Multi-agent based simulation-optimization of maintenance routing in offshore wind farms

Allal, Abdelmoula Ait; Sahnoun, M’hammed; Adjoudj, Reda; Benslimane, Sidi Mohamed; Mazar, Merouane

doi:10.1016/j.cie.2021.107342

Cited by 34 publications

(6 citation statements)

References 39 publications

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“…This perspective fails to recognize the interconnectedness of these aspects and the potential benefits of adopting a holistic approach. In advanced industries worldwide, the concept of breakdown maintenance has gradually faded, replaced by a combination of preventive, predictive, and condition monitoring strategies (23). Experts strive to minimize or eliminate process disruptions, leading to the development of comprehensive maintenance and repair frameworks that optimize unit performance while minimizing costs and maximizing added value (24).…”

Section: Literature Reviewmentioning

confidence: 99%

Functional Model of Integrated Maintenance in Petrochemical Industries

Seyed Hosseini,

Shahanaghi,

Shasfand

2024

IJE

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The purpose of this research is to provide an integrated maintenance model in the petrochemical industry. The current research is applied in terms of purpose and descriptive survey in terms of data collection method. A mixed method (qualitative and quantitative) has been used to conduct the research. The tools used in this research are researcher-made questionnaires (36 Questions), dialog with domestic and foreign professors in the field of maintenance and production, the Delphi technique (41 Maintenance managers), Field investigations (20 internal and 7 overseas petrochemical companies), and experiences and evidence obtained from 12 overhauls during 30 years. The validity was determined through experts' opinions and reliability through Cronbach's alpha evaluation. The results showed that the questionnaire has high validity and reliability. The statistical population includes experts in the field of Maintenance in industry and university, among whom 110 people were selected by targeted sampling. To conduct the research in the first stage, first by using the documentary method and content analysis and interviews with experts, the indicators and dimensions of the strong integrated maintenance and repair model were extracted and given to the experts in the form of a Likert scale for scoring; After conducting the survey, 36 components were selected, and each component of management, manpower, equipment, and knowledge had 9 sub-components. In the next step, the components and sub-components were scored and ranked using the questionnaire and the Analytical hierarchy process method. In this research, the following three results have been obtained: 1. Four main roots (Human, Management, Knowledge, and Equipment) and thirty-six sub-roots of effective maintenance. 2. The essential elements of the formula for measuring the criticality index of equipment. 3. Five indicators for measuring integrated maintenance performance. According to the calculations, the inconsistency between the vectors of each matrix is less than 0.10. Therefore, the constituent vectors of each of the formed matrices are consistent with the three results of the research and the stability of the respective comparisons is acceptable.

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Section: Literature Reviewmentioning

confidence: 99%

Functional Model of Integrated Maintenance in Petrochemical Industries

Seyed Hosseini,

Shahanaghi,

Shasfand

2024

IJE

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“…[39] considers uncertainty in weather conditions and maintenance tasks for a tactical maintenance planning problem. [40] proposes a simulation optimisation approach to determine the impact of opportunistic maintenance. An ant colony system approach is suggested for optimising the vessel routing problem, and a multi agent model to represent the behaviour of the system.…”

Section: Eera Deepwind Conference 2023 Journal Of Physics: Conference...mentioning

confidence: 99%

Maritime logistics optimisation for predictive maintenance at offshore wind farms

Halvorsen-Weare,

Nonås

2023

J. Phys.: Conf. Ser.

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For offshore wind farms, a move from a preventive and corrective maintenance regime to a predictive maintenance regime requires new methods for modelling approaches for maritime logistics planning. This paper presents an overview of the maritime logistics planning problem for a predictive maintenance regime and introduces the current state-of-the-art for operational research in the field of operation and maintenance at offshore wind farms. Findings are that a combination of the vessel resource scheduling problem for operation and maintenance at offshore wind farms with predictive analysis and digital twins is a promising future research step. A framework for a decision support tool is presented that will help bridge the gap, both with respect to the academic path, and the gap between academic research and industry.

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“…Li et al [20] proposed an ant colony optimization algorithm for the adaptive greedy strategy to optimize the path problem, but the algorithm is easy to fall into local optimization. Allal et al [21] adopted the weather and resource-based ant colony algorithm to optimize the routing, maintenance, and scheduling of wind farms, which can effectively speed up the convergence speed compared with the traditional algorithm; however, in the case of insufficient iterations, it is still easy to appear local optimal solutions, and the global optimal solution cannot be obtained.…”

Section: Related Workmentioning

confidence: 99%

Research on Operation and Maintenance Route Planning of Offshore Wind Farm Based on Multiagent

Sheng

Sun

et al. 2022

Wireless Communications and Mobile Computing

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Recently, the ant colony algorithm has been widely used in the field of path planning, which is a key technology required for ship operations in offshore wind farms to improve navigation efficiency and power generation. However, the ant colony algorithm has the defects of a long search time and stagnation in the early stage of the operation and maintenance path planning of offshore wind farms, and it easily falls into the problem of local optima; furthermore, the ant colony algorithm uses incremental construction to build a complete itinerary path, it takes a lot of time to search the path, and only the suboptimal solution is obtained. To address the above problems, in this paper, we propose a multi-agent-based operation and maintenance model for offshore wind farms. Specifically, the introduction of the heuristic factor can optimize the local optimal solution and make the ant colony algorithm clearer when searching for the target. Based on this, increasing the pheromone adjustment factor can eliminate the invalid path from searching and select a high-quality path. In addition, by integrating the genetic algorithm, it is possible to select, cross, and mutate to simulate the natural evolution process to search for the optimal solution, reduce the similarity of the paths constructed by the ant colony, reduce the probability of algorithm stagnation, improve the convergence speed, and improve the time efficiency and solution accuracy of the algorithm. Simulation experiments on a series of benchmark datasets show that the proposed GA-PACO algorithm achieves better performance in global search and path planning than the existing three algorithms.

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Multi-agent based simulation-optimization of maintenance routing in offshore wind farms

Cited by 34 publications

References 39 publications

Functional Model of Integrated Maintenance in Petrochemical Industries

Functional Model of Integrated Maintenance in Petrochemical Industries

Maritime logistics optimisation for predictive maintenance at offshore wind farms

Research on Operation and Maintenance Route Planning of Offshore Wind Farm Based on Multiagent

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