A MONTE CARLO SIMULATION APPROACH FOR SPARE PARTS DEMAND FORECASTING
For a given failure distribution and a given replacement policy, the spare parts demand in a given or random time interval is a random variable. This paper presents a Monte Carlo simulation approach to forecast the spare parts demand. The simulation output is an empiric distribution function of the demand quantity. We discuss the simulation procedures for the cases with multiple identical units, known or unknown initial ages, and fixed and random forecasting interval. The issue to fit the empiric distribution into a theoretic distribution is also presented. A real-world numerical example is included to illustrate the usefulness and appropriateness of the approach.
Inventory management Spare parts Demand forecasting Discrete distribution
R. Jiang Xin Wang
School of Automotive and Mechanical Engineering,Changsha University of Science and Technology,Hunan, Changsha 410076, China
国际会议
北京
英文
767-771
2008-10-27（万方平台首次上网日期，不代表论文的发表时间）