Redundancy allocation to maximize a lower percentile of the system time-to-failure distribution

An algorithm is presented which solves the redundancy-allocation problem when the objective is to maximize a lower percentile of the system time-to-failure distribution. The algorithm uses a genetic algorithm to search the prospective solution-space and a bisection search as a function evaluator. Previously, the problem has most of ten been formulated to maximize system reliability. For many engineering-design problems, this new formulation is more appropriate because there is often no clearly defined mission time on which to base component & system reliability. Additionally, most system designers & users are risk-averse, and maximization of a lower percentile of the system time-to-failure distribution is a more conservative (less risky) strategy compared to maximization of the mean or median time-to-failure. Results from over 60 examples clearly indicate that the preferred system design is sensitive to the user's perceived risk. We infer from these results that engineering-design decisions need to consider risk explicitly, and use of mean time-to-failure as a singular measure of product integrity is insufficient. Similarly, the use of system reliability as the principal performance measure is unwise unless mission time is clearly defined.