计算机集成制造系统 ›› 2022, Vol. 28 ›› Issue (3): 812-825.DOI: 10.13196/j.cims.2022.03.015

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面向多品种小批量制造过程的关键工序识别与聚类分析方法

陈克强,刘伟军+,姜兴宇,徐思迪,王永,刘傲   

  1. 沈阳工业大学机械工程学院
  • 出版日期:2022-03-31 发布日期:2022-03-23
  • 基金资助:
    辽宁省“兴辽英才计划”科技创新领军人才资助项目(XLYC1802038);辽宁省“兴辽英才计划”青年拔尖人才资助项目(XLYC1807211);沈阳市中青年科技创新人才资助项目(RC190148)。

Method of key process identification and cluster analysis in multi-variety and small-batch manufacturing process

  • Online:2022-03-31 Published:2022-03-23
  • Supported by:
    Project supported by the Innovation Talents Promotion Plan of Liaoning Provincial Revitalization Talent Program,China(No.XLYC1802038),the Top Young Innovative Talents Program of Liaoning Provincial Revitalization Talent Program,China(No.XLYC1807211),and  the Top Young and Middle-aged Innovative Talents Program of Shenyang City,China(No.RC190148).

摘要: 关键工序的有效识别及其质量特征数据不足问题是多品种小批量制造过程质量控制的关键。由此,提出一种基于清晰集与灰色关联分析的多品种小批量制造过程关键工序识别方法,综合考虑加工难度、成本、客户(VOC)等因素,构建多品种小批量质量关键工序的识别模型;在此基础上,基于层次聚类分析法对各品种的关键工序进行聚类分析,进而确定分辨率的选择方案,扩大质量特征数据样本量,解决关键工序的质量特征数据不足的问题。以某航天复杂构件制造企业的各品种产品制造工艺流程为例,应用所提方法对其关键工序进行识别与聚类分析,结果验证了所提模型与方法的有效性与可行性。

关键词: 多品种小批量, 关键工序, 清晰集, 层次聚类分析法, 航天复杂构件

Abstract: The effective identification of key processes and the lack of quality characteristic data are the keys to quality control of multi-variety and small-batch manufacturing processes.A key process identification method for multi-variety and small-batch manufacturing process based on clear set and gray correlation analysis was proposed,which comprehensively considered factors such as processing difficulty,cost and Vioce of Customer (VOC).On this basis,the key processes of each variety were analyzed based on the hierarchical clustering analysis method,and then the resolution selection scheme was determined,so as to expand the sample size of quality feature data and solve the problem of insufficient quality feature data of key processes.Taking the manufacturing process flow of various products of an aerospace complex component manufacturing enterprise as an example,the proposed method was used to identify and cluster the key processes,and the analysis results verified the effectiveness and feasibility of the proposed models and methods.

Key words: multi-variety and small-batch, key processes, clear set, hierarchical clustering analysis, aerospace complex component

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