Scheduling of Maintenance Tasks and Routing of a Joint Vessel Fleet for Multiple Offshore Wind Farms

Raknes, Nora Tangen; Ødeskaug, Katrine; Stålhane, Magnus; Hvattum, Lars Magnus

doi:10.3390/jmse5010011

Cited by 33 publications

(23 citation statements)

References 29 publications

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“…They designed an efficient algorithm based on the Dantzig-Wolfe decomposition method where an MILP for each subset of turbines is optimally solved to generate all feasible routes and maintenance schedules. Raknes et al (2017) studied an optimisation model for the maintenance schedule and routing problem taking into account multiple work shifts. Moreover, the model deals with the situation where vessels are able to stay offshore for several shifts.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm

Irawan

Eskandarpour

Ouelhadj

et al. 2021

European Journal of Operational Research

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Scheduling maintenance routing for an offshore wind farm is a challenging and complex task. The problem is to find the best routes for the Crew Transfer Vessels to maintain the turbines in order to minimise the total cost. This paper primarily proposes an efficient solution method to solve the deterministic maintenance routing problem in an offshore wind farm. The proposed solution method is based on the Large Neighbourhood Search metaheuristic. The efficiency of the proposed metaheuristic is validated against state of the art algorithms. The results obtained from the computational experiments validate the effectiveness of the proposed method. In addition, as the maintenance activities are affected by uncertain conditions, a simulation-based optimisation algorithm is developed to tackle these uncertainties. This algorithm benefits from the fast computational time and solution quality of the proposed metaheuristic, combined with Monte Carlo simulation. The uncertain factors considered include the travel time for a vessel to visit turbines, the required time to maintain a turbine, and the transfer time for technicians and equipment to a turbine. Moreover, the proposed simulation-based optimisation algorithm is devised to tackle unpredictable broken-down turbines. The performance of this algorithm is evaluated using a case study based on a reference wind farm scenario developed in the EU FP7 LEANWIND project.

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Section: Literature Reviewmentioning

confidence: 99%

Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm

Irawan

Eskandarpour

Ouelhadj

et al. 2021

European Journal of Operational Research

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“…Gintautas and Sørensen [24] present constraints for both installation and O&M vessels given in the previous literature by Dinwoodie et al [44], Besnard et al [13], Nielsen and Sørensen [10], O'Connor et al [45], Van Bussel and Bierbooms [46], O'Connor et al [47], McMillan and Ault [48], Wu [49] and Ahn et al [50]. Raknes et al [25] consider two different vessel types-an accommodation vessel and a crew transfer vessel, in their analysis. The vessels vary in properties, such as capacity and weather conditions.…”

Section: Vessel Personnel and Spare Part Logisticsmentioning

confidence: 99%

“…They investigate two different vessel types and present the access restrictions for them. Raknes et al [25] present a vessel routing and maintenance scheduling model. They compare different vessel fleet compositions with a commercial mixed-integer programming solver and two rolling-horizon heuristics.…”

Section: Transportation and Vessel Routingmentioning

confidence: 99%

“…More details about the different kinds of maintenance are presented in the following subsections. [36] Bach-Andersen et al [72] Helsen et al [73] Pliego Marugán et al [37] Pattison et al [74] Shafiee et al [23] Raknes et al [25] Rinaldi et al [26] Leite et al [75] Welte et al [40] Artigao et al [76] 2 Nguyen and Chou [27] Wang et al [42]…”

Section: Maintenance Strategymentioning

confidence: 99%

See 1 more Smart Citation

Decision Support Models for Operations and Maintenance for Offshore Wind Farms: A Review

Seyr

Muskulus

2019

Applied Sciences

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This paper reviews the state of the art in offshore wind farm operations and maintenance with a focus on decision support models for the scheduling of maintenance. Factors influential to maintenance planning are collected from the literature and their inclusion in state-of-the-art models is discussed. Methods for modeling and optimization are presented. The methods currently used and possible alternatives are discussed. The existing models are already able to aid the decision-making process. They can be improved by applying more advanced mathematical methods, including uncertainties in the input, regarding more of the influential factors, and by collecting, analyzing, and subsequently using more accurate data.

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“…Maintenance is attaining a more important role in organisations because it can affect productivity and profitability [1][2][3], the useful lifespan of the facilities, the quality of the processes [4] and the fulfilment of safety and environmental standards. This has brought about increasing concern over the performance maintenance measurement [5], as shown by the abundant literature that analyses the matter (see [6][7][8][9][10][11][12][13][14][15][16][17]).…”

Section: Introductionmentioning

confidence: 99%

Asymmetries in the Maintenance Performance of Spanish Industries before and after the Recession

Carnero

2017

Symmetry

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Abstract:Until the last few decades, maintenance has not been considered of special importance by organisations. Thus, the number of studies that assess maintenance performance in a country is still very small, despite the relevance this area has to the level of national competitiveness. This article describes a multicriteria model integrating the fuzzy analytic hierarchy process (FAHP) with Multi-Attribute Utility Theory (MAUT) to assess the maintenance performance of large, medium and small enterprises in Spain, before and after the recession, as well as the asymmetries in the state of maintenance between different activity sectors. The weightings are converted to utility functions which allow the final utility of an alternative to be calculated via a Multi-Attribute Utility Function. From the Spanish maintenance data for different industrial sectors in 2005 and 2010, 2400 discrete probability distributions have been produced. Finally, a Monte Carlo simulation is applied for the estimation of the uncertainty. The results show that the economic crisis experienced by Spain since 2008 has negatively affected the level of maintenance applied, rather than it being considered an area that could deliver cost reductions and improvements in productivity and quality to organisations.

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Scheduling of Maintenance Tasks and Routing of a Joint Vessel Fleet for Multiple Offshore Wind Farms

Cited by 33 publications

References 29 publications

Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm

Simulation-based optimisation for stochastic maintenance routing in an offshore wind farm

Decision Support Models for Operations and Maintenance for Offshore Wind Farms: A Review

Asymmetries in the Maintenance Performance of Spanish Industries before and after the Recession

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