<![CDATA[Preventive maintainance activities are very important for manufacturing industries in order to maintain lifetime of their components/machines and to improve their performances. This research determines preventive maintainance schedules which minimize total cost and maximize reliability of components/machines. Some methods are already developed to obtain the schedule, exact method for example, has been used for many years. However this method having a drawback in the optimization process, in particular is model complexity, time consuming, and may lead to produce unfeasible solutions. Therefore, to overcome the problems, this research use another possible method namely Steady State Genetic Algorithm (SSGA). This research uses fitness function that is depend on Required Reliability which is stated by the company.In this research, SSGA is used to solve the problem of optimizationing in determining preventive maintainace schedule. This method was implemented to determine preventive maintainace schedule of Freeze Drying belongs to Pindad Cooperation. In this case, SSGA involed population size of 2,000 becauseit produces small variance solution and genetic cycle of 500 which produce convergent values based both on cost and reliability. According to the schedule, if the manufacturer would like to obtain machine reliability of60%, then there are not any maintaince avctivites requred during the period of 15 months. In addition, ifthe reliabilityof 80% required, then the company should perform replacement action on the first month and the tenth month. The company should alse perform maintainance activity on the fourth month with cost needed to do the actions is Rp 784,450. This schedule produces reliability for the machine of 68.71%.]]>
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