• CN:11-2187/TH
  • ISSN:0577-6686

›› 2010, Vol. 46 ›› Issue (2): 14-21.

• 论文 • 上一篇    下一篇

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基于误差传递网络的工序流波动分析

刘道玉;江平宇   

  1. 西安交通大学机械制造系统工程国家重点实验室
  • 发布日期:2010-01-20

Fluctuation Analysis of Process Flow Based on Error Propagation Network

LIU Daoyu;JIANG Pingyu   

  1. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University
  • Published:2010-01-20

摘要: 减少工序的波动水平是提高工序加工质量的关键,在多工序加工过程中,由于工序间存在着复杂的交互影响效应,波动源的有效识别是一个重要问题。针对这一问题,提出一种基于误差传递网络的节点波动效应评价方法,基于线性关系建立工序间波动传递方程,进而构建由零件加工特征、加工要素节点组成工序流误差传递网络,在此基础上,定义节点的波动传递系数,并给出不同节点的波动效应值量化方法,通过考察各节点波动效应值,确定工序流需要优先进行改进的工序及加工要素节点。一个三工序加工过程被用于验证提出方法,结果表明该方法能够识别工序流薄弱工序节点。

关键词: 波动辨识, 工序流, 加工特征, 节点波动效应值, 误差传递网络

Abstract: It is a key issue to reduce process fluctuation for improving machining quality of workpiece. For multistage machining processes, it is difficult to identify the fluctuation sources of process flow due to the complicated interactive effects among different stages. In view of this issue, a fluctuation evaluation and identification method is proposed based on machining error propagation network. A fluctuation propagation equation of process flow is established, and a machining error propagation network is constructed, which consists of machining form feature and machining element nodes. Based on this, fluctuation propagation coefficient is defined, and node state variation risk (NSVR) of different node is measured, and the priority of node can be identified according to its NSVR. A three stage process of a box part is used to verify the proposed method.

Key words: Fluctuation identification, Machining error propagation network, Machining form feature, Node state variation risk(NSVR), Process flow

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