Integrated Quality, Maintenance and Production model for multivariate processes: A Bayesian Approach

Abstract

In the era of modern manufacturing, automated inspection systems can facilitate online product quality assessment, generating data that can be used not only in a process control context but for equipment maintenance purposes, as well. The challenge is to develop appropriate tools to efficiently exploit the collected data by transforming them into optimal decisions that add value to the monitoring process. To this end, this paper proposes a Bayesian model that jointly optimises the interrelated process aspects of production, maintenance, and quality in modern manufacturing environments. The process output is characterised by multiple correlated quality characteristics and subject to multiple quality shifts and failures. Optimal real-time decisions are made based on a cost optimisation criterion. Finally, a numerical investigation is conducted to evaluate the performance of the proposed data-driven and widely applicable tool for contemporary processes.