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A Cause-Selecting Control Chart Method for Monitoring and Diagnosing Dependent Manufacturing Process Stages

机译:监视和诊断相关制造过程阶段的原因选择控制图方法

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摘要

Many industrial products are normally processed through multiple manufacturing process stages before it becomes a final product.Statistical process control techniques often utilize standard Shewhart control charts to monitor these process stages.If the process stages are independent,this is a meaningful procedure.However,they are not independent in many manufacturing scenarios.The standard Shewhart control charts can not provide the information to determine which process stage or group of process stages has caused the problems (i.e.,standard Shewhart control charts could not diagnose dependent manufacturing process stages).This study proposes a selective neural network ensemble-based cause-selecting system of control charts to monitor these process stages and distinguish incoming quality problems and problems in the current stage of a manufacturing process.Numerical results show that the proposed method is an improvement over the use of separate Shewhart control chart for each of dependent process stages,and even ordinary quality practitioners who lack of expertise in theoretical analysis can implement regression estimation and neural computing readily.
机译:许多工业产品通常要经过多个制造过程才能加工成最终产品。统计过程控制技术通常使用标准的Shewhart控制图监视这些过程阶段。如果过程阶段是独立的,则这是有意义的过程。在许多制造场景中并不是独立的。标准的Shewhart控制图无法提供信息来确定是哪个过程阶段或一组过程阶段引起了问题(即,标准的Shewhart控制图无法诊断相关的制造过程阶段)。提出了一种基于选择性神经网络集成的控制图原因选择系统,以监控这些过程阶段并区分制造过程中当前阶段出现的质量问题和问题。数值结果表明,所提出的方法是对使用过程的改进。每个部门的单独Shewhart控制图在整个过程中,甚至是缺乏理论分析专业知识的普通质量从业人员,都可以轻松实现回归估计和神经计算。

著录项

  • 来源
    《南京航空航天大学学报(英文版)》 |2018年第4期|671-682|共12页
  • 作者单位

    The 28th Research Institute of China Electronics Technology Group Corporation, Nanjing 210007, P.R.China;

    College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P.R.China;

    College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P.R.China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 TH165.3;
  • 关键词

  • 入库时间 2022-08-19 04:26:03
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