Abstract
Sustainability has received increased interest from academics in various domains. However, the role of ergonomics/human factors in sustainability related literature has not received the same level of interest, especially in the context of future research directions. For the advancement in the field of ergonomics/human factors, sustainability is critical to fulfilling the stakeholder's needs, putting eco-friendly and cost-effective arbitration into practice, and providing ergonomic solutions sensitive to human-wellbeing. This paper has identified the critical research areas in which ergonomics/human factors can amalgamate with sustainability using the unsupervised machine learning algorithm ‘Latent Dirichlet allocation’. The results show that the text mining technique effectively analyzes ergonomics/human factors discipline in sustainability. Furthermore, a conceptual framework is developed that identifies three potential research themes, which academicians and practitioners can apply as a good starting point for future research endeavors. In addition to that, this study also proposed a manufacturing system model for measuring performance based on Plan-Do-Check-Act (PDCA) cycle. Selections of lean, sustainability, and ergonomics/human factors tools are the key points for consideration when measuring performance on the proposed manufacturing system model stages.
| Original language | English |
|---|---|
| Article number | 102369 |
| Journal | Technology in Society |
| Volume | 75 |
| DOIs | |
| Publication status | Published - 21 Sept 2023 |
| Externally published | Yes |
Keywords
- Human factors and ergonomics
- Latent dirichlet allocation (LDA)
- Manufacturing performance
- Sustainability
- Sustainable development
- Text mining
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