Cold vs. hot standby mission operation cost minimization for 1-out-of-N systems

It is well recognized that using the hot standby redundancy provides fast restoration in the case of failures. However the redundant elements are exposed to working stresses before they are used, which reduces the overall system reliability. Moreover, the cost of maintaining the hot redundant elements in the operational state is usually much greater than the cost of keeping them in the cold standby mode. Therefore, there exists a tradeoff between the cost of losses associated with the restoration delays and the operation cost of standby elements. Such a trade-off can be obtained by designing both hot and cold redundancy types into the same system. Thus a new optimization problem arises for the standby system design. The problem, referred to in this work as optimal standby element distributing and sequencing problem (SE-DSP) is to distribute a fixed set of elements between cold and hot standby groups and select the element initiation sequence so as to minimize the expected mission operation cost of the system while providing a desired level of system reliability. This paper first formulates and solves the SE-DSP problem for 1-out-of-N: G heterogeneous non-repairable standby systems. A numerical method is proposed for evaluating the system reliability and expected mission cost simultaneously. This method is based on discrete approximation of time-to-failure distributions of the system elements. A genetic algorithm is used as an optimization tool for solving the formulated optimization problem. Examples are given to illustrate the considered problem and the proposed solution methodology.

[1]  David W. Coit,et al.  Maximization of System Reliability with a Choice of Redundancy Strategies , 2003 .

[2]  A. Saidane,et al.  Optimal Reliability Design: Fundamentals and Applications , 2001 .

[3]  Gregory Levitin Genetic algorithms in reliability engineering , 2006, Reliab. Eng. Syst. Saf..

[4]  J. Onishi,et al.  Solving the Redundancy Allocation Problem With a Mix of Components Using the Improved Surrogate Constraint Method , 2007, IEEE Transactions on Reliability.

[5]  Ta-Cheng Chen,et al.  Immune algorithms-based approach for redundant reliability problems with multiple component choices , 2005, Comput. Ind..

[6]  Mitsuo Gen,et al.  Soft computing approach for reliability optimization: State-of-the-art survey , 2006, Reliab. Eng. Syst. Saf..

[7]  Nam Kee Lee,et al.  System Reliability Allocation and a Computational Algorithm , 1968 .

[8]  W. Weibull A Statistical Distribution Function of Wide Applicability , 1951 .

[9]  Alice E. Smith,et al.  An ant colony optimization algorithm for the redundancy allocation problem (RAP) , 2004, IEEE Transactions on Reliability.

[10]  Amir Abbas Najafi,et al.  A bi-objective model to optimize reliability and cost of system with a choice of redundancy strategies , 2012, Comput. Ind. Eng..

[11]  Gregory Levitin,et al.  Recursive Algorithm for Reliability Evaluation of Non-Repairable Phased Mission Systems With Binary Elements , 2012, IEEE Transactions on Reliability.

[12]  Juan Eloy Ruiz-Castro,et al.  A complex discrete warm standby system with loss of units , 2012, Eur. J. Oper. Res..

[13]  L. Darrell Whitley,et al.  The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best , 1989, ICGA.

[14]  D. Coit Cold-standby redundancy optimization for nonrepairable systems , 2001 .

[15]  Gregory Levitin,et al.  Optimal sequencing of warm standby elements , 2013, Comput. Ind. Eng..

[16]  Gregory Levitin,et al.  Computational Intelligence in Reliability Engineering: Evolutionary Techniques in Reliability Analysis and Optimization , 2006, Studies in Computational Intelligence.

[17]  David W. Coit,et al.  System reliability optimization with k-out-of-n subsystems and changing k , 2011, The Proceedings of 2011 9th International Conference on Reliability, Maintainability and Safety.

[18]  Gregory Levitin,et al.  Sequencing Optimization in k-out-of-n Cold-Standby Systems Considering Mission Cost , 2013, Int. J. Gen. Syst..

[19]  Peng Zhao,et al.  Optimal allocation of redundancies in series systems , 2012, Eur. J. Oper. Res..

[20]  Hoang Pham,et al.  Reliability Characteristics of k-out-of-n Warm Standby Systems , 2012, IEEE Trans. Reliab..

[21]  Vanderlei da Costa Bueno,et al.  Active redundancy allocation for a k , 2007, Eur. J. Oper. Res..

[22]  Way Kuo,et al.  Recent Advances in Optimal Reliability Allocation , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[23]  Mohammad Modarres,et al.  Reliability engineering and risk analysis : a practical guide , 2016 .

[24]  Eric R. Ziegel,et al.  System Reliability Theory: Models, Statistical Methods, and Applications , 2004, Technometrics.

[25]  George Kokolakis,et al.  Reliability analysis of a two-unit general parallel system with (n-2) warm standbys , 2010, Eur. J. Oper. Res..

[26]  Jason Brown,et al.  Reliability: Probabilistic Models and Statistical Methods , 1996 .

[27]  David W. Coit,et al.  Reliability optimization of series-parallel systems using a genetic algorithm , 1996, IEEE Trans. Reliab..

[28]  Gregory Levitin Optimal Structure of Multi-State Systems With Uncovered Failures , 2008, IEEE Transactions on Reliability.

[29]  Salvatore J. Bavuso,et al.  Dynamic fault-tree models for fault-tolerant computer systems , 1992 .

[30]  Ming J. Zuo,et al.  O(kn) Algorithms for Analyzing Repairable and Non-repairable k-out-of-n:G Systems , 2008 .

[31]  Jean-Jacques Lesage,et al.  Dynamic fault tree analysis based on the structure function , 2011, 2011 Proceedings - Annual Reliability and Maintainability Symposium.

[32]  K. Misra,et al.  An efficient algorithm to solve integer-programming problems arising in system-reliability design , 1991 .

[33]  Gregory Levitin,et al.  Computational Intelligence in Reliability Engineering , 2007 .

[34]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[35]  Barry W. Johnson Design & analysis of fault tolerant digital systems , 1988 .

[36]  Baoding Liu,et al.  Redundancy optimization problems with uncertainty of combining randomness and fuzziness , 2004, Eur. J. Oper. Res..