For an edible oil processor, the best way to efficiently manage unique characteristics of different products was by adopting modern control loop performance monitoring software with the ability to recognize different operating states.
Most manufacturing operations are constantly faced with change, and therefore they must be designed to adapt. Change routinely presents itself in the form of different production recipes, varying material properties, irregular equipment availability, weather extremes and many other factors. What’s more, change often includes several of these variables concurrently, and each may interact with others—adding still more complexity.
If so many processes experience these complications, how can manufacturers apply technology to address the issue? Good automation system designs detect these conditions, and then they react by taking control actions to maintain production throughput, quality and efficiency. Even better control designs recognize not only varying conditions, but also unique operating states so they can tailor their control action in ways that are optimized for each state. Production plant control functionality must address changing situations, and similarly it does not make sense for their analysis to be based on averages from many varying states. Simply put: If a control system can respond dynamically to changing production states, then the facility’s controller analytics engines should be able to adapt as well.