Evaluation of a new maintenance concept for the preservation of highways

Dekker, Rommert; Plasmeijer, Raymond Ph.; Swart, Jan

doi:10.1093/imaman/9.2.109

Cited by 10 publications

(10 citation statements)

References 7 publications

(7 reference statements)

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“…Structural dependence exists when the maintenance of one component requires the maintenance of other sub-components or their shutdown. 13 This type of dependency is found in the models proposed by Dekker et al 20 and Zhu et al 21 Recently, Olde Keizer et al 12 classified structural dependencies into two categories based on a technical 3 or a performance point of view. 4…”

Section: Related Workmentioning

confidence: 94%

Dynamic and adaptive grouping maintenance strategies: New scalable optimization algorithms

Hanini

Khebbache

Bouillaut

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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This paper focuses on new efficient and adaptive optimization algorithms to cope with the maintenance grouping problem for series, parallel, and complex systems. We propose a Particle Swarm Optimization approach to cope with small and medium problem sizes, and that will be used to benchmark existing heuristic solutions such as Genetic Algorithms. To address scalability and adaptability issues, we propose a new dynamic optimization algorithm based on a clustering technique. This clustering-based solution is formulated using an Integer Linear Programing approach to guarantee the convergence to global optimal solutions of the considered problem. We show the performance of the proposed approaches with a clear advantage to the clustering-based algorithm that we recommend for large industrial systems.

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Section: Related Workmentioning

confidence: 94%

Dynamic and adaptive grouping maintenance strategies: New scalable optimization algorithms

Hanini

Khebbache

Bouillaut

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…For example, Dekker et al (1998) have studied the maintenance policy for asphalt roads, where the number of maintenance services is limited by integrating neighboring segments into a homogeneous section which is completely repaired. Stochastic dependence, also referred to as probabilistic dependence, applies when the state of one component can affect those of other components or their failure rates.…”

Section: Degradation Modelingmentioning

confidence: 99%

Some Challenges and Opportunities in Reliability Engineering

Zio

2016

IEEE Trans. Rel.

174

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Today's fast-pace evolving and digitalizing World is posing new challenges to reliability engineering. On the other hand, the continuous advancement of technical knowledge and the increasing capabilities of monitoring and computing offer opportunities for new developments in reliability engineering. In this paper, I reflect on some of these challenges and opportunities in research and application. The underlying perspective taken stands on:  the belief that the knowledge, information and data (KID) available for the modeling, computations and analyses done in reliability engineering is substantially grown and continue to do so;  the belief that the technical capabilities for reliability engineering have been significantly advanced;  the recognition of the increased complexity of the systems, nowadays more and more made of heterogeneous, highly interconnected elements. In line with this perspective, opportunities and challenges for reliability engineering are discussed in relation to degradation modeling and integration of multi-state and physics-based models therein, accelerated degradation testing, component-, system-and fleet-wide prognostics and health management in evolving environments. The paper is not a review, nor a state of the art work, but rather it offers a vision of reflection on reliability engineering, for consideration and discussion by the interested scientific community. It does not pretend to give the unique view, nor to be complete in the subject discussed and the related literature referenced to.

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“…The decision variables are the quantity of components to repair, and the key functional constraint is time. 6 The research carried out by Rice et al 5 was expanded upon by Cassady et al 7,8 in a variety of different methods. Initially, more sophisticated systems are examined.…”

Section: Introductionmentioning

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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Evaluation of a new maintenance concept for the preservation of highways

Cited by 10 publications

References 7 publications

Dynamic and adaptive grouping maintenance strategies: New scalable optimization algorithms

Dynamic and adaptive grouping maintenance strategies: New scalable optimization algorithms

Some Challenges and Opportunities in Reliability Engineering

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

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