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Transitioning from basic to adaptive automation

June 11, 2021
In this installment of Automation Zone, learn why industrial automation will rely on edge computing and remote connectivity to deliver adaptive solutions.
The digital transformation journey associated with industrial automation has been under way for some time. It is applicable to manufacturing facilities, processing plants, oil and gas producing equipment, and other operations—basically anywhere there are automated systems. Yet even the most highly automated operations may be quite far from achieving full autonomy, where most actions are taken automatically, with limited human oversight required. Fortunately, the same technologies and efforts used to achieve basic automation are also foundational for implementing more far-reaching capabilities.
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This article is part of our monthly Automation Zone column. Read more from our monthly Automation Zone series.

For instance, remote monitoring capability is important in its own right, and it has gained newfound urgency due to world events like COVID-19, along with regional occurrences such as weather-related disruptions. Implementing the right edge automation technologies with remote connectivity enables users to move beyond basic automation to accomplish far more. This article looks at how foundational industrial automation technologies pave the way for more integrated operations, which in turn will lead to increasingly adaptive functionality.

Expanding capabilities

Industrial automation in terms of operations and maintenance can be expressed as a range of capabilities (see Figure 1). Most modern facilities have moved past the purely manual phase, although they may still have many manual steps for accessing or gathering information from portions of their systems. Any activities that remain manual or unmonitored only increase worker effort and the possibility for introducing errors in operation.

Figure 1. Edge computing and remote connectivity are foundational elements for industries to move beyond basic automation and toward increasingly adaptive functionality. (Source: Emerson)

Automated systems, typically implemented with programmable logic controllers (PLCs) and human-machine interfaces (HMIs), have facilitated huge efficiency and quality gains for manufacturing industries, but today’s companies are realizing they need to improve further.

Optimized operations, enabled by edge computing hardware and software, can let them take these next steps. At this phase, the automation systems must analyze performance, and then alert users regarding how to optimize operations, while pointing out potential anomalies. Remote connectivity is needed to log data to the cloud, and so both operations and maintenance personnel to access the system.

The next phase is for adaptive operations. When automation achieves these levels, it can locally analyze, predict, and resolve issues, only requiring some human confirmation or intervention by exception, respectively. Highly capable edge computing with machine learning is required to achieve this level of automation.

Connected operations are a necessary building block for optimizing and integrating operations, and eventually enabling them to run adaptively (see Figure 2).

Figure 2. Reliable and secure connected operations minimize the need for local personnel and enable more integrated and adaptive production. (Source: Emerson)

Building the foundation

Today’s plant operators often have a somewhat restricted perspective based just on locally available data, with few tools and procedures to help them optimize operations. Similarly, much of the maintenance activities are performed reactively, incurring expensive travel, fieldwork, and downtime.

A foundation of edge-located hardware and software is necessary to advance these operations, and to allow remote systems and users spanning an entire enterprise to interact with each other. Here are some of the key enablers provided by edge computing:

  • access to self-diagnostics built into measurement devices
  • connectivity to industrial internet of things (IIoT) sensors outside of traditional automation
  • automated loop monitoring, tuning, and optimization
  • secure communications to higher-level systems
  • advanced visualization and analytics
  • equipment condition monitoring
  • aggregated status information presented on dashboards
  • prioritized notifications and alerts transmitted to remote workers.

Edge computing hardware and software is available to make these and other benefits a reality, greatly improving operations.

Edge solutions

Edge solutions in the form of edge controllers, edge computing devices, and edge gateways are essential to provide seamless connected operations and to promote basic automation implementations to more advanced levels. These solutions can certainly be built into new installations, but they are equally applicable for retrofitting existing equipment or for adding to already operating systems.

While modern PLCs are very capable in their roles, an edge controller can fulfill the same real-time control role, while also incorporating edge capabilities using a general-purpose operating system in a safe and cooperative manner without compromising the determinism and speed of the real-time control. This future-proofs the operation, especially for new installations where the all-in-one control and compute functionality can be provided using one compact device. If only higher-level visualization, communication, and analytical functions are needed for an application, a standalone separate edge computing device can provide these and is often the ideal solution.

An edge controller or a standalone edge computing device is often the only way to shift sufficient computing power to where it is needed at the operational edge. These devices are built tough enough to withstand the rigors of factory floors, and at remote sites like oilfields—while providing the required functionality.

Implementing edge solutions can result in:

  • adding remote visualization and dashboarding of operational information, with provisions for operator interaction and troubleshooting from anywhere using any device
  • getting the data from non-traditional intelligent sensors, which are usually not part of the control schema, to get a better holistic view of machine operations both on premise or in cloud
  • analyzing the data to determine overall equipment effectiveness, optimizing production throughout the value chain, and transitioning to predictive maintenance.

Today’s generation of edge computing devices are making it easier than ever for users to create and implement advanced solutions for automating their systems. These platforms also future-proof applications, so remote connectivity, optimized operation, and even highly adaptive functionality can be progressively implemented.

Path to adaptive automation

End users and systems integrators in all industries are increasingly integrating edge computing technologies to improve their operations in many ways. Workers can become “super operators,” with actionable visibility into greater swaths of the value chain, by using visualization and analytical tools to reduce risk and improve overall value to the enterprise. Effective automation and remote connectivity empower teams to move away from a reactive approach and toward a culture of efficiently recognizing issues early, no matter where they are, and preventing failures.

As edge computing implementations advance, the state of industrial automation will progress from basic to optimized, and eventually to a high degree of adaptive operation. Throughout all these phases, the secure remote connectivity offered by edge computing hardware and software will endure as an essential requirement.

This story originally appeared in the June 2021 issue of Plant Services. Subscribe to Plant Services here.

About the Author: Vibhoosh Gupta

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