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For capital goods, downtime is expensive. Therefore, system availability is of utmost importance. For example, if a manufacturing system is unavailable, production may stop completely. To guarantee a high availability, typically, a support network is used with both locations close to the installed base and more central locations to serve separate bases. Repair equipment and spare parts need to be located in this multi-echelon repair network. In this thesis, methods are developed to decide for each component whether to discard or repair it upon failure, where to perform repairs, and where to locate (repair) equipment and spare parts. The goal is to find the most cost effective solution that guarantees a target availability of the installed base. The difficulty in finding the optimal solution is that many decisions interact with each other. For example, if a component is repaired at a central location, it makes no sense to repair its subcomponents at a decentralized location. Furthermore, some repairs can only be performed if certain (possibly expensive) equipment is available, while repairing at a central location may lead to long repair lead times, thereby influencing the number of required spare parts. The methods that are developed in this thesis are generic; their applicability is demonstrated in a case study at Thales Nederland

Designing logistics support systems : level of repair analysis and spare parts inventories