IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v233y2021ics0925527320303418.html
   My bibliography  Save this article

Industry 4.0 and the human factor – A systems framework and analysis methodology for successful development

Author

Listed:
  • Neumann, W. Patrick
  • Winkelhaus, Sven
  • Grosse, Eric H.
  • Glock, Christoph H.

Abstract

The fourth industrial revolution we currently witness changes the role of humans in operations systems. Although automation and assistance technologies are becoming more prevalent in production and logistics, there is consensus that humans will remain an essential part of operations systems. Nevertheless, human factors are still underrepresented in this research stream resulting in an important research and application gap. This article first exposes this gap by presenting the results of a focused content analysis of earlier research on Industry 4.0. To contribute to closing this gap, it then develops a conceptual framework that integrates several key concepts from the human factors engineering discipline that are important in the context of Industry 4.0 and that should thus be considered in future research in this area. The framework can be used in research and development to systematically consider human factors in Industry 4.0 designs and implementations. This enables the analysis of changing demands for humans in Industry 4.0 environments and contributes towards a successful digital transformation that avoid the pitfalls of innovation performed without attention to human factors. The paper concludes with highlighting future research directions on human factors in Industry 4.0 as well as managerial implications for successful applications in practice.

Suggested Citation

  • Neumann, W. Patrick & Winkelhaus, Sven & Grosse, Eric H. & Glock, Christoph H., 2021. "Industry 4.0 and the human factor – A systems framework and analysis methodology for successful development," International Journal of Production Economics, Elsevier, vol. 233(C).
  • Handle: RePEc:eee:proeco:v:233:y:2021:i:c:s0925527320303418
    DOI: 10.1016/j.ijpe.2020.107992
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527320303418
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2020.107992?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pedota, Mattia & Grilli, Luca & Piscitello, Lucia, 2023. "Technology adoption and upskilling in the wake of Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    2. Grybauskas, Andrius & Stefanini, Alessandro & Ghobakhloo, Morteza, 2022. "Social sustainability in the age of digitalization: A systematic literature Review on the social implications of industry 4.0," Technology in Society, Elsevier, vol. 70(C).
    3. Cannavacciuolo, Lorella & Ferraro, Giovanna & Ponsiglione, Cristina & Primario, Simonetta & Quinto, Ivana, 2023. "Technological innovation-enabling industry 4.0 paradigm: A systematic literature review," Technovation, Elsevier, vol. 124(C).
    4. Belhadi, Amine & Kamble, Sachin S. & Chiappetta Jabbour, Charbel Jose & Mani, Venkatesh & Khan, Syed Abdul Rehman & Touriki, Fatima Ezahra, 2022. "A self-assessment tool for evaluating the integration of circular economy and industry 4.0 principles in closed-loop supply chains," International Journal of Production Economics, Elsevier, vol. 245(C).
    5. Battaïa, Olga & Dolgui, Alexandre, 2022. "Hybridizations in line balancing problems: A comprehensive review on new trends and formulations," International Journal of Production Economics, Elsevier, vol. 250(C).
    6. Battini, Daria & Berti, Nicola & Finco, Serena & Zennaro, Ilenia & Das, Ajay, 2022. "Towards industry 5.0: A multi-objective job rotation model for an inclusive workforce," International Journal of Production Economics, Elsevier, vol. 250(C).
    7. Laubengaier, Désirée A. & Cagliano, Raffaella & Canterino, Filomena, 2022. "It Takes Two to Tango: Analyzing the Relationship between Technological and Administrative Process Innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    8. Heuser, Patricia & Tauer, Björn, 2023. "Single-machine scheduling with product category-based learning and forgetting effects," Omega, Elsevier, vol. 115(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:eee:proeco:v:233:y:2021:i:c:s0925527320303418. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.