Identifying Downtime Drivers Using SIMLOX Simulations to Rapidly Develop Solutions Improving System and Mission Readiness

Abstract

"In this paper we present a simulation model that directly relates the system results to the individual parts and resources, otherwise known as downtime drivers. Understanding operational downtime drivers and whether they are item- or subsystem-specific is crucial to making strategic decisions for missions and operations. Identifying the drivers in the modeling phase allows for increased preparation and problem-solving to improve mission requirements. While working to solve the issues created by downtime drivers, industry and defense can work together to determine a reasonable solution to overcome the impact an item or subsystem can have on the overall system. This case study describes a scenario where industry and defense have been able to identify downtime drivers for a complicated system and develop a set of reasonable alternatives to address these issues. OPUS10 identifies the initial spares purchase optimization for a given availability requirement. We can then utilize that recommendation in SIMLOX, a Monte Carlo–based simulation tool. Simulation results are often used to identify bottlenecks within the supply chain, spares, and support organization. With the recent software updates to SIMLOX, we can identify downtime drivers. Stakeholders can identify which subsystem(s) or items are causing a system to be down. "