Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 73 for “"Predictive maintenance"”.
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Predictive maintenance for industry 4.0, a holistic approach to performing predictive maintenance as a service.
… machines are complex and can only work in good maintenance conditions. Any failure of this equipment and related tools can easily lead to unintended disruption. Due to the collaborative nature of the manufacturing systems, one machine failure could result in undesired downtimes beyond single …
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A case model for predictive maintenance
… to help predict failure of ion implanters. Predictive maintenance would help to reduce the unscheduled downtime of ion implanters, whose throughput and uptime is highly important to customers. Statistical analysis is performed on historical data to extract metadata that can reflect the …
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Integrated Proactive Multi-Fault Detection for Predictive Maintenance Applications
L'abstract è presente nell'allegato / the abstract is in the attachment
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Predictive Maintenance in Rail Transportation: An Explainable Machine Learning Approach
… yet their reliability depends on effective maintenance strategies that prevent costly disruptions and safety hazards. Traditional fixed-interval maintenance approaches, although widely adopted, are inefficient and fail to capitalise on the predictive potential of modern condition-monitoring …
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A machine learning framework for predictive maintenance of wind turbines
… experts to define and build models for the predictive maintenance of wind turbines. We contribute two libraries that provide experts with the necessary tools to solve prediction problems in the wind energy industry. The first is GPE, which translates and uses the desired prediction problem …
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Zephyr: a Data-Centric Framework for Predictive Maintenance of Wind Turbines
… and in difficult-to-access locations, turbine maintenance is often challenging and costly. In this thesis, we present Zephyr, a flexible machine learning framework for predictive maintenance of wind energy assets. Manual analysis of wind turbine data is difficult and time-consuming due to its …
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A system approach to implementation of predictive maintenance with machine learning
… after. Many people have heard about industrial maintenance technology, but they have difficulty in differentiate concepts such as reactive maintenance, planned maintenance, proactive maintenance, and predictive maintenance. Many people know that big data and Al are essential in industrial …
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Enhancing a Data-Centric Framework for Predictive Maintenance of Wind Turbines
Predictive maintenance of wind turbines is a machine learning task aimed at minimizing repair costs and improving efficiency in the wind turbine and renewable energy industry. Existing machine learning solutions often fail to meet real-world deployment requirements due to fragmented pipelines, lack …
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A Data Science Approach to Holistically Investigate Historical Caster Data for Predictive Maintenance
… provide improved insight on the performance and maintenance of its continuous casters.<br/><br/>At present, there are a number of existing organisational challenges, including poor communication and data sharing that inhibit best use of the collected data. Initial investigations focused on …
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Assessing the impact of historical operational data from complex assets on predictive maintenance models
Over the past one hundred years, maintenance concepts have evolved from a simple "fix when broken" approach to advanced prognostic methods used today that leverage large amounts of historical, operational, and primary sensor data to predict when and how failures will occur. For firms that produce …
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Design and development of a LIVE Digital Twin methodology for predictive maintenance of bearings in rotary machine systems
Digital Twin (DT) is a prominent focus for many predictive and prescriptive maintenance strategies. In maintenance, DT is used for connecting the physical and digital models of a maintenance monitoring system and proactively prescribing maintenance solutions to extend the products life. Many of the …
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Development of a connected platform for industrial equipment monitoring to enable predictive maintenance using supervised machine learning methods
… customers move away from a break fix model to a predictive maintenance program. This project seeks to expand on a sensor connectivity proof of concept ("POC"), which the team successfully built on a prototype grade Raspberry Pi, and make the platform ready for customer beta trial. First, this …
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Dynamic Fleet Maintenance Management
… In this context, new technologies enable predictive maintenance to cover all activities from data acquisition and processing to maintenance decision-making advisory as output. This particularly expands to a wider view of ‘health management’ as opposed to a focus solely on maintenance at …
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Digital Twin for Photovoltaic System Maintenance Support
… Reducing downtime through monitoring and predictive maintenance enables earlier fault detection and improved decision-making for maintenance planning. This thesis presents a modular, holonic digital twin (DT) architecture for maintenance support of industrial PV plants. The proposed …
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Radiated Noise Assessment of Shipboard Systems Using Vibration Analysis
… signatures are minimal. Simultaneously, other predictive maintenance and load monitoring systems are installed on ships for better resource management. This work came from an idea to merge both worlds and used the predictive maintenance system to predict the radiated noise due to vibrations …
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