respond to input changes. If observed plant behavior deviates from textbook expectations — due to noise, dynamic delays or unexpected process interactions — the model is typically adjusted or simplified to maintain internal consistency. In this framework, step tests are used to generate a single gain value over a steady-state interval, often limited to a few weeks of data collection. As a result, the models are inherently linear, time-limited and coarse approximations of reality.
APC vs. AIO: A paradigm shift in modeling
Advanced process control (APC) tools have served the industry well for decades, but they face critical limitations, such as:
• Linearity assumption: APC relies on static gain matrices derived from step tests, assuming linear relationships even in processes known to be nonlinear.
• Limited training data: Step tests are typically run over 1–2 weeks, capturing only a narrow window of plant behavior.
• Delayed first-principles application: Traditional modeling first fits observed data into expected relationships, excluding dynamics that don’t align with those expectations.
An AI-based model-building methodology flips this approach. Rather than beginning with assumptions, closed loop AI optimization (AIO) begins with plant data — months to years of minute-by-minute operating history — and applies deep learning to discover true operational relationships. These deep neural networks specialize in providing the capacity to represent relationships that linear models struggle to express. Importantly, first principles guardrails can be incorporated in AI-based model building, but as a second step where domain experts use their knowledge to interpret and validate the results. Letting the neural networks run outside of the confines of first principles at the start of the model-building process removes unnecessary assumptions and bias and allows the models to uncover unexpected, but valid relationships.
This shift in the order of operations is profound. It enables the model to uncover interactions missed by traditional modeling and adapt to nonlinearity,
multivariable coupling and previously unmeasured effects. While APC simplifies complexity to fit within linear structures, AIO embraces complexity to unlock greater insight.
Critically, AIO models need not be thought of as “black boxes.” Engineering judgment plays a central role — through client collaboration, gain matrix expectation-setting and domain expert review — ensuring that AI-based models remain grounded in physical understanding and site-specific realities.
Case Study: Hydrocracker Optimization and Unexpected Gains Challenge:
Conversion units such as FCCs, hydrocrackers and other multi-product stream reactors present challenges to traditional linear process control and optimization methods, which make them great candidates for an AI-based approach. The closed loop AI optimization (AIO) approach was put to the test to optimize a notoriously finicky hydrocracking unit. The goal was to analyze the impact of changes in weighted average bed temperature (WABT) on product yields. A challenging problem to solve under any circumstances, this particular hydrocracker presented additional hurdles due to the quality of the historical data. The major data quality issues faced were:
• Data compression: To conserve storage, the site had employed compression in its historian system, which interpolated values and omitted intermediate readings within a specified tolerance of the previous sample. This omitted and interpolated data can obscure the dynamic responses critical for accurate modeling. At today’s data storage cost,
FIGURE: Operators and engineers perform what-if simulations to build trust in AIO models. A manipulation (orange) shows that lowering WABT has a $10k/d increase on the objective function.
Courtesy: Imubit
‘An AIO model would identify and safely navigate the nonlinearity, continuously locating the global optimum — even near operational limits.’
it is a best practice to turn off compression settings to avoid running into limitations due to a previous decade’s storage strategy.
• Lack of cut point corrections: Product flows from the hydrocracker’s downstream distillation columns weren’t corrected for cut point variations, limiting the fidelity of yield predictions.
Despite these limitations, the AI model was expected to reveal a nonlinear gain between WABT and diesel yield — consistent with the well-documented over-cracking phenomenon. Initially, diesel yield increases with rising WABT due to enhanced conversion of heavy hydrocarbons. But beyond a threshold, diesel molecules themselves crack into lighter, less valuable LPG products (e.g., butane, propane, ethane). Traditional APC models avoid operating near this inflection point due to linear assumptions breaking down, which could push the unit into an unfavorable economic regime.
An AIO model, by contrast, would identify and safely navigate this nonlinearity, continuously locating the global optimum — even near operational limits.
For this client’s case, however, the AIO model output defied expectations. All product gains with
ANSWERS
‘AI modeling will become the standard for solving previously intractable optimization challenges creating smarter, faster and more profitable decisions and actions in the plant.’
respect to WABT appeared positive, with no visible inflection. Further investigation revealed that this was not a modeling flaw, but a reflection of data limitations — particularly the lack of cut point correction and insufficient temporal resolution due to compression.
Solution: Creativity in the face of constraint
While the model wasn’t suitable for closedloop control in the initial, data-limited form, it still demonstrated value. Visualization of the gain distributions identified optimization opportunities missed by conventional control. To make this actionable, profitability-based variables tied to historical pricing regimes were introduced to the model.
Consider two pricing scenarios:
• When diesel commanded a premium over jet fuel
• When the reverse held true
By segmenting historical data by price regime, the model revealed distinct optimum strategies. For example, under a diesel-favored regime, the predictor model showed that existing operations inadvertently increased jet production at diesel’s expense — an opportunity loss caused by static operating targets.
In facilities where pricing, demand or constraints change frequently, real-time optimization can be a game changer. A closed loop AI optimization (AIO) solution issuing new set points every 5–10 minutes — rather than relying on static weekly plans — can adapt instantly to market shifts,
unplanned outages or competitor behavior. This agility translates directly into multi-million-dollar annual profitability improvements.
AIO solution success dependent upon trust
As the primary interface with process control systems, plant operators are a key ingredient in the success of any closed-loop optimization solution. Building their trust is paramount to them keeping the solution engaged rather than turning it off and resorting to the status quo. Since AI-based solutions are more complex mathematically to explain than first principles or laws of physics, it’s important to include explainability tools, such as what-if simulation capability, so that operators can play around with the models, simulating different scenarios and testing them against their experiences. In the figure, a manipulation to lower reactor WABT shows that reducing the reactor WABT had a positive impact on the unit objective function resulting in a margin gain of ~$10k/ day. By simulating manipulated and disturbance variable moves, shifting constraints and switching up price sets, operators on this hydrocracker built up trust in the AIO models.
Embracing data without abandoning fundamentals
AIO models like the one described in the case study above don’t replace engineering insight — but, rather, they amplify it. Comparing expected gain matrices with those learned from plant data provokes experts to challenge assumptions, quantify deviations and uncover untapped opportunities. This tension between expectation and reality is not a weakness — it’s a strength, and it’s where innovation lives.
As the industry continues to digitalize, the fusion of first-principles thinking with data-first AI modeling will become the standard for solving previously intractable optimization challenges. The result? Heavy process industries like refining and petrochemicals can expect smarter, faster and more profitable decision-making and action across the plant. ce
Greg White is a business consulting engineer at Imubit. Edited by Gary Cohen, senior editor, Control Engineering, WTWH Media.
DataHub software puts OT data on a DMZ using only outbound connections which keeps all inbound firewalls ports closed and requires no VPNs. On the DMZ, connected DataHub software provides secure, bidirectional data flow to and from any cloud service to support real-time Industrial AI.
ANSWERS
Roman Skorupa, Yaskawa
Advantages of multi-axis servo drives
Selecting among technology options in a motion-control application often comes with levels of complexity, especially when dealing with multiple axes. Explore five automation advantages of multi-axis servo drives.
Multi-axis servo drives started gaining popularity in the early 1990s, and since then, more technological advancements have made these devices more powerful. There is an immense upside in the differences in having multiple axes in one simple-to-use package rather than multiple single packaged drives. Selecting among options in a motion-control or machine design application often comes with levels of complexity, especially when dealing with multiple axes. Multi-axis servo drives can help limit that complexity and increase performance in space, synchronization, energy, scalability and data handling aspects.
Space efficiency
TABLE SHOWS SPACE SAVINGS: Graphic compares space differences among using single-axis servo drive, dual-axis servo drive and three-axis servo drive for as many as 18 axes. For instance, Yaskawa’s Sigma-XT Three-Axis drive is 70 mm in width. The smaller models of Yaskawa’s Sigma-XS Single Axis drives are 40 mm wide with 1mm of required spacing. All figures courtesy: Yaskawa
Space efficiency
1. Space is a vital characteristic to consider in designing panels for servo applications. For a multi-axis system, the panel must contain fans and have strict spacing conditions based on safety standards. With increasingly complex systems with multiple connections and routing points, even saving the smallest amount of space can be crucial. For example, one three-axis drive is 70mm in width. To compare, the smaller models of a single-axis drive are 40mm wide with 1mm of required spacing. By driving three axes with the identical power-rated drives, a motion-control application or machine designer can save 52mm or 57% of total width by using multi-axis drives. This idea will save exponentially more space for applications with more axes. The table shows how.
Cost savings (wiring)
2. Consolidating multiple axes into one servo drive helps with panel spacing. Building a panel can become tedious work when following all standards, so space becomes a key issue when designing. Power wiring becomes simpler because multi-axis servo drives often share a common DC bus. Input power circuit protection becomes simpler because of that common bus.
A panel designer does not need to provide circuit protection for multiple power lines to single-axis servo drives. Controller-to-drive communications connections are simpler since multi-axis drives share one communication line, as opposed to the usual daisy-chained lines in multiple single-axis systems. Although minor, in multi-axis servo drives, the motor power and encoder connections are condensed closer together, so the cables from each motor can be routed closer together and more organized.
The total space improvements save costs due to fewer cables and the overall cost of the servo drives.
Communication and data handling
3. Programming multi-axis drives has advantages. Communication connections are greatly simplified when using a multi-axis drive. This goes hand in hand with how the drives are programmed. There is only one device, but each axis can be controlled and interfaced with much more simplicity. Firmware updates to drives can often sideline an application, especially in the design and testing phase. Depending on where the servo drives are located, it can be tough to get cables to reach the correct connectors. With a multi-axis servo drive, you can significantly reduce the amount of device maintenance required.
Energy efficiency
4. Energy efficiency can be improved in applications that use multiple axes. It is important to note that multi-axis drives share a common DC bus, which is crucial for energy dissipation. Take an application that runs two motors simultaneously with opposite motion profiles, where one motor accelerates while the other is decelerating. With a multi-axis drive, energy from the motor that decelerates can be used for the accelerating motor due to the common DC bus. There is no common DC bus with two single-axis servo drives unless extra modifications are made to the drives. So, all the energy that comes from a decelerating motor is just wasted. If an application constantly has situations like this, using a multi-axis drive can drastically save energy, which saves money. Figure 3 shows a basic flow of energy when this happens. In addition, multi-axis servo drives are more efficient, avoiding some power loss. Although small, the differences in power loss can save substantial amounts of energy and money in the long run.
Scalability and modularity
5. Scaling axes on an application is possible when using multi-axis drives. You can drive X, Y and Z axes with one device. More options are available when using something like technologies that enable connection of multiple motors to a chained encoder line. Changing node addresses allows each motor in that line to be individually controlled. A application designer can place up to three motors in a line in specific places to achieve an application. With many available setups and configurations available, the possibilities of applications on one device are numerous. Applications that could benefit from using multi-axis servo drives include computer numeri-
cal control (CNC) machines, simple robotics, packaging machines, printing presses, gantry systems and textile machines. Any application that requires moving through three-dimensional space, requires synchronized joint motion, or precise timing and control between multiple points will require the use of multiple axes. As discussed, many advantages exist in selecting multi-axis drives over single-axis drives. ce
Roman Skorupa, product engineer, Yaskawa. www.yaskawa.com Edited by Mark T. Hoske, editor-in-chief, Control Engineering, WTWH Media, mhoske@wtwhmedia.com.
FIGURE 1: Wiring time and complexity is less when using multi-axis servo drive compared to single axis servo drives.
FIGURE 2: Communications and data handling are simplified when using a multi-axis servo drive compared to linking multiple single-axis servo drives. Courtesy: Yaskawa
FIGURE 3: In some applications, motor deceleration can help power another motor, saving energy compared to “burning” energy in heat with a brake.
FIGURE 4: Yaskawa’s Sigma Link II allows connecting multiple motors to a chained encoder line adding flexibility with less complexity.
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KEYWORDS: Multi-axis servo drives, comparisons with single-axis servo drives CONSIDER THIS How are you simplifying your multi-axis motion control application designs? ONLINE
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ANSWERS
Rick Kephart, Emerson
How distributed energy resources empower smart grids
Distributed energy resources are reshaping the sustainability landscape. Grid operators must adopt intentional, hierarchical architectures to reduce complexity, ensure reliability and unlock the full promise of clean power.
Modern society has an almost insatiable appetite for electricity. Electric cars, data centers and more increasing amounts of electricity from the grid. As the demand on the grid increases, people, companies and even governments call for an increase in sustainable production of that electricity, putting even more pressure on power generators to not only increase output but to do so in new ways.
player, but if teams aren’t careful, the addition of modern, distribution-side DERMS can quickly create unwieldy architectures, reliability issues and cybersecurity concerns.
However, there is an emerging solution — a hierarchical architecture based on grid edge controllers acting as DER gateways. Such a system provides local aggregation points and control at the edge for high-speed DER applications, and it seamlessly integrates into grid management and DERMS solutions for continuous centralized control and visibility.
Investigating a new DER architecture
The grid edge controller/ADMS architecture is hierarchical. The highest level of the architecture is the ADMS. This uppermost level provides distributed energy management functions from the central control location. Grid operators will still use the ADMS to orchestrate and conduct operations across the grid.
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KEYWORDS: Online Text online text
LEARNING OBJECTIVES
Understand the role of distributed energy resources (DERs) in new clean energy initiatives.
Learn about a new hierarchical architecture based on grid edge controllers that act as DER gateways.
Controlling the modern grid system invited cybersecurity concerns.
Online Text online text
ONLINE
Online Text online text
CONSIDER THIS
Online Text online text?
A key element of the response to this global shift has been an evolution of the power grid. The traditional model of siloed generation and distribution, with each team staying in its own lane, has begun to shift. Distributed energy resources (DERs) have been a core element of this shift, with renewable energy generation assets beginning to appear on the distribution side of the power architecture. Rooftop solar installations, community battery and even small, private wind generation sites and more make up these DERs, which have become an important part of the overall energy generation mix.
Bringing DERs into the energy mix is not something that can be done thoughtlessly. Increased options and flexibility also mean increased complexity, so new architectures must be implemented with an intentional strategy. The traditional grid control center with a distributed energy management systems (DERMS) capable advanced distribution management system (ADMS) is still a key
However, instead of connecting all the highspeed, lower-layer assets directly into the centralized control, the ADMS is instead connected to grid edge controllers that act as DER gateways. Each gateway can communicate with multiple DERs in the field and then aggregate and add context to collected data for presentation of information back to the ADMS for visibility and management functions. Everything is connected to the ADMS via a standard, secure protocol, ultimately abstracting away the diversity, capabilities and vintage of the DERs so grid operators focus on orchestration rather than configuration (see Figure 1).
Creating a new DER architecture while combating complexity
The greatest challenge with DERs is that they are often not traditional, transmission-connected entities. Often, DERs — particularly renewable energy assets like solar — are smaller generators connected
FIGURE: Each distributed energy resource (DER) gateway can talk to multiple DERs in the field for improved visibility via a simplified interface. Courtesy: Emerson
on the distribution side. In fact, many renewable energy DERs are not managed by the utilities but rather controlled behind the meter by an end user or an aggregator, making control and coordination complex.
Utilities need visibility into these remote assets, and they need to be able to see their effects and manage their generation throughput. They typically do so by using a digital grid management DERMS application. However, DERs come in a wide array of sizes, formats, manufacturers and vintages, making it difficult to directly connect them to DERMS in the ADMS. As the grid continues to grow, it quickly becomes difficult or impossible to manage all those connections and devices separately. Teams need a control hierarchy that allows them to group the higher-speed, lower-level assets together for easier management.
Grid edge controllers operating as DER gateways aggregate all DER communications — regardless of technology or vintage — together to provide a consistent interface back to the digital grid management solution for easier communications, man-
‘Teams need a control hierarchy that allows them to group
assets
the higher-speed, lower-level
together for easier management.
agement, visibility and control of assets. Moreover, teams can allow grid edge controllers to perform control functions locally and aggregate the reporting back to the grid control center’s ADMS to cut down on bandwidth requirements.
Ultimately, the DER gateway architecture provides effective plug-and-play capability between the individual DERs and the ADMS, cutting complexity and letting operators focus on operations, instead of complex engineering and maintaining connectivity.
Enhancing resiliency and reliability with grid controllers
One of the other benefits of a modern grid architecture built on grid edge controllers functioning as
’
ANSWERS
‘A hierarchical architecture built from an ADMS connected to grid edge controllers serving as DER gateways will dramatically reduce the complexity that stalls expansion, complicates operations and introduces cybersecurity risks.’
DER gateways is increased resilience and reliability. With a traditional architecture, when there are outages, teams must attempt to fix issues from within the central system. If everything is tied into the central system via a complex web of custom connections between DERMS and a variety of different DERs, when a failure occurs, the team must first identify the source of the failure within the system and then diagnose it, slowing repair and increasing the risk of creating additional problems.
In contrast, in a hierarchical system using DER gateways, system reliability is improved. When the assets on the lowest layers fail, the ADMS can work around that single connection to the failing DER gateway until it is resolved, reducing points of failure and increasing uptime, along with the ability to deliver adequate power.
Resiliency is further increased by the fact that the grid edge controllers can run semi-autonomously. If a weather event or other issue severs communications to a DER gateway, the grid edge controllers can keep those assets running safely until communication can be restored. Ultimately, these new architectures add more redundancy into the system, while simultaneously simplifying connectivity and visibility and standardizing for increased scalability.
Ensuring cybersecure connectivity
One of the key concerns with controlling the modern grid is cybersecurity risk. The ADMS is likely very cybersecure, but DERs often have limited or no cybersecurity provisions. If those insecure assets are connected directly to DERMS in the ADMS, communication between the asset and the central control is subject to cyberattack. All a bad
actor needs to do is get between the DER and the ADMS to cause problems.
Fortunately, it is possible to embed cybersecurity agents in DER gateways, as they tend to have more modern processing technology than legacy DER systems. Embedding cybersecurity functions, such as deep packet inspection, inside the gateways helps ensure all communication across the grid is secure. Moreover, incorporating cybersecurity into the DER gateway means that updates only need to be performed on the gateway side, making it possible to continually apply updates and patches to support increased security for the wide variety of assets at lower layers, without risk that a change will interfere with the ADMS.
A more distributed energy future
As communities around the globe continue to add renewable energy DERs — in parallel with associated increases in production on the distribution side of the grid — power companies will need more flexible, scalable architectures to support that evolution. A hierarchical architecture built from an ADMS connected to grid edge controllers serving as DER gateways will dramatically reduce the complexity that stalls expansion, complicates operations and introduces cybersecurity risks.
Though the grid will continue to evolve, and nobody can predict what the smart grids of five to 10 years from now will look like, the technologies exist to prepare for the scale ups and scale outs that will be necessary to support that shift. It is not too early to start preparing for the future of energy production and distribution and a trusted partner can help. ce
Rick Kephart is vice president of technology for Emerson’s power and water solutions business. Edited by Sheri Kasprzak, managing editor of Automation & Controls, WTWH Media, skasprzak@ wtwhmedia.com
Insightsu
CLEAN ENERGY INSIGHTS
uDistributed energy resources are a core element of a shift toward smart grids and clean energy.
uNew architecture must be implemented to enable DERs on the distribution side of renewable energy.
u A new hierarchical architecture based on grid controllers could be a solution.
Antonious Messiha, CMSE, Grantek
Machine safeguarding and why you need to prioritize it now
Machine safeguarding doesn’t just keep facilities compliant. Unguarded machinery represents one of the most obvious and preventable hazards in manufacturing environments.
Machine safeguarding is more than just another compliance checkbox. For manufacturing environmental, health and safety (EHS) managers, machine safeguarding represents far more than just another compliance checkbox. It's a strategic approach that directly impacts worker safety, regulatory compliance and operational excellence. Understanding how proper safeguarding aligns with broader EHS goals can transform your facility's safety culture while meeting critical Occupational Safety and Health Administration (OSHA) requirements.
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KEYWORDS: OMachine safety, safety integration
CONSIDER THIS
Are you using machine safety data to improve safety?
LEARNING OBJECTIVES
Achieve Occupational Safety and Health Administration (OSHA) compliance through effective safeguarding.
Explore strategic environmental, health and safety (EHS) Integration with machine safeguarding.
OSHA has clear expectations when it comes to machine safeguarding, primarily outlined in 29 CFR 1910.212 and related standards. These regulations require that machines with moving parts that could cause injury to be properly guarded at the point of operation, power transmission apparatus and other hazard points.
From a compliance perspective, machine safeguarding helps facilities meet several key OSHA requirements. First, it addresses the general duty to provide a workplace free from recognized hazards.
Unguarded machinery represents one of the most obvious and preventable hazards in manufacturing environments.
Second, specific machine guarding standards require protective devices that prevent operators from encountering dangerous machine parts
during normal operation, maintenance or setup procedures.
Effective safeguarding systems also support OSHA's lockout/tagout (LOTO) requirements under 29 CFR 1910.147. When machines are properly designed with appropriate access points and safety interlocks, maintenance workers can more easily and safely perform required energy isolation procedures. This integration reduces the risk of both routine operational injuries and maintenance-related accidents.
Strategic EHS integration for machines
While meeting regulatory requirements is essential, forward-thinking EHS managers recognize that machine safeguarding serves broader organizational goals. When integrated thoughtfully into EHS programs, safeguarding initiatives can drive improvements across multiple performance areas. Risk reduction and incident prevention: Comprehensive safeguarding programs help identify and mitigate hazards before they result in injuries. This proactive approach aligns with modern EHS management principles that emphasize prevention over reaction. By conducting thorough machine risk assessments, facilities often discover hazards that extend beyond immediate point-of-operation dangers, leading to more comprehensive safety improvements.
Data-driven safety culture: Modern safeguarding systems often include monitoring capabilities that generate valuable safety data. Light curtains, pressure mats and safety PLCs can track near-miss events, providing EHS managers with insights into behavioral patterns and potential problem areas. This data supports evidence-based safety decisions and helps demonstrate the business value of safety investments.
Operational efficiency: Contrary to the misconception that safety measures slow produc-
tion, well-designed safeguarding systems can improve efficiency. Safety interlocks that allow quick changeovers, ergonomically designed guard openings and automated safety systems can reduce downtime while protecting workers. This alignment of safety and productivity goals makes it easier to secure management support for EHS initiatives.
Practical implementation strategies
To maximize the EHS value of machine safeguarding investments, consider these strategic approaches:
• Integrate safeguarding assessments into broader facility risk evaluations. Rather than treating machine guarding as an isolated concern, incorporate it into comprehensive risk management processes that address environmental, health and safety factors holistically.
• Leverage safeguarding projects to advance other EHS goals. When upgrading guarding systems, consider opportunities to improve ergonomics, reduce noise exposure or minimize environmental impacts through better containment of processes.
• Use safeguarding compliance as a foundation for broader safety management system improvements. The systematic approach required for effective machine guarding—hazard identification, risk assessment, control implementation and ongoing monitoring— mirrors best practices for comprehensive EHS management.
• Engage operations teams as partners in EHS success. Machine safeguarding projects provide excellent opportunities to demonstrate how safety, productivity and quality can work together, building support for broader EHS initiatives.
Beyond machine guarding compliance
For EHS managers, machine safeguarding represents a critical intersection of regulatory compliance and strategic safety management. By approaching safeguarding as an integrated component of comprehensive EHS programs rather than
Integrating machine safeguarding into environmental, health and safety (EHS) can: Add operational efficiency
Improve risk reduction and incident prevention
Augment data-driven saftey culture
environmental, safety and health standards. Courtesy: Grantek
an isolated requirement, facilities can achieve better safety outcomes while building a foundation for continued improvement.
The key is recognizing that effective machine safeguarding does more than protect workers from immediate physical hazards — it demonstrates organizational commitment to safety, provides valuable risk management data and creates opportunities to advance broader EHS objectives. In today's manufacturing environment, that comprehensive approach isn't just good practice — it's essential for long-term success.
Remember that effective machine safeguarding is an ongoing process, not a one-time project. Regular reviews, worker feedback and continuous improvement ensure that your safeguarding programs evolve with changing operations and emerging best practices. ce
Antonious Messiha, CMSE, is a sales, safety and logistics expert at Grantek, Burlington, Ontario, Canada. Edited by Sheri Kasprzak, managing editor of Automation & Controls, WTWH Media, skasprzak@wtwhmedia.com.
‘Light curtains, pressure mats and safety PLCs can track near-miss events, providing EHS managers with insights into behavioral patterns and potential problem areas.’
FIGURE 1: Some examples of how integrating machine safeguarding into
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Powering Progress: Meet the 2025 Engineering Leaders Under 40
Celebrating 35 engineering professionals who are driving transformation, mentorship, and excellence across the industrial landscape.
Amanda Pelliccione, Marketing Research Manager, WTWH Media
The future of engineering is in capable hands. The 2025 class of Engineering Leaders Under 40 showcases 35 early- to mid-career professionals whose work is accelerating progress in automation, controls, energy, infrastructure and beyond. These individuals are not only delivering technical breakthroughs—they’re also redefining what leadership looks like in modern engineering environments.
This year’s honorees represent a rich diversity of disciplines and backgrounds, but they share a common vision of using their expertise to solve real-world problems, supporting their communities and elevating their teams. From building gigafactories and digitizing frontline workflows to commissioning renewable facilities and mentoring young engineers, their stories highlight the ingenuity and resilience shaping today’s industrial workforce.
In addition to technical excellence, these leaders are passionate about mentorship, lifelong learning and making engineering more inclusive and future-focused. Many balance high-stakes responsibilities with impactful volunteerism, family life and personal passions that ground and energize their work.
We’re proud to honor these standout professionals who embody the values of innovation, service and human-centered leadership. As you read their stories, we hope you’re as inspired as we are by the energy, optimism and purpose they bring to engineering—and to the world.
Learn more about this program and how to nominate a colleague for 2026 at www.plantengineering.com/events-andawards/engineering-leaders-under-40 or www.controleng. com/leaders-under-40. Nominations open April 1, 2026. ce
Hannah Bonaguidi, 27
Project Manager
Catalyx
Warminster Heights, PA
—Hannah is a rising leader in process automation and analytical technology. She has led more than 40 projects, demonstrating technical skill, adaptability and clear communication. Whether collaborating with experienced engineers or guiding teams unfamiliar with automation, Hannah ensures effective outcomes. Her expertise spans PAT systems, virtualized controls and GMP compliance, making her a trusted, forward-thinking project leader.
Johnnie Burness, 39
Engineering Manager – Factory Systems and Test
Verdagy
Newark, CA
—Johnnie leads high-impact projects at the forefront of modern manufacturing. From gigawatt-scale electrolyzer production at Verdagy to launching Tesla’s Model 3 Drive Unit line, he blends control systems expertise with big-picture strategy. As a licensed PE with an MBA, Johnnie delivers innovative, scalable solutions in complex industrial settings.
Fun Fact: Hannah has tattoos of “L” and “R” on her hands to help with navigation—and a husky named Tankus Pankus afraid of toasters.
Fun Fact: Johnnie didn’t fly until age 22—but now his engineering work takes him around the globe.
Jason Cary, 29
Senior Manufacturing Engineer
ContiTech USA LLC
Wahpeton, ND
—Jason is known for his hands-on engineering and deep process insight. A sub-lead at ContiTech, he’s driven improvements in safety, throughput and quality. Self-taught in rubber extrusion and a subject matter expert in polymer processing, Jason leads initiatives that boost performance while sharing knowledge across facilities.
Fun Fact: Jason restores classic cars with his dad and fosters rescue dogs with his wife.
Brady Darrough, 28
Automation Engineer
Huffman Engineering
Lincoln, NE
—Brady is quickly becoming a go-to expert in SCADA systems and legacy PLC conversions. His work spans utility and industrial projects, from flood recovery efforts to advanced system upgrades. With certifications in Ignition and Rockwell Automation platforms, Brady brings humility, technical rigor and genuine care to every engagement.
Fun Fact: Brady is a cross-country coach, marathon runner, and former agricultural drone pilot for Bayer Crop Science.
Hugo Dozois-Caouette, 33
CTO and Co-founder
MaintainX
San Francisco, CA
—Hugo is transforming industrial maintenance through AI and mobile-first tools. As CTO and co-founder of MaintainX, he built a platform used by more than 11,000 global facilities, improving data visibility and uptime. His passion for intuitive design and team mentorship fuels innovation that supports frontline workers in essential industries.
Danny Dylong, 37
Director, Manufacturing
The RoviSys Company
Aurora, OH
—Danny brings energy, strategic insight and technical depth to automation projects worldwide. From co-op student to director at RoviSys, he’s led teams across 12 countries and multiple sectors. Now driving growth in markets like aerospace, EVs, and defense, Danny is building a dynamic and people-focused engineering culture.
Fun Fact: Hugo is a rock climber, tennis player and long-time contributor to the open-source React-Bootstrap community.
Fun Fact: Danny is a serial hobbyist—he scuba dives, fishes, golfs, and also advocates for causes like leukemia and Parkinson’s research.
Chris Edwards, 37
CEO Sensory Robotics
Cincinnati, OH
Chris pioneered 3D point cloud safety technology—replacing traditional safety devices with reconfigurable, vision-based systems for robotics. As CEO of Sensory Robotics, he self-funded and led the team to a working MVP and multiple pilot installations. His patented work bridges VR, AI and industrial safety with human-centered design.
Fun Fact: Chris performs improv comedy in Cincinnati and preserves Civil War–era family properties through his Heritage Stewardship Committee.
Christen Egan, 33
Engineering Manager General Control Systems
Albany, NY
Christen brings strong leadership and technical excellence to semiconductor and industrial control projects. A licensed PE in four states, she manages projects and engineering policies at GCS’s headquarters. Known for mentoring and innovation, Christen is also active in industry groups and professional certification programs.
Fun Fact: Christen is a Swiftie who attended four Eras Tour concerts in two countries and three cities.
Christopher Evans, 30
Project Engineer
The RoviSys Company
Houston, TX
Christopher is a versatile engineer who has shaped the growth of RoviSys's Texas office. A leader in power and energy projects, he brings curiosity, adaptability and deep technical know-how across multiple platforms. His self-driven learning—from home labs to AI systems—fuels innovation company-wide.
Fun Fact: Christopher sings in a local choir, hand-forged his wife’s engagement ring, and recently took second place in a strongman competition.
Michael Fazzini, 34
Director of Operations
Actemium Avanceon
Exton, PA
Michael blends technical engineering with strategic business leadership. Rising through the ranks at Avanceon, he now oversees operational performance, team development and revenue growth. Known for mentoring and creative problem-solving, Michael is a people-first leader driving transformation in the systems integration space.
Fun Fact: Michael and his wife married in Sorrento, Italy, and he’s a devoted dog dad to four pups and a passionate Philly sports fan.
Victor Foster, 40
Reliability Engineering Manager
International Flavors & Fragrances
Memphis, TN
Victor is a seasoned reliability leader who elevates maintenance strategy through measurable outcomes. He’s led CMMS installations, predictive maintenance integrations and multi-year performance gains, including a 50% drop in reactive work. A board member of the Reliability and Maintainability Center, Victor mentors co-op students and champions reliability as a mission-critical discipline.
Fun Fact: Victor is an Eagle Scout and Cubmaster who guides over 50 youth through character-building and leadership in Scouting.
Daniel Foster-Roman, 35
Industry Principal, Power & Utilities
Seeq
Seattle, WA
Daniel blends power-sector engineering with data science to transform industrial analytics. At Seeq, he leads AI-driven strategy for utilities and mentors teams across disciplines. Formerly with Ontario Power Generation, he earned awards for digital innovation in nuclear and hydro. A contributor to global AI guidelines via the IAEA, Daniel is shaping the future of smart energy.
Fun Fact: Daniel is a drummer who toured with a Canadian indierock band and now jams at home with his toddler daughter.
Mena Francis, 37
Project Manager
Applied Control Engineering
Newark, DE
—Mena is a standout in pharma and life sciences controls engineering, with expertise in medical device manufacturing, GAMP and ISO/FDA standards. A Six Sigma Black Belt and PMP, he drives measurable improvements in process performance while mentoring future engineers and championing continuous learning.
Fun Fact: Mena has traveled to over 30 countries, once competed in Greco-Roman wrestling and is passionate about chess and kayaking.
Prashant
Ghadge, 39
Project Engineer
Compass Energy Systems
Houston, TX
Prashant blends mechanical and controls engineering to design high-performance compressor packages tailored to site and process needs. With experience across diverse compression technologies, he’s led innovations in hydrogen refueling and high-pressure gas systems. A published thought leader and industry advisor, Prashant is recognized for technical depth, safety advocacy and AI-forward thinking in energy systems.
Fun Fact: Prashant volunteers as an event photographer for local nonprofits and expresses his creativity through music, sculpture and stage design.
Michael Jagels, 37
Automation Engineer
CDM Smith
Columbus, OH
Michael leads SCADA system design, startup and commissioning for water infrastructure projects across Ohio. As a licensed PE and technical leader, he balances engineering rigor with 24/7 responsiveness, ensuring safe, reliable operations for public utilities. Passionate about training the next generation, he also mentors new engineers in fieldwork execution and client-centered design.
Fun Fact: Michael transformed his backyard into a native plant sanctuary to help manage stormwater runoff—both at home and in the field.
Luke Kellogg, 38
Senior Controls Engineer
Lectro Engineering
St. Louis, MO
Sharath Kumar Kanniyappan, 34
Sr. Controls Engineering Supervisor
Honeywell Intelligrated
Mason, OH
Sharath leads global warehouse automation projects with technical precision and strategic foresight. Rising from engineer to supervisor, he’s driven Honeywell’s digital transformation through emulation tools and Industry 4.0 adoption. His work bridges customer support, systems analytics and commissioning excellence, delivering value from design to deployment.
Fun Fact: Sharath plays the whistle flute—a talent he’s kept up since his school marching band days—and devours thriller novels on the go.
Luke is the backbone of controls design at Lectro Engineering, managing PLC/HMI programming, schematics and customer support. Rising from assembly tech to senior engineer, he’s led product innovations like vision and leak test machines that opened new markets. Self-taught and service-driven, Luke trains peers and builds machines from first concept to startup.
Fun Fact: Despite no formal training, Luke became his company’s top controls engineer—and now mentors youth through his church and community programs.
David Ladner, 32
Controls & Automation Process
Safety Engineer
Hargrove Controls & Automation
Mobile, AL
David tackles complex automation and process safety projects with calm confidence and technical mastery. From PLC programming to HAZOP studies, he supports clients across industries while mentoring interns and leading community STEM outreach. His custom LED driver design and startup leadership at Hargrove reflect both innovation and impact.
Fun Fact: David travels the globe to explore new cultures and cuisines—and is learning Spanish to connect deeper at work and abroad.
Jonathan Larnard, 31
Senior Automation Engineer
NeoMatrix
Portsmouth, NH
Jonathan is a trusted automation expert who leads high-compliance integration projects in pharma and GMP manufacturing. With nearly a decade at NeoMatrix, he’s known for platform versatility, attention to detail and end-to-end project execution. He’s also a dedicated mentor who models professionalism and continuous learning in every engagement.
Kyle Lick, 35 Automation
Engineer
CDM Smith
Boston, MA
Kyle combines rare dual mastery in automation design and programming with an unwavering commitment to client support. A licensed PE and contributing author to NEIWPCC’s TR-16, he leads major SCADA upgrades while ensuring continuous operations. Calm under pressure, Kyle builds lasting trust across the water and wastewater industry.
Fun Fact: Jonathan is a lifelong soccer fan and avid traveler, and he balances work with tennis, snowboarding and gaming.
Fun Fact: Kyle once traveled to Kyle, Texas, to help break the Guinness World Record for the largest same-name gathering.
Patrick McKinley, 38
Project Engineer
Applied Control Engineering
Newark, DE
Patrick’s expertise in PLC platforms, team leadership and process startups drives success across control upgrades and greenfield builds. From steel plants to pyrolysis projects, he leads with curiosity, clear communication and hands-on skill. His mentorship and technical leadership are making lasting impacts in the automation community.
Fun Fact: Patrick owns a Pittsburgh brewery and applies his engineering know-how to beer-making and business operations.
Shankar Narayanan, 38
Technology Partnerships Manager
Amazon Web Services | Energy & Utilities
San Jose, CA
Shankar leads industrial innovation at AWS, scaling GenAI and cloud tools to modernize aging infrastructure across more than 30 sites. With a background at GE and Baker Hughes, he’s improved safety, uptime and emissions in energy systems. A mentor, author and startup advisor, he advances sustainable engineering at scale.
Muktar Ali Mohammad, 28
Industrial Controls Specialist
SymBioAITech
Farmers Branch, TX
Muktar designs advanced controls for Fortune 500 clients, driving efficiency and safety with PLCs, motion systems and industrial IoT. He mentors engineers, publishes research, and implements predictive analytics in high-speed logistics and food plants. A multilingual innovator, he brings smart automation to life.
Fun Fact: Muktar built a real-time home energy monitoring system—and a smart irrigation setup—just for fun.
Jasmine Nguyen, 27
Controls & Automation Engineer
Hargrove Controls & Automation
Birmingham, AL
Jasmine is a driven automation engineer with a background in chemical engineering and a talent for mastering diverse PLC and DCS platforms. She’s known for her leadership on migrations, onsite client support and mentoring in Hargrove’s co-op program. Jasmine is a versatile problem-solver whose technical excellence and collaborative spirit uplift both projects and peers.
Fun Fact: Shankar volunteers with energy-tech accelerators to guide startups in decarbonization and industrial AI deployment.
Fun Fact: A vintage enthusiast and recipe experimenter, Jasmine honors her Vietnamese roots through food and language.
John Pietras, 34
Project Manager 2
Matrix Technologies
Maumee, OH
John merges technical depth with project leadership, managing multimillion-dollar automation and digital transformation projects across manufacturing and chemicals. From OT networks to Industry 4.0 systems, he delivers results while mentoring younger engineers. A respected leader and strategic thinker, John’s efforts boost efficiency, safety and innovation.
Adi Prasad, 35 Co-Founder, Co-CEO NexiForge
Cambridge, MA
Adi led automation at Tesla, Apple and Rivian before co-founding NexiForge, where he’s compressing new-product introduction from 18 months to 18 days. He’s a pioneer in gigafactory design, AI-driven manufacturing, and yield optimization—delivering innovations that reshape global production. A hands-on leader, Adi mentors engineers worldwide.
Fun Fact: John is an Eagle Scout, avid runner and continues to mentor youth through leadership programs and community service.
Fun Fact: A certified Formula-style driver, Adi races electric cars on weekends and guest lectures at MIT on gigafactory automation.
Aravind Renganathan, 35
Services Growth Leader
Honeywell International Richardson, TX
Aravind leads Honeywell’s services strategy, driving digital transformation and new revenue models across industrial sectors. A seasoned product and service innovator, he’s expanded portfolios and global footprints at companies like Flowserve and Amazon. He blends technical expertise with market insight to deliver scalable, customer-first solutions.
Fun Fact: Aravind is a trained Indian classical vocalist and a dual master’s degree holder who mentors early-career professionals.
David Smit, 37
OT Architect
Interstates
Sioux Center, IA
David is a driving force behind digital transformation in industrial environments. As OT Architect at Interstates, he bridges SCADA, MES and network infrastructure to deliver future-ready solutions. A trusted advisor and sought-after industry speaker, David leads strategic workshops, mentors peers and shapes innovation across client and partner landscapes.
Fun Fact: An avid cyclist and home automation enthusiast, David runs tech-tuning workshops and AV teams in his community.
Edgar Rivera Hernandez, 36
Regional Director
The RoviSys Company Peachtree City, GA
Edgar’s leadership has propelled him from intern to regional director. At RoviSys, he built the Georgia office from 7 to nearly 50 engineers and launched the company’s Puerto Rico expansion. His mentorship, client focus, and commitment to high-quality execution have elevated teams and delivered major automation wins.
Fun Fact: Edgar credits his family—especially his wife, Lydia—for his success, and strives daily to lead by example for his three children.
Steve Solack, 37
Controls Engineering Manager
Mission Design & Automation Holland, MI
Steve leads with vision and empathy, guiding the largest engineering department at Mission Design & Automation. With roots in custom automation, aerospace innovation and patented applications, Steve empowers his team to solve what is seemingly unsolvable. A mentor and motivator, he inspires the next generation through co-op programs and personal example.
Fun Fact: A punk rock fan and woodworker, Steve balances creative DIY projects with raising three daughters—and sharing great music.
Erik Sullivan, 35
Engineering & Maintenance Manager, Renewables
Tidewater Midstream and Infrastructure Ltd.
Prince George, BC, Canada
Erik brings hands-on expertise and decisive leadership to renewable energy operations. He has led major refinery turnarounds, improved reliability across rotating equipment, and played a key role in the launch of Canada’s first renewable diesel facility—all without lost time incidents. His engineering vision advances safety, efficiency and sustainability.
Fun Fact: Erik once tested wildfire sensors by starting a controlled forest fire in Northern Canada. He also builds car parts with 3D printing.
Greg Trujillo, 38
Engineering Manager
IDEC Corporation
Vista, CA
Greg combines deep mechanical expertise with people-first leadership. From aerospace to robotics to sustainability startups, he’s led high-impact projects and earned multiple design patents. Now at IDEC, he empowers engineering teams and mentors students, helping build the next generation of innovators.
Fun Fact: Greg is a first-gen college grad who loves deep sea fishing—early mornings on open water keep him grounded and inspired.
Laurent Trottier, 29
Senior Implementation Consultant MaintainX
Montréal, QC, Canada
Laurent has improved operations for more than 4,000 frontline workers across more than 350 global sites. A people-first digital transformation expert, he leads CMMS rollouts that slash downtime and maintenance costs. Laurent is a vibrant, cross-functional leader who shapes product strategy, mentors peers, and energizes teams with infectious positivity.
Fun Fact: Known for his intro—“You can call me Larry”—Laurent leads bike clubs, races up Mont Royal and inspires colleagues through fitness and fun.
Brice Williams, 40
Department Manager
Matrix Technologies
Cincinnati, OH
Brice blends technical excellence with team-focused leadership. From leading 24/7 system migrations in his early career to growing Matrix Technologies’ Cincinnati office, Brice has proven himself a versatile force in automation. He’s helped standardize PlantPAx systems and trains others in its use, all while fostering client relationships and team development.
Fun Fact: Brice is a Jeep offroading guide and pinball enthusiast who hunts for local machines during work travel—and always plays a few rounds.
Bill Warnke, 39 Senior Consultant Matrix Technologies Maumee,
OH
Bill’s journey at Matrix began as a co-op in 2007 and has since evolved into a standout career as a Senior Consultant and company shareholder. Known for his versatility across industries and continents, Bill has led international implementations and created lasting impact in food and beverage, glass, pharma and other areas. A natural mentor and committee leader, he’s shaped best practices while fostering the next generation of engineers.
Fun Fact: Bill is a passionate runner and golfer, concertgoer and outdoors enthusiast who enjoys recharging with his wife and two daughters.
Engineering Leaders Under 40
Know someone who qualifies as an Engineering Leader Under 40? Help give them the recognition they deserve.
The Engineering Leaders Under 40 program recognizes manufacturing professionals under the age of 40 (as of Sept. 1, 2025) who are making a significant contribution to their plant’s success, and to the control engineering and/or plant engineering professions. Our research shows that finding, training and retaining workers is the biggest issue facing manufacturing today. The goal of the Engineering Leaders Under 40 program is to call attention to these successful young engineers in manufacturing and to show how manufacturers are recruiting and developing the next generation of manufacturing professionals.
Nominate someone at: https://www.controleng.com/events-and-awards/ engineering-leaders-under-40/ See past leaders online at the page above, going back to 2010.
Innovations
Advanced industrial platform: Powerful, scalable, open
See more New Products for Engineers www.controleng.com/products
Inductive Automation Ignition 8.3 advanced industrial platform is described as powerful, scalable and open by design. This major industrial SCADA system upgrade has a new Historian Module Suite, Event Streams Module Perspective module for more dashboard customization and combined configuration and diagnostic data. Inductive Automation, https://inductiveautomation.com/ignition/whatsnew
Powerful spindle motors for machine tools, motion controls
Siemens Industry Inc. introduced the Siemens 1PH8 family of induction motor drives and servomotors in power ratings from 2.8 kW up to 1340 kW for response performance, reduced vibration and stable operation. The line integrates induction and servo technologies to improve manufacturing efficiency and precision. Siemens Industry, www.siemens.com/us/en.html
New tower lights for smarter industrial signaling
Schneider Electric has launched Schneider Electric Harmony XVB7 Modular Tower Lights. The new IoT-enabled signaling devices are designed to support operational efficiency, with the goal of improving safety and reducing downtime in industrial environments by enabling earlier detection and response to potential issues. Schneider Electric, https://www.se.com/ww/en
Process sensor for explosive areas
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Mountaingate Capital, 1225 17th St, Suite 2575, Denver, CO 80202
KNOWN BONDHOLDERS, MORTGAGEES, AND OTHER
The intrinsically safe Migatron RPS-429AA40P-IS2 ultrasonic sensor provides precise measurements in explosive atmospheres and hazardous areas without costly downtime. It suits industries such as chemical processing, oil and gas and mining that involve applications that need high accuracy and reliability in distance measurement and object detection. Migatron Corp., www.migatron.com
Smart power supplies with standard and IO-Link options
Turck PSU67 series smart switching power supplies are IP67-rated devices that deliver 24–28 V field power and are designed for industrial use. These power supplies can be mounted on machines or walls, providing installation options for use in environments with exposure to dust, moisture or vibration. Turck, www.turck.us/en
Back to Basics
CYBERSECURITY
91% of critical infrastructure firms report OT cybersecurity breaches
Widespread OT cyber risks lead to revenue loss, service disruptions and reputational damage. Secure by operations principles helps close the OT cybersecurity gap.
Anewly commissioned study of more than 250 global operational technology (OT) critical infrastructure security decision-makers, conducted by Forrester Consulting on behalf of Schneider Electric, reveals that 91% of global organizations experienced at least one OT breach or failure in the past 18 months, even with security measures in place. These incidents led to service interruptions (51%), revenue loss (49%) and reputational damage (53%).
Roughly seven in 10 global critical infrastructure security decision-makers said they were concerned about their ability to protect their organization; six in 10 questioned their capabilities to detect an OT cyberattack.
The cybersecurity gap
The study highlights a critical gap: 51% still rely on traditional information technology (IT) practices to secure OT environments, and only 40% have 24/7 monitoring in place for OT cyber threats.
Other key findings suggest that implementing secure by operations principles — the practice of embedding cybersecurity into complex, mixed-technology operational environments with an emphasis on proactive, continuous cybersecurity post-deployment — could significantly improve OT security for critical infrastructure. Here are some key findings from the study:
• 75% of respondents agree that secure by operations ¬strategies are likely instrumental in mitigating future OT cyberattacks.
• Organizations that have adopted these principles report up to 53% faster recovery time and a 51% reduction in capital expenditure (Capex).
• Nearly half of respondents indicate potential gains in company reputation (50%), operational efficiency (45%) and regulatory compliance (44%).
Lack of strategy and solutions
The study points out that many critical infrastructure operations teams lack the strategy and solution capabilities needed to protect their OT environments. Managed security service providers (MSSPs) can help organizations augment their current security practices by providing solution capabilities, staffing and expertise needed for securing and monitoring OT environments, maintaining compliance and managing response and recovery services.
“These figures show that while cybersecurity risk is well recognized, the pace of action to mitigate it must accelerate,” said Jay Abdallah, president, cybersecurity solutions, Schneider Electric. “Modern cyber incidents have impacts that surpass purely technical interruptions. They erode trust, disrupt operations and threaten financial stability.
“To close the widening OT cybersecurity gap, organizations must combine internal capabilities with external partnerships that bring specialized, operationally aware expertise. Securing the effective integration between IT and OT environments is critical — not only to strengthen an organization’s security posture, but also to drive industrial competitiveness by enabling smarter, more efficient operations.”
As the threat landscape evolves, secure by design principles must be supported by secure deployment guidelines and configurations when integrating technology into end-user environments. Ongoing maintenance and oversight throughout the technology lifecycle should follow secure by operations practices. ce
Edited by Gary Cohen, senior editor,
Control Engineering, gcohen@wtwhmedia.com, from a Schneider Electric press release.
Insightsu
Critical infrastructure insights
uNine in 10 critical infrastructure organizations hit by OT attacks in the past 18 months
uOne-third of those suffered 4-6 attacks in the last 18 months due to limited visibility and capabilities
u11% experienced between 7-10 breaches despite existing security measures
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