In continuous production units, lost production costs increase due to break downs, so the economic efficiency of these industries depends on proper preventive maintenance and maintenance policies to increase reliability and reduce equipment operating costs. In these industries, all systems, from the simplest to the most complex, require Scheduled maintenance to reduce the risk of failure. On the other hand, a subject that has already been extensively researched for years is the combined decision of preventive maintenance and safety stock. Most of the models reported in the literature implicitly assume that the company owns the manufacturing facility and in-house maintenance work is done. In this article, however, the acquisition of machinery through leasing is considered. The lessor who operates the machinery is responsible for servicing support under this lease contract. This contributes to the lessor's dispute with the lessee. We suggest a new cooperative and non-cooperative Nash game theory for a production unit under a lease to overcome this conflict. The lessor's goal is to find the optimal scheduling of preventive maintenance actions which need to conduct and lease contract costs, and the lessee's goal is to determine the optimum buffer stock size that requires to be produced and the number of lease contract periods to minimize the overall cost to both sides over the lease period. In this scenario, where the analysis is performed from the lessor's and lessee's viewpoint, a mathematical formulation of game theory is required to model the decision problems. Considering the duration of activities and the cost of inaccessibility as a time-dependent variable are other contributions. As the solution method, the genetic meta-heuristic algorithm is implemented and finally a numerical example is solved to evaluate the algorithm's performance.
