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Much attention and monetary investment is rightly paid to the physical design and maintenance of a process plantâs equipment, such as pumps, vessels, heat exchangers, reactors and distillation towers. However, a significant factor affecting a process plantâs performance is the design, and especially the on-going maintenance of, field instrumentation and base-layer control structures. This includes the calibration of field sensors & transmitters, final control elements, as well as the regulatory & âadvanced regulatoryâ control structural design. The condition and reliability of these element are increasingly important as greater reliance is placed upon model predictive control, including AI/ML technologies, and real-time optimization applications. While there are various software products in the marketplace which purport to alleviate the need for manual assessment of field instruments and regulatory control performance, their on-going success is mixed, at best. Therefore, human effort to analyze and assess the condition and quality of instrumentation and controls is still required.
This paper describes a variety of data-analysis techniques which have been found useful in identifying & diagnosing field instrumentation issues, such as sticking valves and calibration errors, assessing actual process behavior of distillation columns and determining proper MV-CV Pairing for regulatory controls. The difference between open loop stable (OLS) and Integrating processes and the effect on PID tuning and, thus, plant performance, is also covered.
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