TY - JOUR
T1 - Maximization of a percentile life of a series system through component redundancy allocation
AU - Prasad, V. Rajendra
AU - Kuo, Way
AU - Kim, Kyungmee O.
N1 - The publication is also published in SpringerLink.
PY - 2001
Y1 - 2001
N2 - In a redundancy allocation problem, maximization of system reliability for a specified mission time has been thoroughly studied. Instead, we consider the optimal redundancy which maximizes a percentile life of a series system without violating a cost constraint. A percentile life is the maximum mission time for which system reliability meets at least a specific value. The proposed measure has advantages over regular reliability maximization in fixing warranties or when a system has no clear mission time. Previously, the proposed problem was solved by a heuristic or a genetic algorithm. Because of the infeasibility of finding a close form of percentile life in the redundancy level, we now develop a lexicographic search methodology to obtain an exact optimal solution. A transformed problem is first considered to get an upper bound, which is iteratively used to reduce search space. When any two stages of a system have a precedence relationship based on the cost and lifetime then the search space can be further reduced. The algorithm is general for any continuous increasing lifetime distributions, and can be easily extended for the additional weight and volume constraints. © 2001, Taylor & Francis Group, LLC.
AB - In a redundancy allocation problem, maximization of system reliability for a specified mission time has been thoroughly studied. Instead, we consider the optimal redundancy which maximizes a percentile life of a series system without violating a cost constraint. A percentile life is the maximum mission time for which system reliability meets at least a specific value. The proposed measure has advantages over regular reliability maximization in fixing warranties or when a system has no clear mission time. Previously, the proposed problem was solved by a heuristic or a genetic algorithm. Because of the infeasibility of finding a close form of percentile life in the redundancy level, we now develop a lexicographic search methodology to obtain an exact optimal solution. A transformed problem is first considered to get an upper bound, which is iteratively used to reduce search space. When any two stages of a system have a precedence relationship based on the cost and lifetime then the search space can be further reduced. The algorithm is general for any continuous increasing lifetime distributions, and can be easily extended for the additional weight and volume constraints. © 2001, Taylor & Francis Group, LLC.
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U2 - 10.1080/07408170108936897
DO - 10.1080/07408170108936897
M3 - RGC 21 - Publication in refereed journal
SN - 2472-5854
VL - 33
SP - 1071
EP - 1079
JO - IIE Transactions (Institute of Industrial Engineers)
JF - IIE Transactions (Institute of Industrial Engineers)
IS - 12
ER -