Fuzzy cause selecting control charts for phase II monitoring of a two stage process

Abstract

In this paper, it is assumed that there is a two-stage process in which the quality characteristic of the second stage is represented by fuzzy number which is monitored to detect shifts in the process. Also due to the existence of cascade property in a two-stage process, the quality characteristic of the second stage is affected by the quality characteristic in the first stage. Using fuzzy random variable which includes two kinds of uncertainty randomness and fuzziness simultaneously is considered. We proposed fuzzy Shewhart cause-selecting control chart and fuzzy exponentially weighted moving average (EWMA) cause-selecting control chart to detect different magnitudes of shift in the process parameters in phase II analysis. The performance of the proposed methods is evaluated by simulation in terms of average run length (ARL) criterion. Finally, a numerical example is given to show the application of the proposed methods step by step.