The time for cooling down and dismantling happens very fast so that spare parts have to be already available prior to the shutdown to avoid excessive downtime due to spare parts unavailability. This condition is common for most engines including machines in manufacturing plants, airplanes engines, ship engines, automobile engines, or heavy equipment in mining. However, this condition does not apply for gas turbines. For gas turbines, cooling down and dismantling are taking a few days and even more than 1 week. This distinctive characteristic has not been studied before. So, an integration model of spare parts inventory and preventive maintenance is proposed. The time factor of engine cooling down and dismantling will be taken into account by this proposed model. Spare parts will arrive after cooling down and dismantling period is finished using just-in-time method. The basic and proposed model are based on the case study from a power generation company in Indonesia. Discrete-event simulations (DES) are carried out using the company's historical data. The results of the DES simulation and data processing with formulas and commercial data are optimized by linear programming methods and response surface methodology (RSM). By incorporating the stochastic characteristic generated by the variations in the duration of cooling down & dismantling, the duration of assembling, and the duration of parts delivery, the application of the proposed model can reduce the duration of spare part inventory in the warehouse which will result to lower storage cost so that it can lead to an increase in the company's profit.
Keywords: integration, model, spare, parts, maintenance, discrete-event, simulation, cooling down, dismantling