Quality costs and Industry 4.0: inspection strategy modelling and reviewing

Abstract

Inspection strategy (IS) is a key component impacting quality costs. Although often considered an inflexible output of initial quality plans, it may require revisions given the dynamic quality situation of the manufacturing system. It is from this background that the present study aims to model and compare different IS based on the cost of quality (CoQ) approach for a case study in the automotive manufacturing industry. While many computational inspection strategy models (ISMs) are available in the literature, most of them face application challenges and struggle to incorporate real-world data. The present study addresses this gap by developing a model that not only represents a real testing station in a manufacturing line but also uses historical production data. Additionally, in relation to model inputs, this study explores the challenges and opportunities of acquiring reliable quality cost estimates in the Industry 4.0 context. Among the main contributions of this work, the developed CoQ-based ISM can be used as a decision-making aiding tool for inspection revision and improvement, while conclusions about quality cost data collection in the industrial digitalization context can help advance the CoQ approach in practice.