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Tuning the Forgotten Loop
We can tune PID controllers, but what about tuning the operator?
The purpose of tuning loops is to reduce errors and thus provide more efficient operation that returns quickly to steady-state efficiency after upsets, errors or changes in load. State-of-the-art manufacturers in process and discrete industries have invested in advanced control software, manufacturing execution software and modeling software to "tune" everything from control loops to supply chains, thus driving higher quality and productivity.
The "forgotten loop" has been the operator, who is typically trained to "average" parameters to run adequately under most steady-state conditions. "Advanced tuning" of the operator could yield even better outputs, with higher quality, fewer errors and a wider response to fluctuating operating conditions. This paper explores the issue of improving operator actions, and a method for doing so.
Over the past decade we've spent, as an industry, billions of dollars and millions of man-hours automating our factories and plants. The solutions have included adding sensors, networks and software that can measure, analyze and either act or recommend action to help production get to "Six Sigma" efficiency. However, few, if any, plants are totally automated. Despite a continuing effort to remove personnel costs and drive repeatability through automation, all plants and factories have human operators. These important human assets are responsible for monitoring the control systems, either to act on system recommendations, or override automated actions if circumstances warrant.
Most of the time, operators let the system do what it was designed and programmed to do. Sometimes, operators make errors of commission, with causes ranging from misinterpretation of data to poor training or errors of omission attributed to lack of attention or speedy response. An operator's job has often been described as hours of boredom interrupted by moments of sheer panic. What the operator does during panic situations often depends on how well he or she has been trained, or "tuned."
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