The optimization design of EWMA charts for monitoring environmental performance
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 Taguchis 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.
optimization design ewma charts non-normal data taguchis loss function environment performance