The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Industry 4.0 and the human factor – A systems framework and analysis methodology for successful development
Open accessAbstract
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.
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Cites
The Content Analysis Guidebook
Neuendorf, K. A. (2017) · doi:10.4135/9781071802878 · Cited by 9,286
Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014) · Business & Information Systems Engineering · doi:10.1007/s12599-014-0334-4 · Cited by 4,276
Industry 4.0: A survey on technologies, applications and open research issues
Lu, Y. (2017) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2017.04.005 · Cited by 3,012
Wang, G., Gunasekaran, A., Ngai, E. W. T., & Papadopoulos, T. (2016) · International Journal of Production Economics · doi:10.1016/j.ijpe.2016.03.014 · Cited by 1,545
The Principles of Sociotechnical Design
Cherns, A. (1976) · Human Relations · doi:10.1177/001872677602900806 · Cited by 1,063
Psychosocial work environment and stress-related disorders, a systematic review
Nieuwenhuijsen, K., Bruinvels, D., & Frings-Dresen, M. (2010) · Occupational Medicine · doi:10.1093/occmed/kqq081 · Cited by 696
The Relation between Work-related Psychosocial Factors and the Development of Depression
Netterstrom, B., Conrad, N., Bech, P., Fink, P., Olsen, O., Rugulies, R., & Stansfeld, S. (2008) · Epidemiologic Reviews · doi:10.1093/epirev/mxn004 · Cited by 467
Cited by
On Predictive Maintenance in Industry 4.0: Overview, Models, and Challenges
Achouch, M., Dimitrova, M., Ziane, K., Sattarpanah Karganroudi, S., Dhouib, R., Ibrahim, H., & Adda, M. (2022) · Applied Sciences · doi:10.3390/app12168081 · Cited by 528
Tseng, M.-L., Tran, T. P. T., Ha, H. M., Bui, T.-D., & Lim, M. K. (2021) · Journal of Industrial and Production Engineering · doi:10.1080/21681015.2021.1950227 · Cited by 341
Human factors and ergonomics in manufacturing in the industry 4.0 context – A scoping review
Reiman, A., Kaivo-oja, J., Parviainen, E., Takala, E.-P., & Lauraeus, T. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101572 · Cited by 261
Metadata
- Authors
- Neumann, W. P., Winkelhaus, S., Grosse, E. H., & Glock, C. H.
- Venue
- International Journal of Production Economics
- Publisher
- Elsevier BV
- Published
- 2021-03
- Volume
- 233
- Pages
- 107992
- ISSN
- 0925-5273 (ISSN-L)
- OpenAlex
- W3106795364
- Cited by
- 583
- References
- 7
- FWCI
- 47.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
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