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Development Of An Intelligent Quality Management System Usingfuzzy Association Rules

机译:基于模糊关联规则的智能质量管理系统开发

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摘要

In order to survive in the increasingly customer-oriented marketplace,continuous quality improvement marks the fastest growing quality organization's success.In recent years,attention has been focused on intelligent systems which have shown great promise in supporting quality control.However,only a small number of the currently used systems are reported to be operating effectively because they are designed to maintain a quality level within the specified process,rather than to focus on cooperation within the production workflow.rnThis paper proposes an intelligent system with a newly designed algorithm and the universal process data exchange standard to overcome the challenges of demanding customers who seek high-quality and low-cost products.The intelligent quality management system is equipped with the "distributed process mining" feature to provide all levels of employees with the ability to understand the relationships between processes,especially when any aspect of the process is going to degrade or fail.An example of generalized fuzzy association rules are applied in manufacturing sector to demonstrate how the proposed iterative process mining algorithm finds the relationships between distributed process parameters and the presence of quality problems.
机译:为了在日益增长的以客户为导向的市场中生存,持续的质量改进标志着增长最快的质量组织的成功。近年来,注意力集中在显示出对质量控制支持有很大希望的智能系统上。据报道,目前使用的系统中有一部分能够有效运行,因为它们旨在保持指定流程内的质量水平,而不是着眼于生产工作流程中的合作。rn本文提出了一种具有新设计算法和通用性的智能系统过程数据交换标准,以克服寻求高质量和低成本产品的苛刻客户的挑战。智能质量管理系统配备了“分布式过程挖掘”功能,可为所有级别的员工提供理解关系的能力在过程之间,尤其是在过程的任何方面以广义模糊关联规则为例,在制造业中进行了应用,以说明所提出的迭代过程挖掘算法如何发现分布式过程参数与质量问题之间的关系。

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