Online automatic process control using observable noise factors for discrete-part manufacturing

Abstract

Robust Parameter Design (RPD) has been used as the primary technique to reduce process and product variability. The offline choice of appropriate control factor settings allows RPD to ensure that noise factors have a minimum influence on responses. In this article, an alternative methodology of automatic process control is proposed, that is, controllable factors are adjusted online based on in-process observations of noise factors. A cautious control strategy, which explicitly considers the observation uncertainty in adjusting the settings of controllable factors, makes the system performance consistently more favorable when compared with the certainty equivalence control strategy and RPD. On the other hand, RPD can be considered a special case of automatic control laws using a constant control setting during production. A case study of a sheet-metal stamping process demonstrates that the implementation of the proposed method in an industrial facility can lead to significant quality improvements.