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

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  • 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
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    Cited by:

    1. Nadeem, Kashif & Wong, Sut I. & Za, Stefano & Venditti, Michelina, 2024. "Digital transformation and industry 4.0 employees: Empirical evidence from top digital nations," Technology in Society, Elsevier, vol. 76(C).
    2. 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).
    3. 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).
    4. 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).
    5. 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).
    6. 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).
    7. 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).
    8. 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).
    9. Heuser, Patricia & Tauer, Björn, 2023. "Single-machine scheduling with product category-based learning and forgetting effects," Omega, Elsevier, vol. 115(C).

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