Optimal reliability allocation of redundant units and repair facilities by arbitrary failure and repair distributions

Gurov, Sergey V.; Utkin, Lev V.; Shubinsky, Igor Borisovich

doi:10.1016/0026-2714(95)91270-6

Cited by 18 publications

(11 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, the infinite capacity is not a practical approach for real cases. On the other hand, Sharma and Misra, Fawzi and Hawkes, Wang, and Gurov et al . addressed the optimal redundancy design considering limited repair capacity.…”

Section: Literature Reviewmentioning

confidence: 99%

A Joint Reliability and Imperfect Opportunistic Maintenance Optimization for a Multi‐State Weighted k‐out‐of‐n System Considering Economic Dependence and Periodic Inspection

Atashgar

Abdollahzadeh

2017

Quality & Reliability Eng

View full text Add to dashboard Cite

This paper formulates a model to simultaneously optimize the redundancy and imperfect opportunistic maintenance of a multi‐state weighted k‐out‐of‐n system. Different from existing approaches that consider binary or multi‐state elements, our approach considers modular redundancy in which each module/subsystem is composed of several multi‐state components in series. The status of each component is considered to degrade with use. Therefore, a new condition‐based opportunistic maintenance approach using three different thresholds for a component health state is developed. The objective is to determine 1) the minimal‐cost of k‐out‐of‐n system structure, 2) optimal imperfect opportunistic maintenance strategy, 3) optimal maintenance capacity, and 4) optimal inspection interval subject to an availability constraint. System availability is defined as the ability to satisfy consumer demand. Based on the three‐phase approach, a simulation procedure is used to evaluate the expected multi‐state system availability and life cycle costs. Also, a multi‐seed Tabu search heuristic algorithm with a proper neighborhood generation mechanism is proposed to solve the formulated problem. An application to the optimal design of a wind farm is provided to illustrate the proposed approach. Sensitivity analysis is conducted to discuss the influence of the different parameters of the simulation model. Copyright © 2017 John Wiley & Sons, Ltd.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A Joint Reliability and Imperfect Opportunistic Maintenance Optimization for a Multi‐State Weighted k‐out‐of‐n System Considering Economic Dependence and Periodic Inspection

Atashgar

Abdollahzadeh

2017

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…To do so we vary q 1 , q 2 , q 3 and see how this affects the expected utility of the optimal solution, tasks (3,4,5,6,7,8,10,13,14). We also investigate how large a change in the trade-off parameters it would take for this solution to no longer be optimal.…”

Section: Sensitivity To Trade-off Parametersmentioning

confidence: 99%

“…Previous approaches have used mathematical optimisation [13,12,16,17] or fuzzy logic [23,18,27,26] to solve the decision problem. We use a utility-based approach.…”

Section: Introductionmentioning

confidence: 99%

Allocation of tasks for reliability growth using multi-attribute utility

Wilson

Quigley

2016

European Journal of Operational Research

View full text Add to dashboard Cite

In reliability growth models in particular, and project risk management more generally, improving the reliability of a system or product is limited by constraints on cost and time. There are many possible tasks which can be carried out to identify and design out weaknesses in the system under development. This paper considers the allocation problem: which subset of tasks to undertake. While the method is applicable to project risk management generally, the work has been motivated by reliability growth programmes. We utilise a model for reliability growth, based on an efficacy matrix, developed with engineering experts in the aerospace industry. We develop a general multi-attribute utility function based on targets for cost, time on test and system reliability. The optimal subset is identified by maximising the prior expected utility. We derive conditions on the model parameters for risk aversion and loss aversion based on observed properties of preference. We give conditions for multivariate risk aversion under the general form of the utility function. The method is illustrated using an example informed by work with aerospace organisations.

show abstract

“…The reliability allocation problem can also be formulated to address other reliability attributes like availability [14] or maintainability.…”

Section: Reliability Allocation For Complex Systemsmentioning

confidence: 99%

Reliability Allocation

Malaiya¹

2007

Encyclopedia of Statistics in Quality and Reliability

View full text Add to dashboard Cite

A system is generally designed as an assembly of subsystems, each with its own reliability attributes. The overall system reliability is a function of the subsystem reliability metrics. The cost of the system is the sum of the costs for all the subsystems. This article examines possible approaches to allocate the reliability values such that the total cost is minimized. The problem is very general and is applicable for mechanical systems, electrical systems, and computer hardware and software. The problem involves expressing the system reliability in terms of the subsystem reliability values and specifying the cost function for each subsystem, which allows setting up an optimization problem. Software reliability allocation is examined as a detailed example. The article also examines some preliminary apportionment approaches that have been proposed. In some cases, it is possible to use exact optimization methods. In general, a complex case will require use of iterative approaches.

show abstract

Optimal reliability allocation of redundant units and repair facilities by arbitrary failure and repair distributions

Cited by 18 publications

References 6 publications

A Joint Reliability and Imperfect Opportunistic Maintenance Optimization for a Multi‐State Weighted k‐out‐of‐n System Considering Economic Dependence and Periodic Inspection

A Joint Reliability and Imperfect Opportunistic Maintenance Optimization for a Multi‐State Weighted k‐out‐of‐n System Considering Economic Dependence and Periodic Inspection

Allocation of tasks for reliability growth using multi-attribute utility

Reliability Allocation

Contact Info

Product

Resources

About