Fuzzy theory applied in quality management of distributed manufacturing system: A literature review and classification

Abstract

Fuzzy theory has been regarded as a very important technique for quality management (QM) of distributed manufacturing system and attracts the attentions of academic and industry; however, there is a lack of a comprehensive literature review and a classification scheme for it. This paper is the first academic literature review of the fuzzy theory applied in quality management of distributed manufacturing system. It involves five most popular databases in this research area and covers more than 20 journals, proposes a classification scheme using clustering analysis method. Sixty-one journal articles were finally selected, reviewed and classified. Each selected article was classified firstly based on four QM dimensions (quality planning, quality control, quality assurance and quality improvement) and the elements/process of each dimension. Sequentially, articles were further classified by the nine fuzzy techniques which are fuzzy regression, fuzzy classification, fuzzy clustering, fuzzy control, fuzzy inference, fuzzy numbers, fuzzy optimization, fuzzy statistics and fuzzy data analysis. Among the four QM dimensions, quality improvement has the highest publications in recent years and fuzzy decision making and fuzzy number are the main techniques adopted in quality improvement.