Journal of Enterprise and Business Intelligence

Analysis of Human Performance in Manufacturing Framework of Industry 4.0

Journal of Enterprise and Business Intelligence

Received On : 02 May 2023

Revised On : 18 July 2023

Accepted On : 18 August 2023

Published On : 05 January 2024

Volume 04, Issue 01

Pages : 051-060


The phrase "Industry 4.0" refers to the fourth wave of industrial change, which includes areas like smart cities that aren't often thought of as stand-alone industrial applications. Water power, steam power, and mechanization were all introduced during the start of the first industrial revolution. The second industrial revolution that followed was marked by the expansion of mass production and assembly lines made possible by the use of electricity. The third industrial revolution was sparked by the development of electronics, information technology, and automation. This was followed by the fourth industrial revolution, which was defined by the appearance of systems of cyber-physical. The goal of the scientific discipline of human performance is to increase a system's overall performance as well as the wellbeing of the people who are a part of it. A comprehensive search yielded a total of 336 scholarly papers, out of which 37 were examined using a human-centered system of work paradigm as described in the body of HFE literature. Within the frames of the macro- and microergonomics work system paradigms, difficulties related to technological growth were analyzed. We outline the essential components of an organizational maturity model using the study that was done. Within the unique context of the manufacturing industry's fast technological improvements, this model seeks to improve the overall performance of sociotechnical work system.


Industry 4.0, Human Performance, Human Ergonomics and Factors, Micro and Macroergonomics Work System Frameworks, Technological Development in Manufacturing Industries.

  1. Z. M. Tanriogen, “The Possible Effects of 4th Industrial Revolution on Turkish Educational System,” Eurasian Journal of Educational Research, vol. 18, no. 77, pp. 1–22, Oct. 2018, doi: 10.14689/ejer.2018.77.9.
  2. M. Oppenheimer, “Designing obedience in the lab: Milgram’s shock simulator and human factors engineering,” Theory & Psychology, vol. 25, no. 5, pp. 599–621, Oct. 2015, doi: 10.1177/0959354315605392.
  3. P. Halmosi, “The Interpretation of Industry 4.0 by Hungarian Technology-Oriented Startups,” Timisoara Journal of Economics and Business, vol. 12, no. 2, pp. 149–164, Dec. 2019, doi: 10.2478/tjeb-2019-0008.
  4. S. “Pil” Kang and M. H. Molenda, “How Shall We Define Human Performance Technology?,” Performance Improvement Quarterly, vol. 31, no. 2, pp. 189–212, Jul. 2018, doi: 10.1002/piq.21276.
  5. H. D. Stolovitch, “Human performance technology: Research and theory to practice,” Performance Improvement, vol. 39, no. 4, pp. 7–16, Apr. 2000, doi: 10.1002/pfi.4140390407.
  6. A. Kochan, “Technology advancements enabling higher functionality and manufacturing flexibility drive European human machine interface markets,” Assembly Automation, vol. 24, no. 4, Dec. 2004, doi: 10.1108/aa.2004.03324dab.002.
  7. F. B. P. Moro, “Macroergonomics and Information Systems Development,” International Journal of Human-Computer Interaction, vol. 25, no. 5, pp. 414–429, Jun. 2009, doi: 10.1080/10447310902865016.
  8. B. M. Kleiner and C. G. Drury, “Large-scale regional economic development: Macroergonomics in theory and practice,” Human Factors and Ergonomics in Manufacturing, vol. 9, no. 2, pp. 151–163, 1999, [Online]. Available:<151::aid-hfm2>;2-g
  9. E. Haro and B. M. Kleiner, “Macroergonomics as an organizing process for systems safety,” Applied Ergonomics, vol. 39, no. 4, pp. 450–458, Jul. 2008, doi: 10.1016/j.apergo.2008.02.018.[
  10. W. Aaberg and C. J. Thompson, “Combining a human performance model and a Six Sigma model to assess performance in a military environment,” Performance Improvement, vol. 50, no. 1, pp. 36–48, Jan. 2011, doi: 10.1002/pfi.20193.
  11. D. Choi, “Quantum Technology and the Military-Revolution or Hype?: The Impact of Emerging Quantum Technologies on Future Warfare,” Expeditions with MCUP, vol. 2023, Sep. 2023, doi: 10.36304/expwmcup.2023.11.
  12. H. Benbya, T. H. Davenport, and S. Pachidi, “Artificial Intelligence in Organizations: Current State and Future Opportunities,” SSRN Electronic Journal, 2020, Published, doi: 10.2139/ssrn.3741983.
  13. M. Kefalaki and F. Diamantidaki, “Emerging trends in Media and Technology. Preface,” Emerging trends in Media and Technology, vol. 4, no. 2, Dec. 2022, doi: 10.34097/jeicom-4-2-december2022-0.
  14. T. H. Patten and J. G. Maurer, “Work Role Involvement of Industrial Supervisors.,” Industrial and Labor Relations Review, vol. 23, no. 3, p. 468, Apr. 1970, doi: 10.2307/2522133.
  15. B. Wahler, “Process Managing Operational Risk. Developing a Concept for Adapting Process Management to the Needs of Operational Risk in the Basel II-Framework,” SSRN Electronic Journal, 2005, Published, doi: 10.2139/ssrn.674221.
  16. M. Colli, U. Berger, M. Bockholt, O. Madsen, C. Møller, and B. V. Wæhrens, “A maturity assessment approach for conceiving context-specific roadmaps in the Industry 4.0 era,” Annual Reviews in Control, vol. 48, pp. 165–177, 2019, doi: 10.1016/j.arcontrol.2019.06.001.
  17. A. Myrodia, T. Randrup, and L. Hvam, “Configuration lifecycle management maturity model,” Computers in Industry, vol. 106, pp. 30–47, Apr. 2019, doi: 10.1016/j.compind.2018.12.006.
  18. H. Zhang, Y. Ouzrout, A. Bouras, and M. M. Savino, “Sustainability consideration within product lifecycle management through maturity models analysis,” International Journal of Services and Operations Management, vol. 19, no. 2, p. 151, 2014, doi: 10.1504/ijsom.2014.065330.
  19. I. Castelo-Branco, F. Cruz-Jesus, and T. Oliveira, “Assessing Industry 4.0 readiness in manufacturing: Evidence for the European Union,” Computers in Industry, vol. 107, pp. 22–32, May 2019, doi: 10.1016/j.compind.2019.01.007.
  20. T. K. Lepasepp and W. Hurst, “A Systematic Literature Review of Industry 4.0 Technologies within Medical Device Manufacturing,” Future Internet, vol. 13, no. 10, p. 264, Oct. 2021, doi: 10.3390/fi13100264.
  21. A. B. (Rami) Shani, R. M. Grant, R. Krishnan, and E. Thompson, “Advanced Manufacturing Systems and Organizational Choice: Sociotechnical System Approach,” California Management Review, vol. 34, no. 4, pp. 91–111, Jul. 1992, doi: 10.2307/41166705.
  22. S. Wang, Z. Cai, X. Si, and Y. Cui, “A Three-Dimensional Geological Structure Modeling Framework and Its Application in Machine Learning,” Mathematical Geosciences, vol. 55, no. 2, pp. 163–200, Oct. 2022, doi: 10.1007/s11004-022-10027-9.


We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


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Valeriya Chekalina, “Analysis of Human Performance in Manufacturing Framework of Industry 4.0”, Journal of Enterprise and Business Intelligence, vol.4, no.1, pp. 051-060, January 2024. doi: 10.53759/5181/JEBI202404006.


© 2024 Valeriya Chekalina. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.