What are the key benefits and strategies to implementing plant automation?

Respondents

• Mithun Nagabhairava, senior manager, data science and AI, Kalypso, Austin, Tex.
• Daniel Pender, global manager, markets and strategy, Rockwell Automation, Milwaukee
• Joe Wagner, MS, field application engineer, Red Lion, Sacramento

Left to right: Mithun Nagabhairava, senior manager, data science and AI, Kalypso, Austin, Tex.
Daniel Pender, global manager, markets and strategy, Rockwell Automation, Milwaukee
Joe Wagner, MS, field application engineer, Red Lion, Sacramento. Courtesy: Kalypso, Rockwell Automation, Red Lion

Question: What are the key advantages of implementing automation in a manufacturing plant?

Joe Wagner: Remote system monitoring, easy data access, and powerful data visualization options are just a few key advantages of implementing automation in a manufacturing plant. Automated systems often make it possible to remotely access and interact with the system from anywhere in the world in a secure way, which also enables quick and easy access to data generated by the automated system.

This data is very useful, as it can be analyzed for process improvements or factored into real-time calculations while also being visualized on a touchscreen interface for easy monitoring and interaction. Overall, automation enables an enhanced level of access and control that can lead to increased uptime, efficiency gains, and quality improvements.

Question: What are the emerging trends and technologies in plant automation that are shaping the future of manufacturing?

Mithun Nagabhairava: Artificial intelligence (AI) is playing a pivotal role in advancing automation to autonomy for industrial manufacturers, akin to the transformative impact autonomous vehicles have changed the automotive realm. Cutting-edge AI and machine learning (ML) technologies, robust computing resources, and cost-effective large-scale data collection are enabling to revolutionize the way factories operate, unlocking unprecedented levels of efficiency, productivity, and quality.

To address the fast-changing customer preferences, workforce challenges, and increased competitive landscape, manufacturers are accelerating digital transformation efforts and prioritizing the application of AI and ML to solve their complex production challenges. Enabled by the advancements in AI/ML, leading industrial manufacturers have already expanded the role of AI to enable autonomous decision-making, as well as augment the remaining human decision processes with context and decision support mechanisms.

Advances in artificial intelligence and machine learning technology are helping manufacturers solve their complex production challenges throughout the enterprise. Courtesy: Kalypso

Joe Wagner: One emerging technology in plant automation that is shaping the future of manufacturing is the message queuing telemetry transport (MQTT) protocol. MQTT was originally designed for connections with devices in remote locations with resource constraints or limited bandwidth, making it very lightweight and efficient at moving data to and from a data broker (either locally or in the cloud). More specifically, MQTT is capable of “report by exception” which means that data is only transmitted when it has changed. MQTT is not necessarily “new” but is still relatively new to the world of manufacturing with many companies just starting to adopt this powerful technology.

Question: How can plant managers ensure automated systems are adaptable and flexible to changing production demands?

Daniel Pender: Plant managers should ensure their team selects automation systems that are scalable, expandable, cyber aware, and designed to be supported and maintained in flexible ways. To future-proof automation and control systems, operational budgets must allocate appropriate annual funding to support operations and maintenance activities. Operator and maintenance training, continuing information technology/operational technology (IT/OT) interactions, cyber and network upgrades all help to support production needs outside of the physical systems and technologies.

Plant managers that leverage their annual capital budgets to support expansions or migrations and acknowledge their environmental, social and governance goals will have the best chance of adapting towards the future.

Joe Wagner: One way to describe this ability to be adaptable and flexible to changing production demands is “future-proofing.” When it comes to ensuring that automated systems are as future-proof as possible, there are several factors to consider such as: compatibility with multiple communication protocols and devices, ability to quickly expand the communications capabilities of the system, and the ability to easily expand the input/output (I/O) capabilities of the system. By choosing the right hardware with this level of flexibility, users can ensure that their system will be adaptable and ready for many years of changing production demands.

A continuous reinforcement loop of control adjustments aimed to reduce variability and optimize target process variables enabled by a robust digital twin of a physical system. Courtesy: Kalypso

Question: What are the most critical considerations when selecting automation technologies for a specific manufacturing process? Describe the challenge and solution.

Daniel Pender: Critical considerations when selecting technologies include abilities to scale and change function. It is impossible to anticipate all future needs today. Even if the process is unchanged, the platform should provide a foundation for data, analytics, and information, because today’s manufacturing demands will certainly change or grow in the future. In any industry, companies need to consider process and discrete controls.

For example, in the power space, high-speed tripping and closing of breakers can require millisecond response time for load shedding, whereas in a chemical plant, process variables might require 250-ms updates to support control schemes. In some industries, like paper mills, companies might need to consider controls enabling both slow- and high-speed cycle times.

Joe Wagner: When selecting automation technologies for a specific manufacturing process there are several critical considerations to keep in mind, some of which will depend on the process itself. Some of the more general considerations include ensuring compatibility with existing devices/processes, being flexible and ready for future changes or additions to the process, and selecting robust hardware that is easy to configure. When considering the challenge of being flexible and ready for future changes, one solution is modular hardware that allows users to easily expand the communications capabilities or input/output (I/O) capabilities of a device in the field with minimal disruption to production.

Question: What are the main challenges faced when integrating automation into an existing manufacturing process?

Joe Wagner: When integrating automation into an existing manufacturing process, users should expect at least a few challenges along the way. For example, it is very common for manufacturing plants to have several pieces of legacy hardware which may not be able to communicate directly with newer automation hardware using modern protocols. In cases like this, users can implement an appropriate protocol converter to overcome communication barriers and achieve a high level of connectivity. Another challenge worth considering is operator training. Any time changes are introduced in a manufacturing environment, users should expect at least some operational learning curve and be ready to address any unexpected issues that may pop up.

Question: How can knowledge transfer and training programs be effectively implemented to upskill the workforce for a more automated environment?

Mithun Nagabhairava: Many industrial organizations are undergoing a significant time of transition. As a generation of highly skilled employees are reaching retirement age and leaving the workforce, they are taking with them decades of hard-won experience and tribal knowledge that the next generation will not have. In addition, the new workforce is more inclined to leverage digital technologies and embrace AI-driven solutions for optimizing processes and fostering innovation.

This shift necessitates a strategic approach to knowledge transfer, training, and upskilling. Leading manufacturing organizations are adopting AI-enabled autonomous capabilities to be central for enterprises to preserve the wisdom of the past and harness the potential of emerging technologies to shape the next-generation workforce.

Increase the probability of success and access time-to-value of new-phase tactical projects. Courtesy: Kalypso

By harnessing autonomous control strategies, organizations can develop robust models that integrate operator insights with knowledge gleaned from historical data to determine the necessary system adjustments for optimal results. With these advanced capabilities, AI is elevating the role of an operator from making repetitive manipulations to managing the performance of the machines.

Question: What key factors influence the return on investment (ROI) for plant automation projects?

Mithun Nagabhairava: As organizations are advancing their automation and digital capabilities, it is important to start with assessing the current level of performance across the manufacturing process. This would help to determine which areas are the most challenging and would provide the best opportunities to improve asset availability, optimize process consistency, enhance quality control, and reduce energy usage.

Leading organizations prioritize high-value use cases, demonstrating their worth through limited deployments and devising strategic plans for scalable implementation.

Autonomy and closed-loop optimization can be achieved at various levels through vertical integration. Courtesy: Kalypso

Question: How can automation improve product quality and consistency in a manufacturing plant?

Daniel Pender: Critical considerations when selecting technologies include abilities to scale and change function. It is difficult to anticipate all future needs today. Even if the process is unchanged, the platform should provide a foundation for data, analytics and information because manufacturing demands will change or grow in the future. In any industry, companies need to consider both process and discrete controls. For example, in the power space, high-speed tripping and closing of breakers can require millisecond response time for load shedding, whereas in a chemical plant, process variables might require 250 ms updates to support control schemes. In some industries, like paper mills, companies might need to consider controls enabling slow- and high-speed cycle times.

Joe Wagner: There are a number of ways automation can improve product quality and consistency in a manufacturing plant, but one word that can describe it very well is “data.” Automated systems are capable of tracking relevant data points over time and displaying that data in clear ways while keeping a historic record of measurements for analysis. For higher-urgency situations, automated systems are capable of alerting users via text and/or e-mail when certain alarms are active, allowing for a quick response and correction. Finally, automated systems may be capable of making automatic real-time adjustments to processes to account for any deviations, ensuring a high level of quality and consistency.

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