Abstract
AbstractThe concurrent use of statistical process control and engineering process control involves monitoring manipulated and controlled variables. One multivariate control chart may handle the statistical monitoring of all variables, but observing the manipulated and controlled variables in separate control charts may improve understanding of how disturbances and the controller performance affect the process. In this article, we illustrate how step and ramp disturbances manifest themselves in a single‐input–single‐output system by studying their resulting signatures in the controlled and manipulated variables. The system is controlled by variations of the widely used proportional‐integral‐derivative(PID) control scheme. Implications for applying control charts for these scenarios are discussed.
Highlights
Statistical process control (SPC) and engineering process control (EPC) have developed more or less independently but with the same overarching goal of reducing process variability
SPC methods typically employ control charts to monitor that a product quality characteristic or important process variable remains close to a nominal value
The analyst may even fail to detect a disturbance affecting the system when monitoring only the controlled variable in an EPC scheme. This mistake may occur since the controlled variable in a feedback controller usually is ‘the’ important process output that the naïve analyst may think warrants monitoring through SPC
Summary
Statistical process control (SPC) and engineering process control (EPC) have developed more or less independently but with the same overarching goal of reducing process variability. If control charts signal a statistically significant change in the process mean and/or variability, the SPC methodology assumes that offline process analysis will be able to identify sources of variation, so-called assignable causes. Given that the root cause can be identified, problem-solving methods can be used to remove or reduce effects of the variation sources. EPC attempts to make a process insensitive to external disturbances by continuously adjusting a process input (manipulated variable) to ensure that an output variable (controlled variable) remains on target (the controller set point). The assignable causes in SPC usually arise from external disturbances Such disturbances will increase probabilities for out-of-control signals in control charts. Controllers in EPC continuously adjust the process to minimize deviations of a controlled variable from its set point due to various unexpected and/or unplanned external phenomena. The control action stems from the manipulation of a related and less sensitive variable thereby transferring the variability from the controlled variable to the manipulated variable
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