Industry need to produce high quality products with appropriate prices to intensify competitive ability in markets has led to increasing use of prevantive maintanance policies. Establishing periodic prevantive maintanance are the most effective procedure to reduce failures. In this research, mathematical programming and MINLP models are used in order to prepare prevantive and maintanance timing programs matched with manufacturing programs. An industrial environment with a lot of machineries and various equipments is considered. An specified demand in an specified period of time e.g. a year is considered too. All of the demands must be supplied by the all of machineries and equipments. Answering the demand is in need of a scheduling of the manufacturing programs to operate by the machineries. And that is why the timing program of equipments should be prepared. Age of the equipments are specified and various. Manufacturing operations can be programmed on different equipments with different ages in which they will have different prevantive and maintanance costs. Actually prevantive and maintanance costs are directly related to their age. The aim of this study is to provide a mathematical model to determine optimal intervals for preventative maintenance and preparation operation scheduling on equipment , and minimizing the maintenance total cost as well. Preparation of the production scheduling is not a new topic, but what is addressed in this study, preparation of the equipment maintenance-scheduling operations and focusing on the cost of maintenance. In this study common methods for scheduling operations will not be used and these scheduling operations is done based on minimizing maintenance costs. Also in the allocation of equipment operation parameters of the equipment due to age. To solve the model on small scall the GAMS software is used. And scale and large scale development on genetic algorithm and particle aggregation which has errors are acceptable.