Integrating SPC and EPC for multivariate autocorrelated process

Lee-Ing Tong*, Chien Hui Yang, Cheng Yi Huang, Cheng Chi Shou

*Corresponding author for this work

Research output: Contribution to journalConference article

3 Scopus citations

Abstract

Statistical process control (SPC) is a widely employed quality control method in industry. SPC is mainly designed for monitoring single quality characteristic. However, as the design of a product/process becomes complex, a process usually has multiple quality characteristics related to it. These characteristics must be monitored by multivariate SPC. When the autocorrelation is present in the process data, the traditional SPC may mislead the results. Hence, the autocorrelated data must be treated to eliminate the autocorrelation effect before employing SPC to detect the assignable causes. Besides, chance causes also have impact on the processes. When the process is out of control but no assignable cause is found, it can be adjusted by employing engineering process control (EPC). However, only using EPC to adjust the process may make inappropriate adjustments due to external disturbances or assignable causes. This study presents an integrated SPC and EPC procedure for multivariate autocorrelated process. The SPC procedure constructs a predicting model using group method of data handling (GMDH), which can transfer the autocorrelated data into uncorrelated data. Then, the Hotelling's T2 and multivariate cumulative sum control charts are constructed to monitor the process. The EPC procedure constructs a controller utilizing data mining technique to adjust the multiple quality characteristics to their target values. Industry can employ this procedure to monitor and adjust the multivariate autocorrelated process.

Original languageEnglish
Pages (from-to)692-696
Number of pages5
JournalProceedings of the International Conference on Electronic Business (ICEB)
StatePublished - 1 Dec 2005
Event5th International Conference on Electronic Business, ICEB 2005 - Hong Kong, Hong Kong
Duration: 5 Dec 20059 Dec 2005

Keywords

  • Autocorrelation
  • Engineering process control
  • Group method of data handling
  • Hotelling's T control chart
  • Multivariate cumulative sum control chart
  • Multivariate process
  • Statistical process control

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