IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i22p14847-d968987.html
   My bibliography  Save this article

Industry 5.0 and the Circular Economy: Utilizing LCA with Intelligent Products

Author

Listed:
  • Chris Turner

    (Surrey Business School, University of Surrey, Guildford GU2 7XH, UK)

  • John Oyekan

    (Department of Automatic Control and Systems Engineering, University of Sheffield, Portobello Street, Sheffield S1 3JD, UK)

  • Wolfgang Garn

    (Surrey Business School, University of Surrey, Guildford GU2 7XH, UK)

  • Cian Duggan

    (Carbon Intelligence, 5th Floor, 103-113 Regent Street, London W1B 4HL, UK)

  • Khaled Abdou

    (Carbon Intelligence, 5th Floor, 103-113 Regent Street, London W1B 4HL, UK)

Abstract

While the move towards Industry 4.0 has motivated a re-evaluation of how a manufacturing organization should operate in light of the availability of a new generation of digital production equipment, the new emphasis is on human worker inclusion to provide decision making activities or physical actions (at decision nodes) within an otherwise automated process flow; termed by some authors as Industry 5.0 and seen as related to the earlier Japanese Society 5.0 concept (seeking to address wider social and environmental problems with the latest developments in digital system, artificial Intelligence and automation solutions). As motivated by the EU the Industry 5.0 paradigm can be seen as a movement to address infrastructural resilience, employee and environmental concerns in industrial settings. This is coupled with a greater awareness of environmental issues, especially those related to Carbon output at production and throughout manufactured products lifecycle. This paper proposes the concept of dynamic Life Cycle Assessment (LCA), enabled by the functionality possible with intelligent products. A particular focus of this paper is that of human in the loop assisted decision making for end-of-life disassembly of products and the role intelligent products can perform in achieving sustainable reuse of components and materials. It is concluded by this research that intelligent products must provide auditable data to support the achievement of net zero carbon and circular economy goals. The role of the human in moving towards net zero production, through the increased understanding and arbitration powers over information and decisions, is paramount; this opportunity is further enabled through the use of intelligent products.

Suggested Citation

  • Chris Turner & John Oyekan & Wolfgang Garn & Cian Duggan & Khaled Abdou, 2022. "Industry 5.0 and the Circular Economy: Utilizing LCA with Intelligent Products," Sustainability, MDPI, vol. 14(22), pages 1-21, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14847-:d:968987
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/22/14847/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/22/14847/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dimitris Mourtzis & John Angelopoulos & Nikos Panopoulos, 2022. "A Literature Review of the Challenges and Opportunities of the Transition from Industry 4.0 to Society 5.0," Energies, MDPI, vol. 15(17), pages 1-29, August.
    2. Brondi, Sonia & Pivetti, Monica & Di Battista, Silvia & Sarrica, Mauro, 2021. "What do we expect from robots? Social representations, attitudes and evaluations of robots in daily life," Technology in Society, Elsevier, vol. 66(C).
    3. Ostheimer, Julia & Chowdhury, Soumitra & Iqbal, Sarfraz, 2021. "An alliance of humans and machines for machine learning: Hybrid intelligent systems and their design principles," Technology in Society, Elsevier, vol. 66(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Weidong & Zuo, Na & He, Wu & Li, Songtao & Yu, Lu, 2021. "Factors influencing the use of artificial intelligence in government: Evidence from China," Technology in Society, Elsevier, vol. 66(C).
    2. Hsing-Chun Hung & Yuh-Wen Chen, 2023. "Striving to Achieve United Nations Sustainable Development Goals of Taiwanese SMEs by Adopting Industry 4.0," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    3. Dario Krpan & Jonathan E. Booth & Andreea Damien, 2023. "The positive–negative–competence (PNC) model of psychological responses to representations of robots," Nature Human Behaviour, Nature, vol. 7(11), pages 1933-1954, November.
    4. Xing, Xinyu & Song, Mengmeng & Duan, Yucong & Mou, Jian, 2022. "Effects of different service failure types and recovery strategies on the consumer response mechanism of chatbots," Technology in Society, Elsevier, vol. 70(C).
    5. Zhang, Lixuan & Yencha, Christopher, 2022. "Examining perceptions towards hiring algorithms," Technology in Society, Elsevier, vol. 68(C).
    6. Padmanathan Kasinathan & Rishi Pugazhendhi & Rajvikram Madurai Elavarasan & Vigna Kumaran Ramachandaramurthy & Vinoth Ramanathan & Senthilkumar Subramanian & Sachin Kumar & Kamalakannan Nandhagopal & , 2022. "Realization of Sustainable Development Goals with Disruptive Technologies by Integrating Industry 5.0, Society 5.0, Smart Cities and Villages," Sustainability, MDPI, vol. 14(22), pages 1-31, November.
    7. Dimitris Mourtzis & John Angelopoulos & Nikos Panopoulos, 2023. "The Future of the Human–Machine Interface (HMI) in Society 5.0," Future Internet, MDPI, vol. 15(5), pages 1-25, April.
    8. Uzir, Md Uzir Hossain & Al Halbusi, Hussam & Lim, Rodney & Jerin, Ishraq & Abdul Hamid, Abu Bakar & Ramayah, Thurasamy & Haque, Ahasanul, 2021. "Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19," Technology in Society, Elsevier, vol. 67(C).
    9. Aymerich-Franch, Laura & Ferrer, Iliana, 2022. "Liaison, safeguard, and well-being: Analyzing the role of social robots during the COVID-19 pandemic," Technology in Society, Elsevier, vol. 70(C).
    10. Mateusz Malarczyk & Mateusz Zychlewicz & Radoslaw Stanislawski & Marcin Kaminski, 2023. "Electric Drive with an Adaptive Controller and Wireless Communication System," Future Internet, MDPI, vol. 15(2), pages 1-20, January.
    11. Turja, Tuuli & Särkikoski, Tuomo & Koistinen, Pertti & Melin, Harri, 2022. "Basic human needs and robotization: How to make deployment of robots worthwhile for everyone?," Technology in Society, Elsevier, vol. 68(C).
    12. Hassan Alimam & Giovanni Mazzuto & Marco Ortenzi & Filippo Emanuele Ciarapica & Maurizio Bevilacqua, 2023. "Intelligent Retrofitting Paradigm for Conventional Machines towards the Digital Triplet Hierarchy," Sustainability, MDPI, vol. 15(2), pages 1-30, January.
    13. Nam, Jinyoung & Kim, Junghwan & Jung, Yoonhyuk, 2023. "Understandings of the AI business ecosystem in South Korea: AI startups' perspective," 32nd European Regional ITS Conference, Madrid 2023: Realising the digital decade in the European Union – Easier said than done? 278005, International Telecommunications Society (ITS).
    14. Catherine Marinagi & Panagiotis Reklitis & Panagiotis Trivellas & Damianos Sakas, 2023. "The Impact of Industry 4.0 Technologies on Key Performance Indicators for a Resilient Supply Chain 4.0," Sustainability, MDPI, vol. 15(6), pages 1-31, March.
    15. Muhammad Zafar Yaqub & Abdullah Alsabban, 2023. "Industry-4.0-Enabled Digital Transformation: Prospects, Instruments, Challenges, and Implications for Business Strategies," Sustainability, MDPI, vol. 15(11), pages 1-33, May.
    16. Ardiansyah Putra, 2023. "The Literature Review Analysis of The Human Resources Development in The Industry Era 4.0 Towards The Era of society 5.0," Technium, Technium Science, vol. 20(1), pages 16-24.
    17. Liu, Yun & Wang, Xingyuan & Wang, Shuyang, 2022. "Research on service robot adoption under different service scenarios," Technology in Society, Elsevier, vol. 68(C).
    18. Wanxin He & Jianhua Fu & Youxi Luo, 2023. "A Study of Well-Being-Based Eco-efficiency Based on Super-SBM and Tobit Regression Model: The Case of China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 167(1), pages 289-317, June.
    19. Balsalobre-Lorente, Daniel & Contente dos Santos Parente, Clara & Leitão, Nuno Carlos & Cantos-Cantos, José María, 2023. "The influence of economic complexity processes and renewable energy on CO2 emissions of BRICS. What about industry 4.0?," Resources Policy, Elsevier, vol. 82(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14847-:d:968987. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.