Process control of product quality

Abstract

Abstract This paper describes a method to control output product quality (product variability) by applying engineering or automatic process control (APC) and statistical process control (SPC) techniques. APC techniques have been used to control process variables such as feed rate, temperature, pressure, viscosity, and to product quality variables as well. SPC techniques have also been applied to control product quality. APC and SPC techniques overlap at the interface of the two process control methodologies. It is possible to produce material of desired quality by having an acceptable level of variation in the measured output characteristics. APC aims to maintain certain key process variables as near their set points for as much of the time as possible. There are situations in process control where some form of feedback control is necessary and yet where stability cannot be easily attained in the feedback control loop. Disturbance (noise) afflicts a process, which together with issues of dynamics and dead time (time delay) compounds the process control problem. The process control practitioner faces a challenge while tackling issues of process delay (dead time) and dynamics (inertia). Process control of product variability (control error standard deviation) is possible by developing and simulating a feedback control algorithm for dead-time processes. It is quite common to encounter problems connected with feedback (closed-loop) control stability, controller limitations, and dead-time compensation to obtain minimum variance (mean square error) control at the output. Details of a method to control the quality of a product at output by applying statistical process monitoring and feedback control adjustment are presented in this paper. The focus of this paper is on the issues of process delay (“dead time”) and dynamics (“inertia”) at the interface between SPC and APC to control output product quality.