Intelligent quality management system using analytic hierarchy process and fuzzy association rules for manufacturing sector

In recent years, steering a quality management system (QMS) has become a key strategic consideration in business. Indeed, companies constantly need to optimise their industrial tools to increase their productivity and to permanently improve the effectiveness and efficiency of their system. The purpose of this paper is to present a methodology for discovering the hidden relationships among the variables in manufacturing sector. Analytic hierarchy process (AHP) was used to prioritise the variables. Apriori algorithm based on the concept of fuzzy set and association rule method is proposed to extract interesting patterns in terms of fuzzy rules, from the data collected using the questionnaire. An intelligent quality management system (IQMS) to convert the data into knowledge in terms of fuzzy association rules has been obtained for manufacturing sector. Based on the analysis it has been found that customer satisfaction takes precedence over profitability. Also, five rules have been derived using the IQMS indicating the various conditions leading to higher customer satisfaction.