Use of Linguistic Variables in Control Charts: A Comparative Literature Analysis

Abstract

Process monitoring, diagnosis, and supervision are critical components of quality management. For this aim, control charts (CCs) are one of the important tools for statistical process control (SPC). However, given the uncertainties in real-world problems, classical logic is often ineffective due to the assumptions it considers while modelling these uncertainties. On the other hand, if quality-related characteristics are determined by linguistic expressions, classical CCs are insufficient to explain quality characteristics, and correctly evaluate the process. As a solution to this problem, decision analyses of CCs developed with linguistic variables under uncertainty are usually performed by using the fuzzy set theory. For this reason, a literature review has been conducted for the purpose of this study. As a result, the aim is to establish a foundation and provide direction for future studies, which consist uncertainty in quality assessment processes, by using linguistic variables to more effectively model the problem.