Intelligent Systems Reference Library

Implementing Industry 4.0

The Model Factory as the Key Enabler for the Future of Manufacturing

Editors: Toro, Carlos, Wang, Wei, Akhtar, Humza (Eds.)

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  • Is the first book of its kind relating the real-world implementation of concepts related to smart manufacturing and Industry 4.0 adoption
  • Constitutes a clear base ground not only for inspiration of researchers, but also for companies who will want to adopt smart manufacturing approaches in their pathway to digitization
  • Comes from an industry pull – applied research perspective
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eBook $129.00
price for USA in USD
  • ISBN 978-3-030-67270-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-3-030-67269-0
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
About this book

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.


About the authors

Dr. Carlos Toro received both his Ph.D. And M.Sc. in Computer Science from the University of the Basque Country (Spain) and his Bachelor degree in Mechanical Engineering (with honors) from EAFIT University (Colombia). In 2003 he moved to Spain and started working in applied research focusing on Industrial and Advanced Manufacturing. At the same time, he lectured at the university of the Basque Country. In 2007 he was invited researcher at the University of Newcastle (Australia) returning in 2011 with a Marie Curie research visitor grant funded by the EU Commission.  Since 2017 he joined A*Star Singapore at their Advanced Remanufacturing and Technology Centre (ARTC) as Senior Technology Architect and research scientist for the Smart manufacturing Division.

Dr. Humza Akhtar is working in A*STAR as Group Manager in Advanced Remanufacturing and Technology Center (ARTC) since 2016 for Smart Manufacturing Group where he is leading a team of research scientists and software developers to create solutions for next generation manufacturing.

He has experience in end to end industry 4.0 solution development through IIoT and data analytics on edge and in cloud. He has also developed solutions for digital twin, factory simulation and immersive visualization through Virtual Reality.

He is also supporting a fast-growing startup Arcstone Pte Ltd as solutions architect for their new I4.0 product line. Humza completed his PhD from Nanyang Technological University in 2017 and the focus of his research was in data compression and optimization.

Dr. Wei Wang is the Coordinating Director of the Smart Manufacturing  Division for the Advanced Remanufacturing and Technology Centre's Smart Manufacturing Group. He is also the Senior Programme Manager of the Smart Manufacturing Joint Lab. Before joining ARTC, Dr Wang Wei held his position as Research Scientist with A*STAR's Institute of Materials Research & Engineering for nearly seven years. He then progressed and spent seven years on secondment with Rolls Royce as an Advanced Technologist.  Dr Wang Wei holds Bachelor in Materials Sciences and Engineering and also a Masters Degree in Engineering, Materials Science with Zhejiang University, China. Dr Wang Wei also received his PhD in Materials Engineering with The Nanyang Technological University (NTU), Singapore.

Table of contents (15 chapters)

Table of contents (15 chapters)
  • A Framework to Support Manufacturing Digitalization

    Pages 1-24

    Seif, Alejandro (et al.)

  • Real-Time Asset Tracking for Smart Manufacturing

    Pages 25-53

    Krishnan, Sivanand (et al.)

  • Unified IIoT Cloud Platform for Smart Factory

    Pages 55-78

    Tan, Shan Zheng (et al.)

  • A Perspective into Analysing Tool Wear Condition in Hard-Turning Process—The Key Lessons Learnt

    Pages 79-111

    Habibullah, Mohamed Salahuddin (et al.)

  • Condition Monitoring for Predictive Maintenance of Machines and Processes in ARTC Model Factory

    Pages 113-141

    Bahador, Amirabbas (et al.)

Buy this book

eBook $129.00
price for USA in USD
  • ISBN 978-3-030-67270-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $169.99
price for USA in USD
  • ISBN 978-3-030-67269-0
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Implementing Industry 4.0
Book Subtitle
The Model Factory as the Key Enabler for the Future of Manufacturing
Editors
  • Carlos Toro
  • Wei Wang
  • Humza Akhtar
Series Title
Intelligent Systems Reference Library
Series Volume
202
Copyright
2021
Publisher
Springer International Publishing
Copyright Holder
The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
eBook ISBN
978-3-030-67270-6
DOI
10.1007/978-3-030-67270-6
Hardcover ISBN
978-3-030-67269-0
Series ISSN
1868-4394
Edition Number
1
Number of Pages
XVIII, 418
Number of Illustrations
14 b/w illustrations, 209 illustrations in colour
Topics