The process of maintenance and repairs is one of the processes of the organization whose main task is to maintain and maintain machines in favorable conditions or to restore them from unfavorable conditions to favorable ones. The failure of machinery leads to the loss of equipment availability time and increases the costs of the organization; Therefore, it is always important to improve the performance of machines and, as a result, to improve the net process. The aim of this research is to develop an integrated model of statistical process control and maintenance maintenance, taking into account the inspection delay policy. Since the presented model is part of NP-Hard problems, therefore, genetic meta-heuristic algorithm has been used to solve it. Finally, the data of Sistan water treatment plant have been analyzed to check and validate the presented model. The results of the research showed that the innovative method of genetics can be used as a suitable solution in highly complex civil engineering problems; Therefore, the GA method can respond well in similar problems where the goal is to optimize the cost and achieve the optimal goal in a short time. Also, the results of the investigation of the parameters of the Sistan refinery showed that in the case where the sample size (n) is equal to 7, the control limit parameter (I) is equal to 2.98, the sampling interval (h) is equal to 4.05, the planned monitoring period (T) is equal to 53.78 and the planned period without monitoring (TD) is equal to 8.09, the value of the minimum cost of the model (E(ct)) is equal to 106.85 , According to the offspring of the genetic algorithm, this algorithm can optimize up to 15.26% of maintenance costs in this case study.