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The optimization design of EWMA charts for monitoring environmental performance

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Abstract

Aimed at reducing the loss in the process of controlling environmental pollution, this paper proposes an optimization design of EWMA charts for monitoring and evaluating the environmental performance. By using Rayleigh distribution to approximate probability distribution of the random process with mean shifts, the parameters of the EWMA charts for non-normal data will be determined such that the overall mean of Taguchi’s loss function (ML) is minimized. Based on these optimal parameters, ML-EWMA charts are constructed for monitoring environmental pollution processes. Then further analysis has been performed to compare the optimization of the ML-EWMA charts and the conventional EWMA charts in terms of their expected losses, the results of which show that ML-EWMA charts in this paper are significantly superior to the conventional EWMA charts as far as the overall loss of ML is concerned. Finally, a numeric example is illustrated to show the application of optimization design of EWMA charts for non-normal environmental data. The optimization design method proposed in this paper can reduce the loss greatly in environmental control and the general idea can be applied in other control charts.

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Acknowledgements

This research was supported by the National Science Foundation of China under grants 71272207, U1204702 and 71002073, Aeronautic Science Foundation of China under grant 2012ZG55024, Foundation for Humanities and Science by the Ministry of Education under grants 10yjc630326 and 11yjc630013.

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Correspondence to Li Xue.

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Liu, Ym., Xue, L. The optimization design of EWMA charts for monitoring environmental performance. Ann Oper Res 228, 113–124 (2015). https://doi.org/10.1007/s10479-012-1239-6

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