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Analytics for the Sharing Economy: Mathematics, Engineering and Business Perspectives pp 309–333Cite as

Industry4.0

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Abstract

The fourth industrial revolution is already showing its disruptive potential in many fields, primarily in the manufacturing, logistics and energy sectors. It is expected to revolutionize production processes, business models and IT infrastructures: eventually, the supply chain will turn into more efficient, adaptable and scalable workflows, ultimately driven by a nearly real-time and utterly bespoke demand of new or enhanced products and services. Science is already supporting this transformation, mostly through its recent developments in AI, finally resulting in an exponential availability of approaches, methods and tools to support and boost it. An ever increasing availability of data, coming from different sources, generated by humans and machines are being fruitfully integrated and will ignite the Industry4.0 paradigm. Machines will be smarter, they will make decisions and trade resources and services using virtual currencies in the emerging framework of the Machine Economy.

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Notes

  1. 1.

    Software as a Service, Infrastructure as a Service, and Platform as a Service are different categories of services offered by cloud computing providers.

  2. 2.

    Due to aggressive return policies designed to increase customer satisfaction.

  3. 3.

    The TCPIP is the suite of standard software protocols needed to exchange information over the Internet.

  4. 4.

    G-code is one of the most popular languages used to program CNC machines: it includes elementary commands to be executed in a specific order (move the tool to a certain point, drill a hole, set a specific speed, etc.).

  5. 5.

    3D printing is an oversimplified example though, because it is essentially a 2D process iterated over a pre-determined number of layers. A more complex CNC machine operating in real 3D (like a multi-axis mill) often requires some—human-operated—fine tuning on the G-code before the actual object can be manufactured.

  6. 6.

    The first open source project of a low cost 3D printer was RepRap, started in 2005 in England (University of Bath).

  7. 7.

    This kind of interaction requires that users are able to use a CAD tool and generate the appropriate file to be uploaded.

  8. 8.

    For this kind of service a technology known as parametric design, which allows to generate CAD files that can be easily personalized by simply changing some parameters, is gaining a lot of popularity.

  9. 9.

    The use of the terms bits and atoms to indicate digital vs physical phenomena and activities was introduced by Prof. Neil Gershenfeld, director of the MIT Center for Bits and Atoms.

  10. 10.

    The range of possible modules is very wide, and an accurate set can be defined only on a case by case basis.

  11. 11.

    http://www.rashid/ae.

  12. 12.

    https://dubainow.dubai.ae.

  13. 13.

    DubaiID provides single identity (being linked to the Emirates Identity Authority) and single login to over 600 government services.

  14. 14.

    To be noticed here that, in a more general scenario, what we want to optimized is an objective function; optimization will take the form of maximizing the posterior probability (e.g. in a naive Bayes model), maximizing a reward function (e.g. in reinforcement learning), etc.

  15. 15.

    16–17 March 2017, Berlin. Panelists: Prof. Wolfgang Wahlster, DFKI, Germany (Chair); Prof. Paolo Traverso, FBK-irst, Italy (Co-Chair); Sahin Albayrak, GT-ARC, Turkey; Dr. Philippe Beaudoin, Element AI, Canada; Dr. Satoshi Sekiguchi, AIST, Japan.

  16. 16.

    In 2015 an interesting and promising proof of concept was developed at Retechnica Ltd. (a startup based in London) for a well-known British airline company, consisting in analyzing—through NLP techniques—tweets posted on the company’s Twitter page and triggering actions to be taken by different functions (marketing and sales, customer relationship, on-ground assistance, etc.).

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Author information

Authors and Affiliations

  1. Links Foundation, Via Pier Carlo Boggio 61, Torino, 10138, Italy

    Edoardo Calia

  2. World Green Economy Organization, Happiness Street, Dubai, UAE

    Davide D’Aprile

Authors
  1. Edoardo Calia
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  2. Davide D’Aprile
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Corresponding author

Correspondence to Edoardo Calia .

Editor information

Editors and Affiliations

  1. DESTEC, University of Pisa, Pisa, Italy

    Emanuele Crisostomi

  2. Ivey Business School, University of Western Ontario, London, Canada

    Bissan Ghaddar

  3. Moovel Group GmbH, Stuttgart, Germany

    Florian Häusler

  4. Ivey Business School, London, ON, Canada

    Joe Naoum-Sawaya

  5. Department of Information & Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano, Salerno, Italy

    Giovanni Russo

  6. Dyson School of Design Engineering, Imperial College London, London, UK

    Robert Shorten

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Calia, E., D’Aprile, D. (2020). Industry4.0. In: Crisostomi, E., Ghaddar, B., Häusler, F., Naoum-Sawaya, J., Russo, G., Shorten, R. (eds) Analytics for the Sharing Economy: Mathematics, Engineering and Business Perspectives. Springer, Cham. https://doi.org/10.1007/978-3-030-35032-1_18

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