IoT requires ‘systems thinking’

By Bill Lydon, InTech, Chief Editor

Should Internet of Things (IoT) investments focus on narrow business outcomes? Keeping IoT deployments simple by focusing on a single narrow application is being sold as a way to apply new technologies. These can be worthwhile investments, but only focusing on narrow applications may put you in the position of "not seeing the forest for the trees." Basically, if you look at specific narrow applications one at a time, you might not realize that a group of separate "trees" go together to make a "forest." If everyone strictly followed this logic, nobody would have invested in a distributed control system or a factory automation system. A major value that automation professionals bring an organization is system-level thinking, analysis, and application. Rather than focusing too closely on one item, taking an overall systems view provides a broader perspective. Generally, this will reveal a whole forest you could not see before because you were too close, and focusing on the trees.

The influx of innovative and lower-cost technology provides a range of new tools for taking a systems-level approach to manufacturing and process operations to increase productivity and efficiency. The ISA95, Enterprise-Control System Integration, and ISA88, Batch Control, series of standards are two strong examples of models for applying system-level thinking that have yielded increased quality, productivity, and efficiency for manufacturers worldwide. It is worth noting that these standards are being applied using IoT and other new technology in new architectures, including Industry 4.0.

The system-focused thinking of automation professionals is critical for the future success and existence of many manufacturing organizations. Manufacturers worldwide have realized low labor cost is not a winning strategy, and this is leading to greater adoption of automation, with IoT accelerating applications. There is a revolution going on with a much wider and growing range of automation options today driven by technology advances and lower-cost solutions. It is analogous to what happened in the computer industry with the shift from mainframe and minicomputers to PCs that enabled small- to medium-size companies to leverage computing to be more competitive. Manufacturers throughout the world are automating to stay competitive and profitable. The alternative is to be overtaken.

Lack of knowledge, more than actual budget constraints, is a major barrier when these types of changes occur. It is easy to do things the way they have always been done as competitive producers with lower prices take away business. It is easy to say they are "giving away the business" rather than seeking to understand the changing competitive landscape.

The automation professional's challenge is to first evaluate production operations to understand the greatest points of inefficiency, including existing overall production processes. Lean manufacturing concepts, value engineering analysis, and logistics analysis are great tools to uncover opportunities for improvement. It is advisable to use these foundational methods on an ongoing basis for continuous improvement. Automation professionals armed with the results of these types of analysis then need to educate themselves on new solutions available through Internet searches, webinars, and industry events.

As illustrated by the changing landscape in the computer industry over the years, the established automation suppliers may not offer the best solutions to be competitive. Too often manufacturers rely on the suppliers they have used for years. This is a very narrow lens for viewing what is possible to be more competitive.

Members of ISA have great opportunities to participate in forums and standards groups to share ideas, concepts, and experiences with other automation professionals.

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About the Author

Bill LydonBill Lydon is InTech’s chief editor. He has more than 25 years of industry experience in building, industrial, and process automation, including product design, application engineering, and project management.

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