A Process-Centric View on Predictive Maintenance and Fleet Prognostics. Development of a Process Reference Model and a Development Method for Fleet Prognostics to Guide Predictive Maintenance Projects PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download A Process-Centric View on Predictive Maintenance and Fleet Prognostics. Development of a Process Reference Model and a Development Method for Fleet Prognostics to Guide Predictive Maintenance Projects PDF full book. Access full book title A Process-Centric View on Predictive Maintenance and Fleet Prognostics. Development of a Process Reference Model and a Development Method for Fleet Prognostics to Guide Predictive Maintenance Projects by Carolin Wagner. Download full books in PDF and EPUB format.
Author: Carolin Wagner
Publisher: Logos Verlag Berlin GmbH
ISBN: 3832555153
Category : Computers
Languages : en
Pages : 320
Get Book Here
Book Description
In the age of digitalization and the fourth industrial revolution, predictive maintenance is becoming increasingly important as a proactive maintenance type. Despite the economic benefits that predictive maintenance generates for companies, its practical application is still in its early stages. This is often due to two prevailing challenges. First, there is a deficiency of knowledge about predictive maintenance and its concrete realization. Second, there is a lack of high quality and rich data of historical machine failures. To increase the representativeness of data, data from several similar machines (i.e. a fleet) should be considered. To foster the effective implementation of predictive maintenance, supportive guidance in the realization of a predictive maintenance project is needed. For this reason, this dissertation presents a process reference model and a development method for fleet prognostics. The process reference model describes a comprehensive and application-independent view of the complete predictive maintenance process. The model is supplemented by the fleet prognostic development method. To address the specific characteristics of the fleet, a systematic process is depicted which provides a means to assess the heterogeneity of the fleet from a data-driven perspective and simplifies the design of an algorithm considering fleet data. Finally, the applicability and value of the research results are demonstrated with three industrial cases
Author: Carolin Wagner
Publisher: Logos Verlag Berlin GmbH
ISBN: 3832555153
Category : Computers
Languages : en
Pages : 320
Get Book Here
Book Description
In the age of digitalization and the fourth industrial revolution, predictive maintenance is becoming increasingly important as a proactive maintenance type. Despite the economic benefits that predictive maintenance generates for companies, its practical application is still in its early stages. This is often due to two prevailing challenges. First, there is a deficiency of knowledge about predictive maintenance and its concrete realization. Second, there is a lack of high quality and rich data of historical machine failures. To increase the representativeness of data, data from several similar machines (i.e. a fleet) should be considered. To foster the effective implementation of predictive maintenance, supportive guidance in the realization of a predictive maintenance project is needed. For this reason, this dissertation presents a process reference model and a development method for fleet prognostics. The process reference model describes a comprehensive and application-independent view of the complete predictive maintenance process. The model is supplemented by the fleet prognostic development method. To address the specific characteristics of the fleet, a systematic process is depicted which provides a means to assess the heterogeneity of the fleet from a data-driven perspective and simplifies the design of an algorithm considering fleet data. Finally, the applicability and value of the research results are demonstrated with three industrial cases
Author: Mikel Armendia
Publisher: Springer
ISBN: 303002203X
Category : Technology & Engineering
Languages : en
Pages : 298
Get Book Here
Book Description
This open access book summarizes the results of the European research project “Twin-model based virtual manufacturing for machine tool-process simulation and control” (Twin-Control). The first part reviews the applications of ICTs in machine tools and manufacturing, from a scientific and industrial point of view, and introduces the Twin-Control approach, while Part 2 discusses the development of a digital twin of machine tools. The third part addresses the monitoring and data management infrastructure of machines and manufacturing processes and numerous applications of energy monitoring. Part 4 then highlights various features developed in the project by combining the developments covered in Parts 3 and 4 to control the manufacturing processes applying the so-called CPSs. Lastly, Part 5 presents a complete validation of Twin-Control features in two key industrial sectors: aerospace and automotive. The book offers a representative overview of the latest trends in the manufacturing industry, with a focus on machine tools.
Author: Dimitris Kiritsis
Publisher: Frontiers Media SA
ISBN: 2889665836
Category : Science
Languages : en
Pages : 124
Get Book Here
Book Description
Author: Ali Soofastaei
Publisher: CRC Press
ISBN: 0429781776
Category : Computers
Languages : en
Pages : 273
Get Book Here
Book Description
Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors
Author: Khalid Al Marri
Publisher: Springer Nature
ISBN: 303156121X
Category :
Languages : en
Pages : 524
Get Book Here
Book Description
Author: Vijay Kumar
Publisher: CRC Press
ISBN: 1000332861
Category : Mathematics
Languages : en
Pages : 289
Get Book Here
Book Description
Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence. This book provides the most recent advances in the field along with case studies and real-world examples. It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management. It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest.
Author: Mircea Gh. Negoita
Publisher: Springer Science & Business Media
ISBN: 3540233180
Category : Business & Economics
Languages : en
Pages : 1337
Get Book Here
Book Description
Annotation The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004. The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.
Author: Petros Nicopolitidis
Publisher: Morgan Kaufmann
ISBN: 0128034637
Category : Technology & Engineering
Languages : en
Pages : 454
Get Book Here
Book Description
Smart Cities and Homes: Key Enabling Technologies explores the fundamental principles and concepts of the key enabling technologies for smart cities and homes, disseminating the latest research and development efforts in the field through the use of numerous case studies and examples. Smart cities use digital technologies embedded across all their functions to enhance the wellbeing of citizens. Cities that utilize these technologies report enhancements in power efficiency, water use, traffic congestion, environmental protection, pollution reduction, senior citizens care, public safety and security, literacy rates, and more. This book brings together the most important breakthroughs and advances in a coherent fashion, highlighting the interconnections between the works in different areas of computing, exploring both new and emerging computer networking systems and other computing technologies, such as wireless sensor networks, vehicle ad hoc networks, smart girds, cloud computing, and data analytics and their roles in creating environmentally friendly, secure, and prosperous cities and homes. Intended for researchers and practitioners, the book discusses the pervasive and cooperative computing technologies that will perform a central role for handling the challenges of urbanization and demographic change. - Includes case studies and contributions from prominent researchers and practitioners from around the globe - Explores the latest methodologies, theories, tools, applications, trends, challenges, and strategies needed to build smart cities and homes from the bottom up - Provides a pedagogy that includes PowerPoint slides, key terms, and a comprehensive bibliography
Author: Ovidiu Vermesan
Publisher: CRC Press
ISBN: 1000794318
Category : Medical
Languages : en
Pages : 435
Get Book Here
Book Description
This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.
Author: Josep Aulinas
Publisher: CRC Press
ISBN: 1000417166
Category : Computers
Languages : en
Pages : 129
Get Book Here
Book Description
Artificial Intelligence (AI) is undoubtedly playing an increasingly significant role in automobile technology. In fact, cars inhabit one of just a few domains where you will find many AI innovations packed into a single product. AI for Cars provides a brief guided tour through many different AI landscapes including robotics, image and speech processing, recommender systems and onto deep learning, all within the automobile world. From pedestrian detection to driver monitoring to recommendation engines, the book discusses the background, research and progress thousands of talented engineers and researchers have achieved thus far, and their plans to deploy this life-saving technology all over the world.
