The architecture of statistical process monitoring system based on both input and output properties

Yasuhiko Takemoto, Tetsuji Yamaguchi, Ikuo Arizono

Research output: Contribution to journalArticle

Abstract

We have contrived these control charts in order to detect the out-of-control state of the process. The assignable causes of the out-of-control state consist of the incompleteness of materials supplied from the previous process or in the process operation at the present process. In quality management, it is important to detect the out-of-control state and to remove the factor by which it is caused. Although conventional control charts, in which the state of the process is judged only on output data of products from the present process, are useful statistical tools for detecting the out-of-control state, the procedure for identifying the factor that causes the out-of-control state has not been actively contrived. By the way, because there is a type II error in monitoring the previous process, it is clear that the incompleteness of materials can not be excluded from the assignable cause of the out-of-control state in the present process. Therefore, in this study, we consider the active use of the input data of materials provided in the present process in addition to the output data of products obtained from the present process, in order to both improve the detection of the out-of-control state of the present process and specify the factor of the assignable cause. First, we propose the new statistical procedure for monitoring the process state by using both the output data from the present process and the input data into the present process. Next, when the out-of-control state of the present process is detected by the proposed monitoring procedure, we consider the procedure for specifying the factor of the assignable cause of the out-of-control state. We also verify the effectiveness of the proposed monitoring system with both the judgment of the process state and the recognition of the assignable cause through numerical simulations. Further, we consider the economical operation of the proposed monitoring system based on the loss of the quality.

Original languageEnglish
Pages (from-to)265-273
Number of pages9
JournalJournal of Japan Industrial Management Association
Volume56
Issue number4
Publication statusPublished - 2005
Externally publishedYes

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Keywords

  • AIC (Akaike Information Criterion)
  • Assignable causes
  • Control chart
  • Kullback-Leibler information
  • Multivariate control chart
  • Taguchi's loss function

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Engineering (miscellaneous)

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