Dynamic Programming Model for Multi-Stage Reliability Growth Planning

Abstract

The development of modern sophisticated system is increasingly concerned with system overall reliability, which makes Reliability Growth Planning (RGP) particularly important. Reliability Growth Planning provides decision makers with accurate and reliable information during the multi-stage product development decision making process. Dynamic programming (DP) is an effective method to multi-stage decision making such as multiple stage reliability growth planning. This paper adopts the advantages of dynamic programming to establish reliability growth planning model and investigates the computational complexity of the algorithms. Insights during reliability growth planning, such as the relationship between the final achievable reliability and the initial parameter settings, the number of stages, and time allocation granularity is studied through an example. It is found that when the number of stages is fixed, the higher level of the time allocation granularity, the larger the final reliability level of reliability growth planning. In the case of a fixed time allocation granularity, there exists an optimal number of stages to maximize the final reliability level.