| description abstract | Longterm support of legacy electronic systems is challenging due to mismatches between the system support life and the procurement lives of the systems’ constituent components. Legacy electronic systems that are used in safety, mission, and infrastructure critical applications that must be supported for 20+ yr are threatened with diminishing manufacturing sources and material shortages (DMSMS)type obsolescence, and their effective system support lives may be governed by existing nonreplenishable inventories of spare parts. This paper describes the development of the end of maintenance (EOM) model, which uses a stochastic discreteevent simulation that follows the life history of the population of parts in a system using timetofailure distributions and other forecasted demands. The model determines the support life of the system based on existing inventories of spare parts and cards, and optionally harvesting parts from existing cards to extend the support life of the system. The model includes: part inventory degradation, periodic inventory inspections, and design refresh planning for selected cards. A case study using a real legacy system comprised of 117,000 instances of 70 unique cards and 4.5 أ— 106 unique parts is presented. The case study was used to evaluate the support life of a system with various future failure assumptions, including with and without the use of part harvesting. The case study also includes sensitivity analyses for selected design refreshes to maximize potential system lifecycle capabilities, and optional design refresh planning required to sustain the system to a specific date. | |
