Development of a Fuzzy Exponentially Weighted Moving Average Control Chart with an α‑level Cut for Monitoring a Production Process

摘要

Statistical quality control is a useful approach that applies to statistical techniques for monitoring a production system. Thesecharts are effective to monitor the process under certain conditions. On the other hand, the fuzzy set theory is an appropriatetool to deal with an uncertain situation. This paper is fourfold. First of all, triangular fuzzy numbers with an α-level cuttechnique are used for each sample. The α-level cut technique is sensitive to satisfy the process requirement. Second, a fuzzyexponentially weighted moving average (FEWMA) control chart is proposed with the α-level cut technique. The proposedFEWMA detects small shifts under uncertain situations while using a unity technique for samples. Third, the fuzzy targetfocusedprocess capability index (FC_(pm)) index is proposed to measure the fuzzy process performance. Then, a case studyis presented to monitor a pumice block plant using the FEWMA control chart with the α-level cut and measure the processperformance with the FC_(pm) index. Comparative studies are also presented. By using the proposed FEWMA control chartwith the α-level cut, the accuracy and the flexibility of control specification limits are reported for the case study.