Estimating The Number Of Failures And The Spare Parts Demand - Installed Base Approach

Official URL: https://risc01.sabanciuniv.edu/record=b3401904

This thesis investigates the estimation of failures and the corresponding demand for spare parts using the installed base approach. The installed base refers to the total number of units of a product or system that are currently in use by customers. The usage behavior of the customers in conjunction with the failure rate of a product shapes the future demand for spare parts of a product. We include these important factors in our mathematical model to develop a comprehensive framework for accurately predicting the number of failures that can occur and the resultant demand for spare parts. Accurate estimation of failures and spare parts demand enables better inventory management, optimized maintenance schedules, and improved customer satisfaction. We propose models to estimate the mean, variability, and in general any moments of returned and defective items. In addition, we formulate the relations that give the saturation time of spare parts demand. Knowing when to expect the highest parts demand and how much demand will occur at that time is important for the manufacturer in order to prepare its maintenance facility and staff and stock the necessary spares. We also compute the distribution of spare parts demand by a time point, during a time interval, and after a time till the time that product disappears from the market over the whole life cycle of the product. We can identify the necessary stock level that needs to be kept in the inventory to satisfy the upcoming demand with a certainty level considering the lead time of providing the part. Also, a business can use the information about the distribution of spare parts demand to make a wiser last-time buy order decision. Our models also provide valuable insights by estimating the mean, variance, and covariance of two key factors: the installed base and discarded items. This information is crucial for the manufacturer as it enables them to gauge the success of their product and develop effective strategies to enhance its market performance. Additionally, the data related to discarded items serves as a valuable resource for the manufacturer to meet the demand for spare parts.