Abstract
The performance of any production system is highly dependent on processing equipment that is free of faults and breakdowns. This can be achieved through maintenance planning and statistical quality control. The aim of this research is to develop a model for statistical quality control with an integrated optimization-based maintenance model for multicomponent series systems using an exponentially weighted moving average chart. The optimization model is based on both the preventive and corrective maintenance policies. The developed model is used to find the optimal values of sample size, sample frequency, width of control chart limit in units corresponding to the standard deviation, and interval of preventive maintenance while minimizing the total expected cost of the system per unit time. The study included a case study example to demonstrate its applicability and to analyze the influence of cost parameters on the developed integrated model. Finally, sensitivity analysis was conducted to demonstrate the effectiveness of the proposed model.