Proactive and Efficient Spare Parts Inventory Management Policies Considering Reliability Issues
Spare parts inventory management plays an important role in many industries. They exist to serve the maintenance planning and a good planning can significantly reduce maintenance cost. This thesis developed a series of non-linear programming models to obtain optimal spare parts replenishment policies for failure-based maintenance in a single period. Both single Part Number case and multiple Part Numbers case with a budget constraint are addressed. Compared with traditional forecasting methods which only consider historical data, our proposed inventory policies take into account reliability issues and predict impending demands based on part failure distributions from two perspectives: failure time and failure numbers. Therefore, optimal order quantity and best order time can be found to realize total cost minimization, as well as a systematic inventory optimization.