Samrad Jafarian-Namin - Department of Industrial Engineering, Faculty of Engineering, Yazd University, Yazd, Iran
Mohammad Saber Fallah Nezhad - Department of Industrial Engineering, Faculty of Engineering, Yazd University, Yazd, Iran
Reza Tavakkoli-Moghaddam - School of Industrial Engineering, College of Engineering University of Tehran, Tehran, Iran
Ali Salmasnia - Department of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Qom, Iran
Mehrdad Mirzabaghi - School of Industrial Engineering, College of Engineering University of Tehran, Tehran, Iran

The survival of producers in the world of competition requires an appropriate plan including statistical process monitoring, inventory control and maintenance policy, which have commonly been studied separately in the literature. While, if their integration gets analyzed, it is possible to achieve more favorable conditions of economic production quantity at a lower cost for the entire system in production processes. In the few studies on their integrations, one of the basic assumptions of monitoring is the independence of data. Nevertheless, in practice, particular patterns of correlation pattern could be extracted by sampling in which independency is violated. As the main objective of thisresearch, an integrated model for determining the optimal parameters of quality, production and maintenance policy in the presence of autocorrelated data is provided for the first time. Eventually, the total cost of the system in the proposed model must be minimized according to the statistical constraint. Due to the complexity of the model, a genetic algorithm is used to obtain optimal decision variables.

Statistical Process Monitoring (SPM), Economic Production, Quantity (EPQ), Maintenance Policy (MP), Autocorrelated, Data, Genetic Algorithm (GA)