An intelligent GA-nonparametric DEWMA sign chart for green chain management

In green management, the quality control performs a key factor for chain materials and products in chain productions. Selecting the correct control chart is essential to effectively monitoring process shifts. In particularly, a nonparametric control chart is recommended over a traditional control chart when the quality characteristics of a process are unknown. This paper designs an intelligent genetic algorithm (GA)-nonparametric EWMA sign chart for green chain management by an adaptive GA controller to upgrade green chains satisfactions. In this paper, we extend the nonparametric exponentially weighted moving average (EWMA) sign chart to a double EWMA (DEWMA) sign chart to improve the detection ability in small green process shifts. Simulation studies show that the nonparametric DEWMA sign chart performs better than the EWMA sign chart in detecting small process shifts, but that they perform similarly when detecting large shifts.