工业工程 ›› 2020, Vol. 23 ›› Issue (5): 109-117.doi: 10.3969/j.issn.1007-7375.2020.05.015

• 专题论述 • 上一篇    下一篇

基于熵权和模糊物元的改进多元过程能力分析

赵家黎, 李江, 徐远平   

  1. 兰州理工大学 机电工程学院,甘肃 兰州 730050
  • 收稿日期:2019-07-10 发布日期:2020-10-30
  • 作者简介:赵家黎(1980-),男,河南省人,副教授,博士研究生,主要研究方向为过程质量控制、数字化设计与制造
  • 基金资助:
    国家自然科学基金资助项目(51265024)

An Analysis of Improved Multivariate Process Capability Based on Entropy Weight and Fuzzy Matter Element

ZHAO Jiali, LI Jiang, XU Yuanping   

  1. School of Mechanical and Electronic Engineering, Lanzhou University of Technology, Lanzhou 730050, China
  • Received:2019-07-10 Published:2020-10-30

摘要: 为解决多品种小批量产品数据采集困难及各指标间存在交互影响致使传统方法难以奏效的现状,基于主成分分析法的多元过程能力指数会造成信息量缺损。该方法将工序能力影响因素采用模糊物元方法构造工序相似条件,选出相似工序将小批量问题变成大批量处理,应用公差系数法将原始数据转化为相对数据。提出基于熵权理论和模糊物元的改良多元过程能力指数。该论文结合某产品进行实例分析,验证了该方法的实用性和有效性。

关键词: 多品种小批量, 模糊物元, 熵权理论, 多元过程能力指数

Abstract: In solving the difficulty in data collection of multi-variety and small batch products and the interaction between various indicators, the traditional methods are not effective. The multi-process capability index based on principal component analysis will cause information loss. By using the fuzzy matter element method, the process similar conditions are constructed, the similar process selected to turn the small batch problem into large batch processing, and the tolerance coefficient method is applied to convert the original data into relative data. As a result, an improved multivariate process capability index based on entropy weight theory and fuzzy matter elements is proposed. In conclusion, a product is analyzed for example, thus verifying the practicability and effectiveness of the method.

Key words: multi-variety and small batch, fuzzy matter-element, entropy weight theory, multivariate process capability index (MPCIs)

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