| Title | Smart manufacturing as a strategic tool to mitigate sustainable manufacturing challenges: a case approach |
|---|---|
| ID_Doc | 18195 |
| Authors | Kannan, D; Gholipour, P; Bai, CG |
| Title | Smart manufacturing as a strategic tool to mitigate sustainable manufacturing challenges: a case approach |
| Year | 2023 |
| Published | Annals Of Operations Research, 331.0, 1 |
| Abstract | Due to the manufacturing sector's severe negative impacts on sustainable development, sustainable manufacturing is gaining more momentum than ever. Despite the advantages of sustainable manufacturing, academic literature resources report that practitioners still face several challenges while implementing sustainable manufacturing. To eliminate such challenges, numerous mitigation strategies have been proposed, including those that identify Industry 4.0 technologies as a key factor. However, current studies are generally more focused on the application of Industry 4.0 technologies/smart manufacturing in sustainable manufacturing; most fail to provide an in-depth understanding of how these technologies might mitigate the existing adoption challenges of sustainable manufacturing. In this study, the key challenges of sustainable manufacturing are identified through literature review and analyzed with MCDM tools such as the Best-Worst Method and WASPAS method. The results suggest that governmental challenge demonstrates the greatest weight in the final ranking, followed by technological and organizational challenges. Among the sub-challenges, "lack of support from the government in the form of regulations / policies" and "absence of subsidies and incentives" display the most weight. Further, a framework has been proposed to map the collected challenges with relevant mitigating smart manufacturing technologies to bridge the gap remaining from existing studies. Finally, this study contributes to the new field of approaching smart manufacturing as a mitigating strategy for sustainable manufacturing implementation through highlighting the implications and recommendations. |
| https://link.springer.com/content/pdf/10.1007/s10479-023-05472-6.pdf |
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