Addressing the Reliability and Life Cycle Cost Analysis Problem for Technology and System Developers Early in the DoD System Development Process

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Date
2005-12-06
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Virginia Tech
Abstract

Early in the process of developing or upgrading new weapon systems, Department of Defense (DoD) system and technology developers are faced with decisions regarding which technologies are appropriate for inclusion into the conceptual design. To reduce risk and improve decision making, system and technology developers need a capability to assess the impact of technology reliability on the attributable Operating and Support (O&S) cost of the system. Early understanding of the reliability implications of potential technologies on system O&S cost will help make better informed decisions early in the system development timeline, prior to points of design lock-in. Using a Marine Corps case study and a system dynamics simulation model, this thesis examines the nature of the relationship between component reliability and attributable changes in O&S cost. This thesis also develops a potential analysis methodology repeatable for future use. The modeling results indicate that this relationship is best described as exponential decay, meaning that the savings in O&S cost per system mile is proportional for any fixed incremental change in component reliability. We find these results to be insensitive to changes in preventative maintenance policies, maintenance deferment ratios, and component replacement cost. We completed verification and validation using the case study and existing Marine Corps systems, finding good association between the modeling results and the actual system. This analysis is valuable to the system and technology developer by helping to answer the question: "how reliable is reliable enough in terms of O&S cost" when considering technologies with uncertainties in long-term performance.

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Keywords
Early Operating and Support Cost Assessment, Defense Systems, System Dynamics, Modeling & Simulation, Technology Insertion Analysis, System Reliability
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