NDLI: Integrating EPC and SPC for MIMO system

Content Provider	IEEE Xplore Digital Library
Author	Ling Yang Shey-Huei Sheu
Copyright Year	2005
Description	Author affiliation: Dept. of Ind. Eng. & Manage., St. John's Univ., Taipei, Taiwan (Ling Yang)
Abstract	In this paper, using multivariate engineering process control (MEPC) alone is compared with using MEPC coupled with multivariate statistical process control (MSPC). MEPC and MSPC are two strategies for quality improvement that have developed independently. MEPC is to minimize variability by adjusting some manipulative process variables to keep the process output on the target vector. MSPC is to reduce variability by monitoring and eliminating assignable causes of variation. The simulation is used to evaluate the average run lengths and the averages of the performance measure. The simulation results show that use of both MEPC and MSPC can always outperform the use of either alone. Especially in detecting small sustained shifts of the mean vector, combining MEPC with the multivariate generally weighted moving average (MEPC/MGWMA) chart is more sensitive than MEPC/multivariate exponentially weighted moving average (MEPC/MEWMA) chart and MEPC/Hotelling multivariate chart. An example of the application is also given.
Starting Page	127
Ending Page	132
File Size	250456
Page Count	6
File Format	PDF
ISBN	0780392981
DOI	10.1109/ICSMC.2005.1571133
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	MIMO Process control Control charts Monitoring Technology management Engineering management Vectors Industrial engineering Electrical equipment industry Industrial control GWMA Control chart multivariate engineering process control statistical process control EWMA
Content Type	Text
Resource Type	Article

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