LONDON, ON, June 16th, 2020 – JMP Solutions and Control Station are joining forces to provide process and control loop audit services for manufacturing environments in order to identify and…Read More
Knowing how to tune a PID loop while satisfying its unique control objective is critical. Fortunately there is a group of descriptive statistics that characterizes a controller’s core performance attributes and that helps you to get the tunings right each time. Below are four (4) KPIs that process control experts frequently use when determining if their new PID tuning parameters are right for the job.Read More
As stated in a previous post, tuning PID controllers is a multi-step process. After you gather your data from your step test, the next step in the process is fitting a model to your Process Data. Fitting a model involves the analysis of bump test data and the calculation of tuning parameters that are specific to both your controller and your control objective. This post highlights some industry best practices for fitting a model to your test data.Read More
Poor Controller Tuning.
Operator interventions and Mode Changes are often viewed negatively. When a PID loop is switched out of automatic there can be a sense that the controller wasn’t allowed to perform its job. With each change, goals related to production throughput and efficiency suffer a psychological hit. Since so much is invested in automating plant-wide production, interventions can feel like a step backwards. Viewed in a different light, however, those interventions provide potentially valuable insights that help production to move forward.
Temperature is one of the more common types of self-regulating – also known as non-integrating – processes used in industry. Like other self-regulating loops, temperature loops tend to naturally settle at a new operating state when adjustments are made to the corresponding Controller Output. What’s more, temperature loops are nonlinear in their behavior and process dynamics can vary considerably from one range of operation to the next.Read More
Tuning a PID controller doesn’t have to be hard. Whether a practitioner chooses to tune control loops manually or with the help of software, the procedure is relatively straight forward and can produce highly effective results. It can be argued that using software is faster and provides more optimal results than manual tuning, but that’s an argument that largely depends on the economic importance of the PID control loop in question. In the end, the goal is the same: To tune for improved control loop performance.Read More
Level controllers present challenges that are different from others. Although their presence is significant they lag behind Flow controllers in their overall share of the typical production facility’s process control landscape. Unlike other processes such as Temperature, Pressure and Flow, Level control loops demonstrate different dynamics, they don’t play by the same rules as the non-integrating (also known as self-regulating) types. And although best-practices for modeling and tuning Level loops are similar they involve nuances that can hamper a less experienced practitioner.Read More