Multi-objective optimization design of EWMA chart with time-varying parameters for multiple assignable shifts

WANG Haiyu

Systems Engineering - Theory & Practice ›› 2021, Vol. 41 ›› Issue (11) : 3031-3042.

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Systems Engineering - Theory & Practice ›› 2021, Vol. 41 ›› Issue (11) : 3031-3042. DOI: 10.12011/SETP2020-0947

Multi-objective optimization design of EWMA chart with time-varying parameters for multiple assignable shifts

  • WANG Haiyu
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Abstract

In order to improve the efficiency of process quality monitoring and reduce the cost of quality control, aiming at many kinds of shifts that may occur in the process, this paper constructs an EWMA chart with time-varying parameters, which dynamically adjusts the parameters of control chart according to process sampling. And Markov chain method is used to calculate the APL value, which is used to evaluate the monitoring efficiency of control chart. According to the dispersion of multiple assignable shifts to be monitored, the calculation methods of quality control cost for a certain range of shifts and multiple separate shifts are given, and the multi-objective optimization design model of EWMA chart with time-varying parameters is constructed with the APL and unit product quality cost as the objective functions. Two numerical examples are used to illustrate the application of this optimization design method. Finally, the optimization design method is compared with several EWMA charts and multiple assignable shifts control charts. The results show that the multi-objective optimization design proposed in this paper is significantly better than the existing EWMA charts and multiple assignable shifts control charts.

Key words

statistical process control (SPC) / multiple assignable shifts / exponentially weighted moving average (EWMA) chart / multi-objective optimization

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WANG Haiyu. Multi-objective optimization design of EWMA chart with time-varying parameters for multiple assignable shifts. Systems Engineering - Theory & Practice, 2021, 41(11): 3031-3042 https://doi.org/10.12011/SETP2020-0947

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Funding

National Natural Science Foundation of China (71672209, U1904211)

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