Product support and spare parts considering system reliability and operating environment

Abstract: The required spare parts planning for a system/machine is an integral part of the product support strategy. The number of required spare parts can be effectively estimated on the basis of the product reliability characteristics. The reliability characteristics of an existing machine/system are influenced not only by the operating time, but also by factors such as the environmental parameters (e.g. dust, humidity, temperature, moisture, etc.), which can degrade or improve the reliability. In the product life cycle, for determining the accurate spare parts needs and for minimizing the machine life cycle cost, consideration of these factors is useful. Identification of the effects of operating environment factors (as covariates) on the reliability may help in the prediction and calculation of the required spare parts for a system under given operating conditions, which constitutes the research problem studied in this thesis. The Proportional Hazard Model (PHM) method is used for estimation of the hazard (failure) rate of components under the effect of covariates. In this research an approach has been developed to forecast and estimate accurately the spare parts requirements and to create rational part ordering strategies. Subsequently, a model considering environmental factors is developed to forecast and estimate the required number of spare parts within a specific period of the product life cycle. This thesis only discusses non- repairable components (changeable/service parts), which must be replaced after failure. In addition, the existing method for calculating the number of spare parts on the basis of the reliability characteristics, without consideration of covariates, is modified to arrive at the optimum spare parts requirement. To test the model, case studies concerning spare parts planning based on the reliability characteristics of parts and with/without considering the operating environment have been carried out. The results show clearly the differences between the consumption patterns for spare parts with and without taking into account the effects of covariates in the estimation. The final discussion treats spare parts logistics and inventory management. In this work an attempt is made to minimize the inventory cost and consequently the product life cycle cost. Two models for ordering, purchasing and storing spare parts are discussed in connection with the inventory management.