Robust possibilistic programming-based three-way decision approach to product inspection strategy

Abstract

During product inspection, Type I and Type II errors, widely considered to assess product quality, are represented by erroneously rejecting non-defective products and erroneously accepting defective products, respectively. Meanwhile, the formulation of product inspection strategy is oftentimes deemed as an interdependent process influenced by multiple factors (e.g., production technology and customer demand) from both upstream (e.g., production process) and downstream (e.g., customer zone). Due to the limited understanding and knowledge of decision-makers on imprecise parameters of these factors, it is challenging for decision-makers to formulate an appropriate product inspection strategy. To address the aforementioned challenges, an improved three-way decision (3WD), known as robust possibilistic programming (RPP)-based 3WD is put forth. Such an improvement for 3WD is evident in two aspects (1) the RPP model endows 3WD to address imprecise parameters and chance constraints using flexible attitudes, and (2) the RPP model ensures the formulation of the product inspection strategy of 3WD is robust. Additionally, with the aid of 3WD, an intermediate/uncertain decision, is introduced to simultaneously reduce the aforementioned two types of errors. A case study of a semiconductor manufacturing system, along with discussions and two comparative studies, is presented to demonstrate the effectiveness and performance of this approach. As shown in this study, the proposed approach (1) effectively prevents decision-makers from making an over-conservative attitude in the formulation of the product inspection strategy, (2) has better performance in satisfying customer demand, and (3) has significant advantages in terms of cost and computational time.