An optimisation framework for airline fleet maintenance scheduling with tail assignment considerations

Sanchez, David Torres; Boyacı, Burak; Zografos, Konstantinos G.

doi:10.1016/j.trb.2019.12.008

Cited by 20 publications

(17 citation statements)

References 26 publications

(39 reference statements)

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“…Recent studies oriented the research in maintenance procedures by considering the programming approach [39], by classifying the state of the vehicles [40], or by applying artificial Engine RPM (rpm) In Appendix A and in Appendix B are reported more details about SAE J1939 protocols and IVECO vehicle parameters, respectively.…”

Section: Discussionmentioning

confidence: 99%

Predictive Maintenance of Bus Fleet by Intelligent Smart Electronic Board Implementing Artificial Intelligence

Massaro¹,

Selicato²,

Galiano³

2020

IoT

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This paper is focused on the design and development of a smart and compact electronic control unit (ECU) for the monitoring of a bus fleet. The ECU system is able to extract all vehicle data by the on-board diagnostics-(ODB)-II and SAE J1939 standards. The integrated system Internet of Things (IoT) system, is interconnected in the cloud by an artificial intelligence engine implementing multilayer perceptron artificial neural network (MLP-ANN) and is able to predict maintenance of each vehicle by classifying the driver behavior. The key performance indicator (KPI) of the driver behavior has been estimated by data mining k-means algorithm. The MLP-ANN model has been tested by means of a dataset found in literature by allowing the correct choice of the calculus parameters. A low means square error (MSE) of the order of 10−3 is checked thus proving the correct use of MLP-ANN. Based on the analysis of the results, are defined methodologies of key performance indicators (KPIs), correlating driver behavior with the engine stress defining the bus maintenance plan criteria. All the results are joined into a cloud platform showing fleet efficiency dashboards. The proposed topic has been developed within the framework of an industry research project collaborating with a company managing bus fleet.

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Section: Discussionmentioning

confidence: 99%

Predictive Maintenance of Bus Fleet by Intelligent Smart Electronic Board Implementing Artificial Intelligence

Massaro¹,

Selicato²,

Galiano³

2020

IoT

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“…The suggested approach tries to optimize the wasted period in checks. Sanchez et al [18] presented a multi-objective mixed-integer linear programming model and an iterative algorithm to run commercially viable and maintenance feasible flight and maintenance schedules.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Subject to:(2), (3), (9)-(11),(14);(18),(19)) is the revised version of (1). -CMTSP does not change the computational tractability as it has the same size and complexity as 2.…”

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confidence: 99%

Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

2021

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We study the maintenance task scheduling problem for an aircraft fleet in an uncertain environment from the viewpoint of robust optimization. Given a daily horizon, the maintenance tasks delegated to a shop should be scheduled in such a way that sufficient aircrafts are available on time to meet the demand of planned missions. The tasks are either scheduled maintenance activities or unexpected repair jobs when a major fault is detected during pre-or after-flight check of each mission. The availability of skilled labour in the shop is the main constraint. We propose a robust formulation so that the maintenance tasks duration is subject to unstructured uncertainty due to the environmental and human factors. As a result of the specific structure of the primary model and non-convexity of the feasible space, the classical robust optimization methods cannot be applied. Thus, we propose an ϵ-Conservative model in tandem with Monte-Carlo sampling to extract the set of all feasible solutions corresponding to various disturbance vectors. Since the one-way sampling-thenoptimization approach does not guarantee the probabilistic feasibility, we employ a hybrid simulationoptimization approach to ensure that the solutions provided by the ϵ-Conservative model are robust to all uncertainty scenarios. The experimental results confirm the scalability of the proposed methodology by generating the robust optimal solutions, satisfying all conservatism levels and uncertainty scenarios irrespective of the problem size.

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“…(3) Aircraft maintenance management taking into account the types of surveys that are classified as short, medium, and long term (Sanchez, Boyaci, and Zografos, 2020).…”

Section: Economization Of Lcc Airlines Activitiesmentioning

confidence: 99%

Economization Methods Used by Low-Cost Airlines – An Overview

Punda¹,

Jasiulewicz-Kaczmarek²,

Dziwulski³

2021

ERSJ

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Purpose:The crisis caused by the pandemic has forced airlines (both full-service carriers (FCC) and low cost carriers (LCC)) to review their business models and look for opportunities to make up for losses. The goal of this paper is to review the cost optimization methods used by LCC airlines and to identify the activities of LCC that were taken to reduce costs. Design/Methodology/Approach: The analysis of the areas of economization of activities undertaken by the LCC carried out in the article is the result of a literature review of business models used by LCC carriers. Findings: The conducted literature analysis allowed for the identification of seven main areas in which measures are taken to reduce the costs of the LCC line. Practical Implications: Economization methods implemented by LCC lines at the strategic level reduce the carrier's costs and can be adapted to the market in which it operates. Originality/Value: Although the business models used by LCC lines are not a new topic, the review of economization methods from a strategic perspective presented in the article has not been discussed in the literature.

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An optimisation framework for airline fleet maintenance scheduling with tail assignment considerations

Cited by 20 publications

References 26 publications

Predictive Maintenance of Bus Fleet by Intelligent Smart Electronic Board Implementing Artificial Intelligence

Predictive Maintenance of Bus Fleet by Intelligent Smart Electronic Board Implementing Artificial Intelligence

Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

Economization Methods Used by Low-Cost Airlines – An Overview

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