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

机译:基于层次分析和模糊关联规则的制造业智能质量管理系统

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摘要

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.
机译:近年来,操纵质量管理系统(QMS)已成为企业中的关键战略考虑。实际上,公司不断需要优化其工业工具以提高生产率并永久提高系统的有效性和效率。本文的目的是提出一种发现制造业变量之间隐藏关系的方法。层次分析法(AHP)用于确定变量的优先级。提出了一种基于模糊集概念和关联规则方法的Apriori算法,从问卷中收集到的数据中,根据模糊规则提取出有趣的模式。已经为制造业获得了一种智能质量管理系统(IQMS),可以根据模糊关联规则将数据转换为知识。根据分析,发现客户满意度优先于盈利能力。同样,使用IQMS得出了五个规则,这些规则指示导致更高客户满意度的各种条件。

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