Integral inventory control in spare parts networks with capacity restrictions

Integral inventory control of repairable items in service networks can result in a significant gain compared to traditional local control mechanisms, in terms of both efficiency and customer service. Research on quantitative decision support models has yielded various useful results. However, in many of these models, the random components such as demand and lead times are modelled as black boxes.In this thesis, the author focuses on the modelling of the lead times in repair facilities with limited capacities and reasonable repair priority settings. To this end, several kinds of multi-class, multi-server queueing models with different priority settings have been developed. The resultant queueing models are plugged into a well-known spare parts supply model, which usually assumes ample server capacity. The multi-class nature of the queueing models, which means that items with different arrival and service rates share the same queueing process, makes it possible to obtain more natural spare part models and more flexibility in optimisation