Bayesian Based Predictive Analytics For Manufacturing Performance Metrics In The Era Of Industry 4 0
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Bayesian Based Predictive Analytics For Manufacturing Performance Metrics In The Era Of Industry 4 0
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Author : Salehi, Mehdi
language : en
Publisher: KIT Scientific Publishing
Release Date : 2019-10-10
Bayesian Based Predictive Analytics For Manufacturing Performance Metrics In The Era Of Industry 4 0 written by Salehi, Mehdi and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-10 with Technology & Engineering categories.
Quality In The Era Of Industry 4 0
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Author : Kai Yang
language : en
Publisher: John Wiley & Sons
Release Date : 2024-01-24
Quality In The Era Of Industry 4 0 written by Kai Yang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-24 with Technology & Engineering categories.
Enables readers to use real-world data from connected devices to improve product performance, detect design vulnerabilities, and design better solutions Quality in the Era of Industry 4.0 provides an insightful guide in harnessing user performance and behavior data through AI and other Industry 4.0 technologies. This transformative approach enables companies not only to optimize products and services in real-time, but also to anticipate and mitigate likely failures proactively. In a succinct and lucid style, the book presents a pioneering framework for a new paradigm of quality management in the Industry 4.0 landscape. It introduces groundbreaking techniques such as utilizing real-world data to tailor products for superior fit and performance, leveraging connectivity to adapt products to evolving needs and use-cases, and employing cutting-edge manufacturing methods to create bespoke, cost-effective solutions with greater efficiency. Case examples featuring applications from the automotive, mobile device, home appliance, and healthcare industries are used to illustrate how these new quality approaches can be used to benchmark the product’s performance and durability, maintain smart manufacturing, and detect design vulnerabilities. Written by a seasoned expert with experience teaching quality management in both corporate and academic settings, Quality in the Era of Industry 4.0 covers sample topics such as: Evolution of quality through industrial revolutions, from ancient times to the first and second industrial revolutions Quality by customer value creation, explaining differences in producers, stakeholders, and customers in the new digital age, along with new realities brought by Industry 4.0 Data quality dimensions and strategy, data governance, and new talents and skill sets for quality professionals in Industry 4.0 Automated product lifecycle management, predictive quality control, and defect prevention using technologies like smart factories, IoT, and sensors Quality in the Era of Industry 4.0 is a highly valuable resource for product engineers, quality managers, quality engineers and quality consultants, industrial engineers, and systems engineers who wish to make a participatory approach towards data-driven design, economical mass-customization, and late differentiation.
Production Planning And Control In Semiconductor Manufacturing
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Author : Tin-Chih Toly Chen
language : en
Publisher: Springer Nature
Release Date : 2022-09-19
Production Planning And Control In Semiconductor Manufacturing written by Tin-Chih Toly Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-19 with Technology & Engineering categories.
This book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. It reports in real examples and presents case studies as supporting evidence. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing. However, related research results are mostly scattered in various journal issues or conference proceedings, and there is an urgent need for a systematic integration of these results. In addition, many related discussions have placed too much emphasis on the theoretical framework of information systems rather than on the needs of semiconductor manufacturing management. This book addresses these issues.
Predictive Maintenance In Smart Factories
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Author : Tania Cerquitelli
language : en
Publisher: Springer Nature
Release Date : 2021-08-26
Predictive Maintenance In Smart Factories written by Tania Cerquitelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-26 with Science categories.
This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.
Implementing Industry 4 0
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Author : Carlos Toro
language : en
Publisher: Springer Nature
Release Date : 2021-04-03
Implementing Industry 4 0 written by Carlos Toro and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-03 with Technology & Engineering categories.
This book relates research being implemented in three main research areas: secure connectivity and intelligent systems, real-time analytics and manufacturing knowledge and virtual manufacturing. Manufacturing SMEs and MNCs want to see how Industry 4.0 is implemented. On the other hand, groundbreaking research on this topic is constantly growing. For the aforesaid reason, the Singapore Agency for Science, Technology and Research (A*STAR), has created the model factory initiative. In the model factory, manufacturers, technology providers and the broader industry can (i) learn how I4.0 technologies are implemented on real-world manufacturing use-cases, (ii) test process improvements enabled by such technologies at the model factory facility, without disrupting their own operations, (iii) co-develop technology solutions and (iv) support the adoption of solutions at their everyday industrial operation. The book constitutes a clear base ground not only for inspiration of researchers, but also for companies who will want to adopt smart manufacturing approaches coming from Industry 4.0 in their pathway to digitization.
Guide To Industrial Analytics
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Author : Richard Hill
language : en
Publisher: Springer Nature
Release Date : 2021-09-27
Guide To Industrial Analytics written by Richard Hill and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-27 with Computers categories.
This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.
Cloud Analytics For Industry 4 0
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Author : Sirisha Potluri
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-10-03
Cloud Analytics For Industry 4 0 written by Sirisha Potluri and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-03 with Business & Economics categories.
This book provides research on the state-of-the-art methods for data management in the fourth industrial revolution, with particular focus on cloud.based data analytics for digital manufacturing infrastructures. Innovative techniques and methods for secure, flexible and profi table cloud manufacturing will be gathered to present advanced and specialized research in the selected area.
The Digital Shopfloor Industrial Automation In The Industry 4 0 Era
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Author : John Soldatos
language : en
Publisher: CRC Press
Release Date : 2022-09-01
The Digital Shopfloor Industrial Automation In The Industry 4 0 Era written by John Soldatos and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Technology & Engineering categories.
In today’s competitive global environment, manufacturers are offered with unprecedented opportunities to build hyper-efficient and highly flexible plants, towards meeting variable market demand, while at the same time supporting new production models such as make-to-order (MTO), configure-to-order (CTO) and engineer-to-order (ETO). During the last couple of years, the digital transformation of industrial processes is propelled by the emergence and rise of the fourth industrial revolution (Industry4.0). The latter is based on the extensive deployment of Cyber-Physical Production Systems (CPPS) and Industrial Internet of Things (IIoT) technologies in the manufacturing shopfloor, as well as on the seamless and timely exchange of digital information across supply chain participants. The benefits of Industry 4.0 have been already proven in the scope of pilot and production deployments in a number of different use cases including flexibility in automation, predictive maintenance, zero defect manufacturing and more. Despite early implementations and proof-of-concepts, CPPS/IIoT deployments are still in their infancy for a number of reasons, including:• Manufacturers’ poor awareness about digital manufacturing solutions and their business value potential, as well as the lack of relevant internal CPPS/IIoT knowledge.• The high costs that are associated with the deployment, maintenance and operation of CPPS systems in the manufacturing shopfloors, which are particularly challenging in the case of SME (Small Medium Enterprises) manufacturers that lack the equity capital needed to invest in Industry 4.0.• The time needed to implement CPPS/IIoT and the lack of a smooth and proven migration path from existing OT solutions.• The uncertainty over the business benefits and impacts of IIoT and CPPS technologies, including the lack of proven methods for the techno-economic evaluation of Industry4.0 systems. • Manufacturers’ increased reliance on external integrators, consultants and vendors. • The absence of a well-developed value chain needed to sustain the acceptance of these new technologies for digital automation.In order to alleviate these challenges, three European Commission funded projects (namely H2020 FAR-EDGE (http://www.far-edge.eu/), H2020 DAEDALUS (http://daedalus.iec61499.eu) and H2020 AUTOWARE (http://www.autoware-eu.org/)) have recently joined forces towards a “Digital Shopfloor Alliance”. The Alliance aims at providing leading edge and standards based digital automation solutions, along with guidelines and blueprints for their effective deployment, validation and evaluation. The present book provides a comprehensive description of some of the most representative solutions that offered by these three projects, along with the ways these solutions can be combined in order to achieve multiplier effects and maximize the benefits of their use. The presented solutions include standards-based digital automation solutions, following different deployment paradigms, such as cloud and edge computing systems. Moreover, they also comprise a rich set of digital simulation solutions, which are explored in conjunction with the H2020 MAYA project (http://www.maya-euproject.com/). The latter facilitate the testing and evaluation of what-if scenarios at low risk and cost, but also without disrupting shopfloor operations. As already outlined, beyond leading edge scientific and technological development solutions, the book comprises a rich set of complementary assets that are indispensable to the successful adoption of IIoT/CPPS in the shopfloor. The book is structured in three parts as follows: • The first part of the book is devoted to digital automation platforms. Following an introduction to Industry 4.0 in general and digital automation platforms in particular, this part presents the digital automation platforms of the FAR-EDGE, AUTOWARE and DAEDALUS projects. • The second part of the book focuses on the presentation of digital simulation and digital twins’ functionalities. These include information about the models that underpin digital twins, as well as the simulators that enable experimentation with these processes over these digital models. • The third part of the book provides information about complementary assets and supporting services that boost the adoption of digital automation functionalities in the Industry4.0 era. Training services, migration services and ecosystem building services are discussed based on the results of the three projects of the Digital Shopfloor Alliance. The target audience of the book includes:• Researchers in the areas of Digital Manufacturing and more specifically in the areas of digital automation and simulation, who wish to be updated about latest Industry4.0 developments in these areas.• Manufacturers, with an interest in the next generation of digital automation solutions based on Cyber-Physical systems.• Practitioners and providers of Industrial IoT solutions, which are interested in the implementation of use cases in automation, simulation and supply chain management.• Managers wishing to understand technologies and solutions that underpin Industry4.0, along with representative applications in the shopfloor and across the supply chain.
Industry 4 0 Data Analytics
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Author : Rajesh Agnihotri
language : en
Publisher:
Release Date : 2012
Industry 4 0 Data Analytics written by Rajesh Agnihotri and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Intelligent Analytics For Industry 4 0 Applications
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Author : Avinash Chandra Pandey
language : en
Publisher:
Release Date : 2023
Intelligent Analytics For Industry 4 0 Applications written by Avinash Chandra Pandey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Decision making categories.
"The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and Artificial intelligence and machine learning, into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive sub-domains. To this end, the book will aim to review and highlight the challenges faced by Intelligent Analytics in Industry 4.0 and present the recent developments done to address those challenges"--