Robust economic and economic-statistical design of EWMA control chart

Uncertainty in the cost and process parameters is very common in practice. In this paper, we develop a scenario-based robust economic and economic-statistical design of exponentially weighted moving average control chart to account for economic and statistical criteria as well as the uncertainty. For this purpose, we use Lorenzen and Vance cost function for economic and economic-statistical design of an exponentially weighted moving average control chart in the real applications. Absolute robustness criterion which minimizes the worst-case scenario and also robust deviation which minimizes the deviation from the optimal solutions are applied to explore the robust approach for robust design of the exponentially weighted moving average control chart. The optimization models are solved by using the genetic algorithm. The performance of the proposed methods is illustrated through two numerical examples. Finally, the application of the proposed methods is illustrated in a real manufacturing case in the tile production industry.