基于模糊神经网络的质量成本控制模型

Shang Shan-shan, You Jian-xin
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引用次数: 4

摘要

为了建立新的质量成本控制模型,本文首先在PAF模型的基础上,设置质量成本的第三层次主体,即质量成本由预防成本、评估成本、失效成本组成,并根据历史数据进行帕累托分析,找出主要影响主体;其次,运用相关分析和偏相关分析,找出实际影响主体;然后对这些实际影响主体进行了可控因素和不可控因素的分析。最后,在所有分析结果的基础上,利用模糊控制和神经网络,设置模糊子集和规则,建立基于模糊子集和规则的质量成本控制模型,实现质量成本的自动化控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quality cost control model based on fuzzy neural network
In order to develop a new quality cost control model, the paper first sets the third level subject of quality cost base on the PAF model, which is that quality cost is composed of prevention cost, appraisal cost, failure cost and does Pareto analysis according to the history data, finding the main influential subjects, second, it uses correlation analysis and partial correlation analysis to find the actual influential subjects, then it analyses the controllable factors and uncontrollable factors to these actual influential subjects. Finally, based on all the analysis results, and by taking use of fuzzy control and neural network, the paper sets fuzzy subsets and rules and establishes a quality cost control model based on them to facilitate automatic quality cost control.
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