Recent Advances in Optimal Reliability Allocation

Kuo, Way; Wan, Rui

doi:10.1007/978-3-540-37368-1_1

Cited by 79 publications

(76 citation statements)

References 116 publications

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“…Nevertheless, our approach differs because it is based on a different exact formula. Regarding reliability optimization, a lot of work has been done in this area since the 1990s (Kuo and Wan (2007)). For example, Mettas and Kallenberg (2000) determined the minimum required reliability for each component of a system in order to achieve a system reliability goal with minimum cost.…”

Section: Literaturementioning

confidence: 99%

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Reliability optimization for series systems under uncertain component failure rates in the design phase

Peng

Houtum

et al. 2018

International Journal of Production Economics

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. (2018). Reliability optimization for series systems under uncertain component failure rates in the design phase. International Journal of Production Economics, 196(2), 163-175. DOI: 10.1016163-175. DOI: 10. /j.ijpe.2017 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. AbstractWe develop an optimization model to determine the reliability design of critical components in a serial system. The system is under a service contract, and a penalty cost has to be paid by the OEM when the total system down time exceeds a predetermined level, which complicates the evaluation of the expected cost under a given reliability design. Furthermore, in the design phase for each critical component, all possible designs are subject to uncertain component failure rates. Considering the computational intractability of evaluating the system performance, we develop approximate evaluation methods which take the system uncertainty into account. Numerical results show that the method which includes randomness in the number of failures, failure rates and repair times leads to efficient and accurate evaluations and to close-to-optimal design decisions when used in an enumeration procedure for the optimization problem. We also show that ignoring these three types of uncertainty may result in bad design decisions.

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Section: Literaturementioning

confidence: 99%

“…Kuo and Wan, 2007, Jin and Wang, 2012, Kim et al, 2017, all parameters are assumed to be precise. However in reality there is considerable uncertainty and inaccuracy in the estimation of model parameters.…”

Section: Literaturementioning

confidence: 99%

Reliability optimization for series systems under uncertain component failure rates in the design phase

Peng

Houtum

et al. 2018

International Journal of Production Economics

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“…Furthermore, availability can be improved in an existing system through improved maintainability when the reliability values are not realized according to the manufacturer's specifications. 15 There are several definitions of availability depending on the user's point of view. All such definitions use equation (1) as a baseline, which essentially provides a probability of the system being operational.…”

Section: Availability Classification and Quantificationmentioning

confidence: 99%

Achieved availability importance measure for enhancing reliability-centered maintenance decisions

Gravette

Barker

2014

Proceedings of the Institution of Mechanical Engineers, Part O:

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An effective defense strategy requires aircraft, among other weapons systems, to be available and ready for use when circumstances deem necessary. This article offers a set of importance measures to identify the critical components in a system from their influence on system-achieved availability, a common Department of Defense availability calculation that is a ratio of mean time between maintenance and total system time, including mean maintenance time. With these measures, more effective maintenance plans, including inspection and supply inventory, can focus on those components that more significantly impact achieved availability. A decision-making formulation results from these component importance measures, and an example based on a US Air Force system illustrates the modeling contributions.

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“…In fact, the efficiency is different when different algorithms are used, so there is no need to compare what kind of algorithm is more excellent. Reliability allocation algorithm should have improved the efficiency of allocation synthesizing multiple algorithms, however, there are few studies aiming at the issue up to now [5].…”

Section: Introductionmentioning

confidence: 99%

Hybrid PSO-SQP Algorithm for Solving System Reliability Allocation Optimization

Tang¹,

Guo²,

Mo³

2015

Proceedings of the 2015 International Conference on Materials Engineering and Information Technology Applications

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System reliability allocation is an important ingredient in system reliability design, and it is also a decision-making issue of reliability engineering. To achieve the optimization of system reliability allocation, an optimization model for system reliability allocation, which takes the system cost as the objective function, is constructed through the general cost function. In order to overcome the shortcomings of particle swarm optimization (PSO) appearing in reliability allocation optimization, the premature and/or slow speed of convergence in later period, the sequential quadratic programming (SQP) was introduced to improve the PSO algorithm. The algorithm uses PSO as the global optimizer while the SQP is employed for accelerating the local search. Thus, the particles are able to search the whole space while searching for local optimization fast, which not only assures the convergence of the algorithm, but also increases the probability of obtaining the global optimum. Applied the algorithm to the problem of system reliability allocation, the simulation results show that it has excellent global search capability and provides rational optimization results compared to the existing approaches.

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Recent Advances in Optimal Reliability Allocation

Cited by 79 publications

References 116 publications

Reliability optimization for series systems under uncertain component failure rates in the design phase

Reliability optimization for series systems under uncertain component failure rates in the design phase

Achieved availability importance measure for enhancing reliability-centered maintenance decisions

Hybrid PSO-SQP Algorithm for Solving System Reliability Allocation Optimization

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