Bi-Objective Fuzzy Selective Maintenance Allocation Problem

Quddoos, Abdul; Ali, Irfan; Khalid, Marzuki

doi:10.1080/01966324.2015.1040177

Cited by 4 publications

(4 citation statements)

References 16 publications

(13 reference statements)

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“…The results are presented in Table 7. Additionally, Ali and Hasan [1], Gupta et al [21], Hassen et al [23], Quddoos et al [36], Diallo et al [13], have considered different types of selective maintenance models and solved it using fuzzy programing and some other existing techniques. The fuzzy set concept, and the intuitionistic fuzzy set, can only handle incomplete or imprecise information.…”

Section: Comparison With the Existing Methodsmentioning

confidence: 99%

Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability

Kamal

Modibbo

AlArjani

et al. 2021

Complex Intell. Syst.

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Selective maintenance problem plays an essential role in reliability optimization decision-making problems. Systems are a configuration of several components, and there are situations the system needs small intervals or break for maintenance actions, during the intervals expert carried out the maintenance actions to replace or repair the deteriorated components of the systems. Because of the uncertainty associated with the component’s operational time, failure, and next mission duration create a new challenge in determining optimal components allocation and evaluating future missions successfully. In this paper, a multi-objective selective maintenance allocation problem is formulated with fuzzy parameters under neutrosophic environment. A new defuzzification technique is introduced based on beta distribution to convert fuzzy parameters into crisp values. The neutrosophic goal programming technique is used to determine the compromise allocation of replaceable and repairable components based on the system reliability optimization. A numerical illustration is used to validate the model and ascertain its effectiveness. The result is compared with two other approaches and found to be better. The method is flexible and straightforward and can be solved using any available commercial packages. The extension of the concept can be useful to other complex system reliability optimization.

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Section: Comparison With the Existing Methodsmentioning

confidence: 99%

Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability

Kamal

Modibbo

AlArjani

et al. 2021

Complex Intell. Syst.

Self Cite

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“…The author transformed the problem into a linearization membership form by applying a first-order Taylor series technique. Using a fuzzy programming technique, Quddoos et al 32 devised a bi-objective selective maintenance distribution issue in which a fuzzy and precise number of broken items are fixed and replaced to achieve maximum system dependability in a cost-effective way. Haseen et al 33 presented a formulation of the selective maintenance issue as a multi-objective nonlinear programming problem with triangular fuzzy cost, time, and dependability factors.…”

Section: Uncertain Selective Maintenance Optimization Modelsmentioning

confidence: 99%

“…The author transformed the problem into a linearization membership form by applying a first‐order Taylor series technique. Using a fuzzy programming technique, Quddoos et al 32 . devised a bi‐objective selective maintenance distribution issue in which a fuzzy and precise number of broken items are fixed and replaced to achieve maximum system dependability in a cost‐effective way.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimizing system reliability through selective maintenance allocation: A novel multi‐objective programming approach using neutrosophic fuzzy concept

Kamal

Gupta

Jalil

et al. 2023

Quality & Reliability Eng

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Selective maintenance refers to the problem of decision‐making on how to maintain a multi‐component complex system that can be repaired or replaced. The goal is generally to plan ahead in order to improve the likelihood of success for future maintenance tasks. In this article, we proposed a multi‐objective decision‐making model for maximizing the system reliability of a multi‐component systems. The objective functions represent the reliability of the sub‐systems arranged in series comprising of components arranged in parallel forms. The cost and total time incurred in the repair/replacement activities are considered as two sets of constraints in the proposed model. Fuzzy logic is incorporated to deal with the inherent uncertainty that exists in the parameters involved in the proposed model. To solve the uncertain multi‐objective selective maintenance model, we have proposed four‐valued neutrosophic technique. The proposed solution methodology combines the concept of four‐valued neutrosophic fuzzy set with fuzzy goal programming technique. Four linear membership functions for the degrees of truth, uncertainty, contradiction, and false are used to obtain the compromise solution through the proposed technique. To determine the feasibility and applicability of the proposed model and solution methodology, a case problem of multi‐component system of an aircraft gas turbine engine is studied.

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“…A common point among the above studies is that most of the selective maintenance models are regarded as single-objective optimization problem, and only a few studies have dealt the SMP with multi-objective optimization. To maximize the subsystems’ reliability, Quddoos et al 31 investigated a bi-objective fuzzy selective maintenance model. Mellal and Zio 32 adopted an adaptive particle swarm optimization for the reliability optimization of multi-objective system.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective imperfect selective maintenance optimization for series-parallel systems with stochastic mission duration

Huang

Wen

2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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To improve the probability that an engineering system successfully completes its next mission, it is crucial to implement timely maintenance activities, especially when maintenance time or maintenance resources are limited. Taking series-parallel system as the object of study, this paper develops a multi-objective imperfect selective maintenance optimization model. Among it, during the scheduled breaks, potential maintenance actions are implemented for the components, ranging from minimal repair to replacement. Considering that the level of maintenance actions is closely related to the maintenance cost, age reduction coefficient and hazard rate adjustment coefficient are taken into account. Moreover, improved hybrid hazard rate approach is adopted to describe the reliability improvement of the components, and the mission duration is regarded as a random variable. On this basis, a nonlinear stochastic optimization model is established with dual objectives to minimize the total maintenance cost and maximize the system reliability concurrently. The fast elitist non-dominated sorting genetic algorithm (NSGA-II) is adopted to solve the model. Numerical experiments are conducted to verify the effectiveness of the proposed approach. The results indicate that the proposed model can obtain better scheduling schemes for the maintenance resources, and more flexible maintenance plans are gained.

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Bi-Objective Fuzzy Selective Maintenance Allocation Problem

Cited by 4 publications

References 16 publications

Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability

Neutrosophic fuzzy goal programming approach in selective maintenance allocation of system reliability

Optimizing system reliability through selective maintenance allocation: A novel multi‐objective programming approach using neutrosophic fuzzy concept

Multi-objective imperfect selective maintenance optimization for series-parallel systems with stochastic mission duration

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