Contents 1. INTRODUCTION
Globalization business environment speeds up the development of quality management, and the widely used makes the Six Sigma management become one of the popular quality management method in the world. The Six Sigma makes up of statistical process control-SPC, the measurement system analysis-MSA, the failure mode and effect analysis-FMEA, and the experiment of design-DOE, etc. As we known, quality has always been the domain of accurate science, and the traditional methods for assessing the capability of manufacturing processes are dealing with crisp quality, but the existence fuzzy uncertainty in manufacturing system is an unarguable fact, just as Carvalho and Machado [1] commented, “In a global market, companies must deal with a high rate of changes in business environment…The parameters, variables and restrictions of the production system are inherently vagueness.” Such a factual recognition inevitably brought fuzzy mathematics initiated by Zadeh [2] into manufacturing system management and quality management, and after the inception of the notion of fuzzy sets, there are efforts by many authors, such as Viertl and Taheri [3], as well as Zadeh himself, to apply this notion in statistics. So in this paper, we introduce the fuzzy attribute of quality and the way of a qualified handling of fuzzy quality. It brings to light the transition and consistency between precise quality and fuzzy quality. The paper primary introduces the development of “fuzzy control chart” and “fuzzy process capability indices”, other applications of fuzzy quality tools in Six Sigma management, such as fuzzy FMEA, fuzzy MSA, fuzzy DOE, are also introduced.