A new perspective on fuzzy process capability indices: Robustness

Abstract

Process performance can be analyzed by using process capability indices (PCIs), which are summary statistics to depict the process' location and dispersion successfully. Many PCIs have been proposed in the literature. Although they are very usable statistics to summarize process' performance, they can give misleading results and can cause incorrect interpretation if the process parameters have a correlation. In this case, the new PCIs called robust PCIs (RPCIs) should be applied. In this paper RPCIs are obtained for a piston manufacturing company and the fuzzy set theory is incorporated to increase PCIs' flexibility and sensitivity by defining specification limits and standard deviation as fuzzy numbers. Then fuzzy RPCIs are obtained to express the process performance more realistic for the piston manufacturing stage.