What Role Should CLPM Play in a Process Manufacturer’s Intelligent Operations Strategy? How Does CLPM Contribute to Improved Process Health and Asset Health?

PID control loops are critical in the regulation of plant-floor production processes. The health of these loops serves as an indicator of the wellness of a facility’s overall production process and its ability to operate efficiently. This suggests that investing in control loop performance monitoring (CLPM) should be prioritized as the foundation of a process manufacturer’s data-centric Intelligent Operations and sustainability initiatives. 

Consider the following insights shared by Gopal Gopalkrishnan, Capgemini’s Senior Director of Global Digital Manufacturing:

• While advanced machine learning methods may have a role in process improvements such as model predictive control, multivariate and multi-unit process optimization, and others, a sound CLPM program should be the first step. Simple statistics such as loops in manual versus auto, variability, and average absolute error can provide actionable KPIs that are easier to understand and act on without dealing with false positives.
• CLPM is not only crucial for process health but also asset health, particularly for control valves. A well-managed and well-behaved control loop is a prerequisite for good process health, with CLPM serving as the first rung. It can expose loops with oscillations and valve chatter, leading to excessive component wear and premature valve failure. It can also identify valve stiction, a troublemaker that can be easily seen through CLPM charts.
• By implementing CLPM and making control loop statistics available through dashboards for plant-wide audiences, the Hawthorne effect – awareness of being observed – can motivate action and keep production processes running well via healthy control loops

Gopal suggests that a layered fit-for-purpose approach to IIoT analytics for process health via process control loops is critical for plant-floor production processes. Investing in CLPM as the foundation of data-centric Intelligent Operations, Sustainability, Smart Maintenance, and others before chasing advanced Machine Learning methods is key. By adopting a layered approach to analytics with a bias for simplicity, process manufacturers can achieve better process health and asset health while improving their overall production processes. These, in turn, elevate plant efficiency and ultimately lead to increased profitability.

To learn more about the role that CLPM solutions play in establishing healthy, sustainable plant operations, click here and read Gopal’s article published on The OSIsoft Community’s PI Square forum.

https://pisquare.osisoft.com/s/Blog-Detail/a8r8W0000008UCaQAM/a-layered-fitforpurpose-approach-to-iiot-analytics-for-process-health