Integrated models for critical spare parts management in asset intensive industries

Spare parts are of key importance for equipment intensive industries –such as Mining, Aeronautic, or Defense– since their role is to efficiently support the operation of critical equipment and enhance system performance, thereby meeting business success. Organizations within such industries face continuous challenges to improve utilization, reduce costs, and manage risks. Miscalculating these decisions might lead to overstress on equipment and associated spare components, thus affecting availability, reliability, and system throughput. Critical spare parts therefore merit complex modeling. However, an asset management perspective –a systemic means of optimally managing resources to ensure sustainable business goals– has not been integrated into every vital decision stage of spares policies. In an effort to include this type of approach, this research has modeled the spares process from selection of the most important resources to supply chain requirements. The general objective of this thesis is to develop an asset management-based framework to optimize the life cycle of critical spare parts by integrating five key decision areas, namely: prioritization, ordering, replacement, maintenance outsourcing, and pool allocation. These areas are crucial to performance excellence for asset intensive firms. The resulting support system is documented by five ISI journal articles dealing with the key decision areas. The methodology is illustrated by an introduction, real-industry case studies, and sequential addressing of aims and contributions for each appended paper. They are summarized as follows. First, Paper I “Throughput centered prioritization of machines in transfer lines” delivers the graphical tool called System Efficiency Influence Diagram, which prioritizes the critical resources for system throughput considering intermediate buffers. Second, Paper II “Critical spare parts ordering decisions using conditional reliability and stochastic lead time” introduces the concept of Condition-Based Service Level to define the spares ordering time at which the system operation is sufficiently reliable to withstand lead time variability. Third, Paper III “Value-based optimization of intervention intervals for critical mining components” shows the influence of business value for accelerating versus postponing the optimal epoch to perform the spares replacement. Fourth, Paper IV “Optimizing maintenance service contracts under imperfect maintenance and a finite time horizon” sets contract conditions for motivating service receivers and external providers