NDLI: Allocation of extra components to ki-out-of-mi subsystems using the NPI method

Content Provider	IEEE Xplore Digital Library
Author	Khuhro, Z.-u.-A. Naureen, F. Salhi, A.
Copyright Year	2009
Description	Author affiliation: Department of Mathematical Sciences, University of Essex, Colchester, CO4 3SQ, UK (Khuhro, Z.-u.-A.; Naureen, F.; Salhi, A.)
Abstract	The allocation of components to systems remains a challenge due to the components success and failure rate which is unpredictable to design engineers. Optimal algorithms often assume a restricted class for the allocation and yet still require a high-degree polynomial time complexity. Heuristic methods may be time-efficient but they do not guarantee optimality of the allocation. This paper introduces a new and efficient model of a system consisting of ki-out-of-mi subsystems for allocation of extra components. This model is more general than the traditional k-out-of-n one. This system which consists of subsystem i (i = 1, 2, …, x) is working if at least ki(out of mi) components are working. All subsystems are independent and the components within subsystem i (i = 1, 2, …, x) are exchangeable. Components exchangeable with those of each subsystem have been tested. For subsystem i, ni components have been tested for faults and none were discovered in si of these ni components. We assume zero-failure testing, that is, we are assuming that none of the components tested is faulty so si = ni, i = 1, 2, …, x. We are using lower and upper probability that a system consisting of x independent ki-out-of-mi subsystems works. This allocation problem dealt with in this paper can be categorised as either to which subsystem the expected number of extra components should be allocated subject to achieving maximum reliability (Lower probability) of the system consisting subsystems, so si = ni, i = 1, 2, …, x. The resulting component allocation problems are too complicated to be solved by traditional approaches; therefore, the Nonparametric Predictive Inference (NPI) method is used to solve them. These results show that NPI is a powerful tool for solving these kinds of problems which are helpful for design engineers to make optimal decisions. The paper also includes suggestions for further research.
Starting Page	1
Ending Page	6
File Size	168479
Page Count	6
File Format	PDF
ISBN	9781424433131
DOI	10.1109/IC4.2009.4909211
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-02-17
Publisher Place	Pakistan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	zero-failure testing independent subsystems exchangeable components lower and upper probability NPI Software performance reliability Pareto optimization Reliability engineering Mathematics Computer science Design engineering Polynomials Power system reliability Testing Power engineering and energy
Content Type	Text
Resource Type	Article

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