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Добірка наукової літератури з теми "MAINTENANCE PREDICTION"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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Дисертації з теми "MAINTENANCE PREDICTION"

1

Morrison, David J. "Prediction of software maintenance costs." Thesis, Edinburgh Napier University, 2001. http://researchrepository.napier.ac.uk/Output/3601.

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This thesis is concerned with predicting the costs of maintaining a computer program prior to the software being developed. The ubiquitous nature of software means that software maintenance is an important activity, and evidence exists to support the contention that it is the largest and most costly area of endeavour within the software domain. Given the levels of expenditure associated with software maintenance, an ability to quantify future costs and address the determinants of these costs can assist in the planning and allocation of resources. Despite the importance of this field only a lim

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2

Ishihara, Yasuo. "Prediction of human error in rail car maintenance." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10629.

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3

Hartmann, Jens. "Analysis of maintenance records to support prediction of maintenance requirements in the German Army." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA392054.

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4

Kumbala, Bharadwaj Reddy. "Predictive Maintenance of NOx Sensor using Deep Learning : Time series prediction with encoder-decoder LSTM." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18668.

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In automotive industry there is a growing need for predicting the failure of a component, to achieve the cost saving and customer satisfaction. As failure in a component leads to the work breakdown for the customer. This paper describes an effort in making a prediction failure monitoring model for NOx sensor in trucks. It is a component that used to measure the level of nitrogen oxide emission from the truck. The NOx sensor has chosen because its failure leads to the slowdown of engine efficiency and it is fragile and costly to replace. The data from a good and contaminated NOx sensor which is

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5

Podda, G. "PREDICTION OF OPTIMAL WARFARIN MAINTENANCE DOSE USING ADVANCED ARTIFICIAL NEURAL NETWORKS." Doctoral thesis, Università degli Studi di Milano, 2013. http://hdl.handle.net/2434/219087.

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Introduction. The individual response to vitamin K antagonists (VKA) is highly variable, being influenced by clinical factors and genetic variants of enzymes that are involved in the metabolism of VKA (CYP2C)) and vitamin K (VKORC1). Currently, the dose of VKA is adjusted based on measurements of the prothrombin time. In the last years, mathematical algorithms were developed for estimating the appropriate VKA dose, based on different mathematical approaches working on clinical and genetic data. Artificial Neural Networks (ANN) are computerized algorithms resembling interactive processes of th

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6

Tse, Peter W. "Neural networks for machine fault diagnosis and life span prediction." Thesis, University of Sussex, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390518.

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7

Wan, Husain Wan Mohd Sufian Bin. "Maintainability prediction for aircraft mechanical components utilising aircraft feedback information." Thesis, Cranfield University, 2011. http://dspace.lib.cranfield.ac.uk/handle/1826/7272.

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Анотація:

The aim of this research is to propose an alternative approach to determine the maintainability prediction for aircraft components. In this research, the author looks at certain areas of the maintainability prediction process where missteps or misapplications most commonly occur. The first of these is during the early stage of the Design for Maintainability (DfMt) process. The author discovered the importance of utilising historical information or feedback information. The second area is during the maintainability prediction where the maintenance of components is quantified; here, the author p

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8

Kaidis, Christos. "Wind Turbine Reliability Prediction : A Scada Data Processing & Reliability Estimation Tool." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-221135.

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This research project discusses the life-cycle analysis of wind turbines through the processing of operational data from two modern European wind farms. A methodology for SCADA data processing has been developed combining previous research findings and in-house experience followed by statistical analysis of the results. The analysis was performed by dividing the wind turbine into assemblies and the failures events in severity categories. Depending on the failure severity category a different statistical methodology was applied, examining the reliability growth and the applicability of the “bat

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9

Sammouri, Wissam. "Data mining of temporal sequences for the prediction of infrequent failure events : application on floating train data for predictive maintenance." Thesis, Paris Est, 2014. http://www.theses.fr/2014PEST1041/document.

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Анотація:

De nos jours, afin de répondre aux exigences économiques et sociales, les systèmes de transport ferroviaire ont la nécessité d'être exploités avec un haut niveau de sécurité et de fiabilité. On constate notamment un besoin croissant en termes d'outils de surveillance et d'aide à la maintenance de manière à anticiper les défaillances des composants du matériel roulant ferroviaire. Pour mettre au point de tels outils, les trains commerciaux sont équipés de capteurs intelligents envoyant des informations en temps réel sur l'état de divers sous-systèmes. Ces informations se présentent sous la form

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10

Hussin, Burairah. "Development of a state prediction model to aid decision making in condition based maintenance." Thesis, University of Salford, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.490430.

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Condition monitoring and fault diagnosis for operational equipment are developing and bowing their potential for enhancing the effectiveness and efficiency of maintenance management, including maintenance decision-making. In this thesis, our aim is to model the condition of equipment items subject to condition-monitoring in order to provide a quantitative measure to aid maintenance decision-making. A key ingredient towards dealing with the modelling work is to define the state or condition of the equipment with an appropriate measure and the observed condition monitoring may be a function of t

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