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- Ahmadi, Alireza
(författare)
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Aircraft scheduled maintenance programme development : decision support methodologies and tools
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The air transport business is large in its operations, integrated, automated and complex. Air carriers are constantly striving to achieve high standards of safety and simultaneously to attain an increased level of availability performance at minimal cost. This needs to be supported through an effective maintenance programme which has a major impact on the availability performance and which ultimately can enhance the aircraft’s capability to meet market demands at the lowest possible cost. The development of a maintenance programme is challenging, but can be enhanced by supporting methodologies and tools. The purpose of this study is to develop decision support methodologies and tools for aircraft scheduled maintenance programme development within the framework of Maintenance Review Board (MRB) process. To achieve the purpose of the research, literature studies, case studies, and simulations have been conducted. Empirical data have been collected through document studies, interviews, questionnaires, and observations from the aviation industry. For data analysis, theories and methodologies within risk, dependability and decision making have been combined with the best practices from the aviation industry. One result of the research is the identification of potential areas for improving the use of MSG-3 methodology in aircraft scheduled maintenance development. Another result is the development of a systematic methodology guided by the application of an Event Tree Analysis (ETA) for the identification and quantification of different operational risks caused by aircraft system failures, to support decision making for maintenance task development. A third result is a proposed methodology, based on a combination of different Multi-Criteria Decision Making (MCDM) methodologies, for selecting the most effective maintenance strategy for aircraft scheduled maintenance development. Finally, the fourth result is a proposed Cost Rate Function (CRF) model supported by a graphical approach. The approach can be used to identify the optimum maintenance interval and frequencies of Failure Finding Inspection (FFI) and to develop a combination of FFI and restoration tasks for the aircraft’s repairable items which are experiencing aging. These results are related to some of the specific industrial challenges, and are expected to enhance the capability of making effective and efficient decisions during the development of maintenance tasks. The results have been verified through interaction with experienced practitioners within major aviation manufacturers and air operators.
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| 2. |
- Block, Jan, 1973-
(författare)
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Part-out Based Spares Provisioning and Management : A Study for Aircraft Retirement
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The operation and maintenance phase of a complex technical system may deal with strategicdecisions for asset retirement and end-of-life management. When a fleet of aircraft reachesthe retirement phase, the operation of remaining fleet should still be kept at a defined level ofavailability. Obviously, the provisioning of spares is a key issue to support the maintenanceand operation of the remaining fleet. The best practice within the aviation industry is to re-usethe spares of retired aircraft to support the operational fleet. This is referred to parting-out.The purpose of the research conducted for this thesis has been to develop decision supportmethodologies, models and tools for the management of a sustainable part-out-based sparesprovisioning for an aircraft fleet during its retirement period. The proposed methodology willbe used to support the retirement process of aircraft fleet and enhance the organisation’scapability of making efficient and cost-effective decisions concerning the re-use of spare partsduring the retirement period. To achieve the purpose of this research, literature studies, casestudies, algorithm development and simulations have been conducted. Empirical data havebeen collected through document studies, interviews, and the perusal of archival records fromSaab Support and Services AB. The data analysis performed for this research has been basedon theories and methodologies within reliability analysis, cost modelling, spares forecasting,stock provisioning and decision making, in combination with the best practices implementedby the aviation industry for the end-of-life management and retirement of aircraft.In the present thesis, part-out-based spares provisioning (PBSP) program is proposed to utiliseretired aircraft units effectively as spare parts. The proposed approach is illustrated andverified through a case study performed on the “Saab-105” military aircraft fleet withinSwedish air force fleet. A PBSP programme is proposed, associated management activitiesare described, the key decision criteria are presented, and a functional framework for aneffective PBSP is suggested. The proposed PBSP program provides a foundation for furthermeasures and tasks to be performed within the retirement period, such as terminatingmaintenance contracts, discarding internal maintenance capabilities, reviewing stocks, scalingdown administrative processes (e.g. spares procurement and obsolescence monitoring), etc.An important part of the PBSP programme is the reliability analysis of multiple repairableunits, and this has been investigated, using parametric and non-parametric reliabilityapproaches. The aim is to identify a practical approach for estimation of the future sparedemand at fleet level. Furthermore, a set of computational models and search algorithm havebeen developed for the identification of applicable termination times, of both the parting-outprocess and the maintenance and repair actions performed on the units. This includestermination of the parting-out process (PO), the sending of parted-out units directly to storage(POS), and repair actions performed on the units received at the repair shops owing tocorrective (CM) and preventive (PM) maintenance, as well as the parted-out units that need tobe repaired (POM). The feasible termination alternatives are compared with regard to theirrespective costs and the most cost-effective solutions are identified.The results of the research study show that a PBSP programme can yield large reductions inmaintenance and spares procurement costs, while supporting operation of existing fleet athighest required availability. It also contributes positively to implement a green supply chainduring the retirement phase. The methodology and approaches introduced within the thesiscan be applied in other civil applications, such as energy, mining, process industry andtransportation sectors.
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| 3. |
- Khajehei, Hamid, 1987-
(författare)
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Data-driven models for railway track geometry maintenance
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Railways are currently experiencing higher demands on safety, infrastructure performance, network capacity and service quality, etc. As a result, a high level of track availability, service quality and infrastructure robustness against unexpected events is required, at reduced cost, to meet the demands. The track geometry is one of the critical parameters influencing the performance of the infrastructure and the capacity and quality of service of the railway network. The track geometry continuously degrades and deviates from the designed level over time and under the influence of various factors. A poor track geometry negatively affects the ride quality and passenger comfort and increases the risk of train derailment. To ensure a safe and reliable track for the trains, the track geometry should be kept in an acceptable condition. This necessitates the development of an applicable and effective tamping regime, as the main maintenance action for track geometry rejuvenation. An effective tamping regime enables enhancement of the availability and safety performance of the track, to control the track degradation and to restore the damaged track to an operational state, at the lowest possible cost. The purpose of the research conducted for this thesis was to develop data-driven methodologies and optimization approaches for the development of a plan for predictive railway track geometry maintenance. First, a study was carried out to investigate the application of artificial neural networks to estimation of the track geometry degradation rate in spatial space by considering the operational and constructional covariates. In addition, the relative importance of the observed covariates for the track geometry degradation was also explored. The results showed that the maintenance history, the degradation value after tamping and the frequency of the trains passing along the track were the most important covariates affecting the track geometry degradation rate. Second, a case study was performed on a heavy haul railway line to analyse the isolated twist and longitudinal level defects. A data-driven model was developed to predict the occurrence of track geometry defects. A machine learning technique, namely the RUSBoost algorithm, was used to classify the track sections into healthy and unhealthy track sections. In order to capture information about the shape of the defects, first- and second-order derivatives of the track irregularities were used. The observed anomalies in the conducted case study in the pattern of the track geometry degradation were also explored. It was found that applying a combination of the kurtosis and the standard deviation to represent the track quality is beneficial for identifying the anomalies in the trend of geometry defects. Third, a simulation-based framework was developed with the aim of allocating an effective maintenance limit by assessing the effect of different maintenance limits on the total maintenance cost. The results showed that it is not one value only, but a range of values for the maintenance limits which can be selected to minimize the total maintenance costs. However, by considering the safety aspects of track geometry maintenance, it is suggested that one should select the lower bound of the range of cost-effective limits for maintenance planning. Finally, an optimization model was developed to schedule track tamping activities with the aim of minimizing both the track geometry maintenance costs and the number of unplanned maintenance actions. The proposed model enables infrastructure managers to examine the effect of different scenarios for the control and management of isolated defects on the track geometry condition and the maintenance cost. The results obtained in the present research are highly relevant for specific industrial challenges and are expected to enhance the capability of infrastructure managers to make effective and efficient decisions when developing their planning and scheduling of the tamping regime. The results have been verified through interaction with experienced practitioners working for a major railway infrastructure manager and railway maintenance subcontractors.
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| 4. |
- Khosravi, Mahdi, 1988-
(författare)
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Leveraging Data-Driven and Alignment Techniques for Optimal Railway Track Maintenance Scheduling
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The railway infrastructure plays a pivotal role in fostering economic growth and poverty alleviation. Over time, these infrastructures deteriorate due to aging and usage, compromising their functionality. Given their crucial socioeconomic significance and vast scale, ensuring their functionality and availability is paramount. Thus, an effective condition-based maintenance program is essential to restore reliability, facilitate cost-effective restoration, and enable continued benefits.Track is a critical railway component susceptible to degradation from traffic loading, resulting in deviations from designated geometry parameters. Such degradation jeopardizes safety, availability, and travel quality. Developing an effective tamping regime emerges as a vital maintenance measure to control degradation and restore track geometry to acceptable standards. An optimal maintenance schedule becomes imperative to minimize costs, enhance track availability and capacity, and ensure safety.Achieving efficient tamping scheduling necessitates accurate prediction of geometry degradation, accounting for tamping effects, and modeling the evolution of single defects. However, uncontrolled shifts in geometry measurements from different inspections—known as positional errors—can misplace defects and distort their evolution analysis. Therefore, precise alignment of geometry measurements is vital to eliminate such positional errors.The purpose of this research was to streamline maintenance scheduling through leveraging track geometry measurements for modeling and prediction. Firstly, a study addressed alignment through evaluating and comparing four methods—Cross-Correlation Function (CCF), Recursive alignment by fast Fourier transform (RAFFT), Correlation optimized warping (COW), and Dynamic Time Warping (DTW). Furthermore, a combined RAFFT-COW method was proposed, overcoming their limitations. Comparison revealed COW aligned datasets satisfactorily without altering their shape but could not align endpoints precisely. The combined method effectively aligned datasets even when the datasets were stretched or compressed. Secondly, a modified COW (MCOW) addressed accurate and efficient alignment. MCOW surpassed COW's restrictions and reduced alignment time. To enhance robustness, MCOW with channel fusion (MFCOW) combined data from different channels, significantly reducing positional errors. Thirdly, a multi-objective approach proposed aimed at reducing positional errors in geometry measurements of track as a linear asset. Accordingly, recursive segment-wise peak alignment (RSPA) and MCOW were evaluated and compared. Furthermore, a novel rule-based approach proposed which prevented data loss during alignment, preserving all the single defects. In addition, the results revealed that RSPA excelled in aligning peaks, while MCOW proved efficient for datasets with equal priority data points.Finally, an optimization model minimized track geometry maintenance costs through tamping scheduling. Key track quality indicators, including the standard deviation of the longitudinal level and single defects and the impact of preventive/corrective tamping on these indicators were integrated. Results showcased the influence of fixed maintenance window costs and maintenance cycle intervals on tamping expenses. The model's validity was confirmed through interactions with experienced practitioners from prominent railway infrastructure and maintenance entities.
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| 5. |
- Soleimanmeigouni, Iman, 1988-
(författare)
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Predictive Models for Railway Track Geometry Degradation
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Railways are a vital and effective means of mass transportation and play a vital role in modern transportation and social development. The benefits of the railway compared to other transportation modes are a high capacity, high efficiency and low pollution, and owing to these advantages, railways are nowadays experiencing a higher demand for the transportation of passengers and goods. This is in turn imposing higher demands on the railway capacity and service quality. As a result, infrastructure managers are being driven to develop new strategies and plans to fulfil new requirements, which include a higher level of resilience against failure, a more robust and available infrastructure, and cost reduction. This can be achieved by making efficient and effective maintenance decisions by applying RAMS (reliability, availability, maintainability, and safety) analysis and LCC (life cycle cost) assessment.A major part of the railway maintenance burden is related to track geometry maintenance. Due to the forces induced on the track by traffic, the railway degrades over time, causing deviations from the designed vertical and horizontal alignment. When the track geometry degrades to an unacceptable level, this can cause catastrophic consequences, such as derailment. Maintenance actions are used to control the degradation of the track and restore the geometry condition of the track sections to an acceptable state.With the current advancements in the field of technologies for railway track geometry measurement, a large amount of event data and condition monitoring data is available. Such technologies, along with advances in predictive analytics, are providing the possibility of predicting the track geometry condition in support of a predictive maintenance strategy. The aim of the research conducted for this thesis has been to develop methodologies and tools for the prediction of railway track geometry degradation, in order to facilitate and enhance the capability of making effective decisions for inspection and maintenance planning. To achieve the purpose of this research, literature studies, case studies and simulations have been conducted.Firstly, a literature review was performed to identify the existing knowledge gaps and challenges for track geometry degradation modelling and maintenance planning. Secondly, a case study was conducted to analyse the effect of tamping on the track geometry condition. By considering the track geometry condition before tamping as the predictor, a probabilistic approach was utilised to model the recovery after tamping interventions. Thirdly, a two-level piecewise linear framework was developed to model the track geometry evolution over a spatial and temporal space. This model was implemented in a comprehensive case study. Fourthly, a data-driven analytical model was developed to predict the occurrence of track geometry defects. This model enables infrastructure managers to predict the occurrence of severe isolated geometry defects. Finally, an integrated model was created to investigate the effect of different inspection intervals on the track geometry condition.
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