Greg: In part 3 we introduced to you some key insights gained from the ISA 5.9 Technical Report on proportional-integral-derivative (PID) structures and external-reset feedback to do what can be an incredible job of basic and advanced regulatory control. Here we get close to the bottom line in terms of how you measure and improve loop and process performance. We start with my general view on performance opportunities documented in ISA 5.9 and conclude with a perspective of significant optimization opportunities offered by Dr. Russ Rhinehart, emeritus professor at the Oklahoma State University School of Chemical Engineering, who has developed practical methods for nonlinear modeling and optimization in the process industry.
There are many different metrics, objectives, and methods for improving loop performance that are a result of many different types of products, processes, dynamics, markets and PID capabilities. Typically, the actual goal is to improve process performance and profit, which should dictate the required loop performance, such as good load regulation or minimizing propagation of variability.
Explore the impact of edge computing on industrial robotics, enabling real-time processing, reducing latency, and enhancing security in smart warehouses.
Watch the video to find out how simulation for automation lets you validate and optimize production machines so you can build better battery machines faster.
