AEWMA t Control Chart for Short Production Runs

Chang Zhiyuan () and Sun Jinsheng ()
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Chang Zhiyuan: School of Automation, Nanjing University of Science and Technology, Nanjing210064, China
Sun Jinsheng: School of Automation, Nanjing University of Science and Technology, Nanjing210064, China

Journal of Systems Science and Information, 2017, vol. 4, issue 5, 444-459

Abstract: Owing to the limited number of inspections during a short run process, it is impossible to get the correct estimate of the population mean and standard deviation during Phase I implementation of control chart. The t control chart proposed recently can overcome this problem. The EWMA t control chart has been proposed to monitor the process mean, but a single EWMA t control chart cannot perform well for small and large shifts simultaneously, which is known as the “inertia problem”. The adaptive varying smoothing parameter EWMA (AEWMA) control chart can overcome the inertia problem. In this paper, the AEWMA t control chart for short run process is proposed. The truncated average run length and the probability of trigger a signal are adopted to test the performance of short run AEWMA t chart. Based on the investigation of the joint effect of control chart parameters on the performance of AEWMA t chart, a new optimization algorithm is proposed for statistical design of the AEWMA control chart. Simulations are performed for perfect and imperfect setup conditions, the results show that the AEWMA t control chart performs better than the EWMA t control chart.

Keywords: AEWMA control chart; t chart; short run; TARL; Markov chain (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:4:y:2017:i:5:p:444-459:n:5

DOI: 10.21078/JSSI-2016-444-16

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