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Dissertations / Theses on the topic 'Data-driven maintenance'

Author: Grafiati

Published: 25 June 2021

Last updated: 29 July 2025

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1

Sedghi, Mahdieh. "Data-driven predictive maintenance planning and scheduling." Licentiate thesis, Luleå tekniska universitet, Industriell Ekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-80828.

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The railway track network is one of the major modes of transportation and among a country’s most valuable infrastructure assets. Maintenance and renewal of railway infrastructure have a vital role in safety performance, the quality of the ride, train punctuality, and the life cycle cost of assets. Due to the large proportion of maintenance costs, increasing the efficiency of maintenance through optimised planning can result in high amounts of cost-saving. Moreover, from a safety perspective, late maintenance intervention can result in defective track and rollingstock components, which in sever

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2

Decker, de Sousa Leticia <1981&gt. "Data-stream driven Fuzzy-granular approaches for system maintenance." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10273/1/phdThesis_LeticiaDecker.pdf.

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Intelligent systems are currently inherent to the society, supporting a synergistic human-machine collaboration. Beyond economical and climate factors, energy consumption is strongly affected by the performance of computing systems. The quality of software functioning may invalidate any improvement attempt. In addition, data-driven machine learning algorithms are the basis for human-centered applications, being their interpretability one of the most important features of computational systems. Software maintenance is a critical discipline to support automatic and life-long system operation. As

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3

Roychowdhury, Sayak. "Data-Driven Policies for Manufacturing Systems and Cyber Vulnerability Maintenance." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1493905616531091.

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4

ANTOMARIONI, SARA. "Data-driven approaches to maintenance policy definition: general framework and applications." Doctoral thesis, Università Politecnica delle Marche, 2021. http://hdl.handle.net/11566/289660.

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La competitività dell’attuale scenario industriale richiede elevati livelli di affidabilità di processo, in particolare per impianti complessi: infatti un elevato numero di componenti li rende potenzialmente più soggetti a guasti. In questo contesto, la tesi mira a proporre un framework generale per supportare il processo di gestione della manutenzione. Si presentano quattro applicazioni basate sul caso di studio di una raffineria di petrolio. Nella prima applicazione, si adotta il framework per derivare le regole di associazione tra i guasti dei componenti dopo un arresto dell'impianto di raf

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5

Okwori, Emmanuel. "Data-driven approaches for proactive maintenance planning of sewer blockage management." Licentiate thesis, Luleå tekniska universitet, Arkitektur och vatten, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-83891.

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Blockages have been reported to account for a significant proportion of reported failures in sewer networks. The malfunctioning of the sewer network from blockages and the subsequent disruption to other public services and flooding may constitute a risk to the environment and human health. Due to the complex nature of underground sewer networks, a reactive approach to blockage maintenance is typically employed. However, although proactive maintenance strategies have been developed, both approaches could be expensive and highlight the need to address the problem with analytics-based methods. Al

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6

Jiang, Tianyu. "Data-Driven Cyber Vulnerability Maintenance of Network Vulnerabilities with Markov Decision Processes." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1494203777781845.

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7

Larsson, Olsson Christoffer, and Erik Svensson. "Early Warning Leakage Detection for Pneumatic Systems on Heavy Duty Vehicles : Evaluating Data Driven and Model Driven Approach." Thesis, KTH, Mekatronik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-261207.

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Modern Heavy Duty Vehicles consist of a multitude of components and operate in various conditions. As there is value in goods transported, there is an incentive to avoid unplanned breakdowns. For this, condition based maintenance can be applied.\newline This thesis presents a study comparing the applicability of the data-driven Consensus SelfOrganizing Models (COSMO) method and the model-driven patent series introduced by Fogelstrom, applied on the air processing system for leakage detection on Scania Heavy Duty Vehicles. The comparison of the two methods is done using the Area Under Curve val

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8

Dinmohammadi, Fateme. "Data-driven risk-based modelling approaches to maintenance optimisation of railway transport assets." Thesis, Glasgow Caledonian University, 2018. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.743925.

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9

CIPOLLINI, FRANCESCA. "Data-Driven and Hybrid Methods for Naval Applications." Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/989847.

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The goal of this PhD thesis is to study, design and develop data analysis methods for naval applications. Data analysis is improving our ways to understand complex phenomena by profitably taking advantage of the information laying behind a collection of data. In fact, by adopting algorithms coming from the world of statistics and machine learning it is possible to extract valuable information, without requiring specific domain knowledge of the system generating the data. The application of such methods to marine contexts opens new research scenarios, since typical naval problems can now be sol

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10

Lundgren, Andreas. "Data-Driven Engine Fault Classification and Severity Estimation Using Residuals and Data." Thesis, Linköpings universitet, Fordonssystem, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-165736.

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Recent technological advances in the automotive industry have made vehicularsystems increasingly complex in terms of both hardware and software. As thecomplexity of the systems increase, so does the complexity of efficient monitoringof these system. With increasing computational power the field of diagnosticsis becoming evermore focused on software solutions for detecting and classifyinganomalies in the supervised systems. Model-based methods utilize knowledgeabout the physical system to device nominal models of the system to detect deviations,while data-driven methods uses historical data to

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11

TIGRINI, ANDREA. "Neuromuscular Control Modeling: from Physics to Data-Driven Approaches." Doctoral thesis, Università Politecnica delle Marche, 2022. https://hdl.handle.net/11566/299445.

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Il controllo neurale della postura umana è stato investigato a partire da un punto di vista fisico. Il paradigma di controllo intermittente è stato usato allo scopo di capire il peso di quest'ultimo nella generazione delle traiettorie del centro di pressione. Un primo contributo di questo lavoro rigurda quindi l'analisi del centro di pressione generato dal suddetto modello biomeccanico attraverso l'extended detrended fluctuation analysis, recentemente proposta in letteratura. Le proprietà di correlazione a lungo termine e disomogeneità sono risultate strettamente legate al guadagno derivativo

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12

Kullenda, Kuben. "Enabling firm performance through data driven decision making in maintenance management : a dynamic capabilities view." Diss., University of Pretoria, 2020. http://hdl.handle.net/2263/79594.

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Maintenance management is seen as a “necessary evil”, rather than a profit contributing resource that could intensify competitive advantage for the organisation. With the world facing the fourth industrial revolution, a radical increase in the reshaping of companies and competition within asset intensive industries is being observed. Organisations in these industries are being forced to rethink traditional ways of working and gearing the workforce with higher and more diversified competency profiles. This suggests that the traditional way of executing maintenance management, being predominantl

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13

Ponomarenko, Maksym. "Maintenance of the Quality Monitor Web-Application." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-28816.

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Applied Research in System Analysis (ARiSA) is a company specialized in the development of the customer-specific quality models and applied research work. In order to improve the quality of the projects and to reduce maintenance costs, ARiSA developed Quality Monitor (QM) – a web application for quality analysis. QM application has been originally developed as a basic program to enable customers to evaluate the quality of the sources. Therefore, the business logic of the application was simplified and certain limitations were imposed on it, which in its turn leads to a number of issues related

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14

Lembke, Benjamin. "Bearing Diagnosis Using Fault Signal Enhancing Teqniques and Data-driven Classification." Thesis, Linköpings universitet, Fordonssystem, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158240.

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Rolling element bearings are a vital part in many rotating machinery, including vehicles. A defective bearing can be a symptom of other problems in the machinery and is due to a high failure rate. Early detection of bearing defects can therefore help to prevent malfunction which ultimately could lead to a total collapse. The thesis is done in collaboration with Scania that wants a better understanding of how external sensors such as accelerometers, can be used for condition monitoring in their gearboxes. Defective bearings creates vibrations with specific frequencies, known as Bearing Characte

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15

Nguyen, Hoang-Phuong. "Model-based and data-driven prediction methods for prognostics." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASC021.

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La dégradation est un phénomène inévitable qui affecte les composants et les systèmes d'ingénierie, et qui peut entraîner leurs défaillances avec des conséquences potentiellement catastrophiques selon l'application. La motivation de cette Thèse est d'essayer de modéliser, d'analyser et de prédire les défaillances par des méthodes pronostiques qui peuvent permettre une gestion prédictive de la maintenance des actifs. Cela permettrait aux décideurs d'améliorer la planification de la maintenance, augmentant ainsi la disponibilité et la sûreté du système en minimisant les arrêts imprévus. Dans cet

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16

Berg, Martin, and Albin Eriksson. "Toward predictive maintenance in surface treatment processes : A DMAIC case study at Seco Tools." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik, konst och samhälle, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-84923.

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Surface treatments are often used in the manufacturing industry to change the surface of a product, including its related properties and functions. The occurrence of degradation and corrosion in surface treatment processes can lead to critical breakdowns over time. Critical breakdowns may impair the properties of the products and shorten their service life, which causes increased lead times or additional costs in the form of rework or scrapping. Prevention of critical breakdowns due to machine component failure requires a carefully selected maintenance policy. Predictive maintenance is used t

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17

Wileman, Andrew John. "An investigation into the prognosis of electromagnetic relays." Thesis, Cranfield University, 2016. http://dspace.lib.cranfield.ac.uk/handle/1826/13665.

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Electrical contacts provide a well-proven solution to switching various loads in a wide variety of applications, such as power distribution, control applications, automotive and telecommunications. However, electrical contacts are known for limited reliability due to degradation effects upon the switching contacts due to arcing and fretting. Essentially, the life of the device may be determined by the limited life of the contacts. Failure to trip, spurious tripping and contact welding can, in critical applications such as control systems for avionics and nuclear power application, cause signif

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18

Eker, Ömer F. "A hybrid prognostic methodology and its application to well-controlled engineering systems." Thesis, Cranfield University, 2015. http://dspace.lib.cranfield.ac.uk/handle/1826/9269.

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This thesis presents a novel hybrid prognostic methodology, integrating physics-based and data-driven prognostic models, to enhance the prognostic accuracy, robustness, and applicability. The presented prognostic methodology integrates the short-term predictions of a physics-based model with the longer term projection of a similarity-based data-driven model, to obtain remaining useful life estimations. The hybrid prognostic methodology has been applied on specific components of two different engineering systems, one which represents accelerated, and the other a nominal degradation process. Clo

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19

Jose, Sagar. "Stratégies d'apprentissage multimodal pour le diagnostic et le pronostic de la santé des machines industrielles dans un contexte de manque de données." Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSEP093.

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Les approches de Pronostic et gestion de la santé des systèmes (Prognostics and Health Management : PHM) guidées par les données sont fortement dépendantes de la disponibilité et de la qualité d’historiques de défaillances, une exigence souvent difficile à satisfaire dans les systèmes de surveillance en conditions industrielles. Cette divergence crée un écart significatif entre les méthodologies de PHM et leur application pratique sur des systèmes réels. L’accent prédominant mis sur les ensembles de données unimodales dans les travaux de recherche en PHM basée sur les données met en lumière le

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20

Krupa, Miroslav. "Metody technické prognostiky aplikovatelné v embedded systémech." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-233568.

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Hlavní cílem dizertace je poskytnutí uceleného pohledu na problematiku technické prognostiky, která nachází uplatnění v tzv. prediktivní údržbě založené na trvalém monitorování zařízení a odhadu úrovně degradace systému či jeho zbývající životnosti a to zejména v oblasti komplexních zařízení a strojů. V současnosti je technická diagnostika poměrně dobře zmapovaná a reálně nasazená na rozdíl od technické prognostiky, která je stále rozvíjejícím se oborem, který ovšem postrádá větší množství reálných aplikaci a navíc ne všechny metody jsou dostatečně přesné a aplikovatelné pro embedded systémy.

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21

Wu, Bai Rong. "Condition based maintenance optimization using data driven methods." Thesis, 2013. http://spectrum.library.concordia.ca/977934/1/Wu_PhD_F2013.pdf.

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In condition based maintenance (CBM), maintenance activities are scheduled based on the predicted equipment failure times, and the predictions are performed based on conditon monitoirng data, such as vibration and acoustic data. The reported health condition prediction methods can be roughly classified into model-based, and data-driven, and integrated methods. Our research mainly focuses on CBM optimization using data driven methods, such as proportional hazards model (PHM) and artificial neural network (ANN), which don't require equipment physical models. In CBM optimization using PHM, the a

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22

Chen, Kuan-Yu, and 陳冠宇. "Applying Data Driven Approach to Cluster Components for Preventive Maintenance." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/479gt4.

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碩士<br>國立中央大學<br>企業管理學系<br>106<br>Utilizing preventive maintenance can reduce machine’s shutdown and improve the equipment efficiency. Traditional preventive maintainance methods focus on maintaining single component. The research, however, strives to maintain a group of components to further reduce the maintenance time. Components are clustered into group according to the their distributions of lifespans. Clusters that save the most maintenance costs are recommended to managers for maintenance scheduling. The methodology is applied to an auto component company for experiments. The results show

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23

Zschech, Patrick. "Data Science and Analytics in Industrial Maintenance: Selection, Evaluation, and Application of Data-Driven Methods." 2020. https://tud.qucosa.de/id/qucosa%3A72318.

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Data-driven maintenance bears the potential to realize various benefits based on multifaceted data assets generated in increasingly digitized industrial environments. By taking advantage of modern methods and technologies from the field of data science and analytics (DSA), it is possible, for example, to gain a better understanding of complex technical processes and to anticipate impending machine faults and failures at an early stage. However, successful implementation of DSA projects requires multidisciplinary expertise, which can rarely be covered by individual employees or single units wit

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