Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Data mining seems to be a promising way to tackle the problem of unpredictability in MRO organizations. The Amsterdam University of Applied Sciences therefore cooperated with the aviation industry for a two-year applied research project exploring the possibilities of data mining in this area. Researchers studied more than 25 cases at eight different MRO enterprises, applying a CRISP-DM methodology as a structural guideline throughout the project. They explored, prepared and combined MRO data, flight data and external data, and used statistical and machine learning methods to visualize, analyse and predict maintenance. They also used the individual case studies to make predictions about the duration and costs of planned maintenance tasks, turnaround time and useful life of parts. Challenges presented by the case studies included time-consuming data preparation, access restrictions to external data-sources and the still-limited data science skills in companies. Recommendations were made in terms of ways to implement data mining - and ways to overcome the related challenges - in MRO. Overall, the research project has delivered promising proofs of concept and pilot implementations.

Data mining.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Data mining

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development.

Information visualization. --- Data mining.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

"A Microscopic, Telescopic, and Kaleidoscopic View of Data Science."

Data mining --- Big data

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

In recent years, a considerable amount of effort has been devoted, both in industry and academia, to improving maintenance. Time is a critical factor in maintenance, and efforts are placed to monitor, analyze, and visualize machine or asset data in order to anticipate to any possible failure, prevent damage, and save costs. The MANTIS Book aims to highlight the underpinning fundamentals of Condition-Based Maintenance related conceptual ideas, an overall idea of preventive maintenance, the economic impact and technical solution. The core content of this book describes the outcome of the Cyber-Physical System based Proactive Collaborative Maintenance project, also known as MANTIS, and funded by EU ECSEL Joint Undertaking under Grant Agreement nº 662189. The ambition has been to support the creation of a maintenance-oriented reference architecture that support the maintenance data lifecycle, to enable the use of novel kinds of maintenance strategies for industrial machinery. The key enabler has been the fine blend of collecting data through Cyber-Physical Systems, and the usage of machine learning techniques and advanced visualization for the enhanced monitoring of the machines. Topics discussed include, in the context of maintenance: Cyber-Physical Systems, Communication Middleware, Machine Learning, Advanced Visualization, Business Models, Future Trends. An important focus of the book is the application of the techniques in real world context, and in fact all the work is driven by the pilots, all of them centered on real machines and factories. This book is suitable for industrial and maintenance managers that want to implement a new strategy for maintenance in their companies. It should give readers a basic idea on the first steps to implementing a maintenance-oriented platform or information system.

Cooperating objects (Computer systems) --- Data mining --- Energy