Moving average control chart under neutrosophic statistics

Continuous monitoring and improving the production process is a crucial step for the entrepreneur to maintain its position in the market. A successful process monitoring scheme depends upon the specification of the quality being monitored. In this paper, the monitoring of temperature is addressed using the specification of moving average under uncertainty. We determined the coefficients of the proposed chart utilizing the Monte Carlo simulation for a different measure of indeterminacy. The efficiency of the proposed chart has been evaluated by determining the average run lengths using several shift values. A real example of weather-related situation is studied for the practical adoption of the given technique. A comparison study shows that the proposed chart outperforms the existing chart in monitoring temperature-related data.