上海交通大学学报

上海交通大学学报（自然版）

• 机械工程 • 上一篇    下一篇

控制批量零件加工过程偏差源的多元指数加权移动平均法

李斯克，苗瑞，赵言正，江志斌   

  1. （上海交通大学 机械与动力工程学院，上海 200240）
  • 收稿日期:2009-08-12 修回日期:1900-01-01 出版日期:2010-04-29 发布日期:2010-04-29

Multivariate Exponentially Weighted Moving Average Control of Error Sources in Batch Production of Parts

LI Sike,MIAO Rui,ZHAO Yanzheng，JIANG Zhibin   

  1. (School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2009-08-12 Revised:1900-01-01 Online:2010-04-29 Published:2010-04-29

摘要： 为了监控批量零件加工尺寸偏差的时域属性，在分析了单件零件加工尺寸偏差状态空间模型的基础上，给出了零件加工尺寸偏差与偏差源的空间关系，并提出了控制批量零件加工尺寸偏差源的多元指数加权移动平均（MEWMA）法.以批量零件加工过程偏差源为输入变量，通过仿真分析零件加工过程，比较了在偏差源阶跃型、奇异值型以及趋势型异常模式下面向偏差源的MEWMA法与面向偏差的休哈特法的统计控制.结果表明，所提出的MEWMA法具有有效性和可行性.

关键词: 尺寸偏差, 传播模型, 偏差源, 多元指数加权移动平均法

Abstract: To statistically control the crosscorrelation of part dimension errors in batch production, spatial relationship between part dimensional features and error sources was established based on analysis of part dimension error and its propagation model. Multivariate exponentially weighted moving average (MEWMA) was adopted to control error sources in batch production of parts, and a method to control part dimension error in batch production through statistical control of error resources which are taken as inputs was proposed. Efficiency and reliability of this model were verified by simulation analysis based on comparison of MEWMA control of error sources and Shewart control of dimension deviations in step abnormal pattern, singular value abnormal pattern and trend abnormal pattern of error sources.

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