Supply chain resilience and improving sustainability through additive manufacturing implementation: a systematic literature review and framework

Priyadarshini, Jaya; Kr Singh, Rajesh; Mishra, Ruchi; Chaudhuri, Atanu; Kamble, Sachin

Abstract

Additive manufacturing (AM) is rapidly transforming supply chains across various sectors. This study explores the current academic literature on AM applications in the supply chain and practitioner literature to explore the application of AM across various sectors. It then identifies AM’s role in achieving supply chain resilience and environmental sustainability. Key themes addressed in the literature have also been discussed. TCM (Theory, Characteristics and Methodology) framework has been used to identify the research gaps and provide future research directions. The study also proposes a research framework and propositions based on AM characteristics and capabilities required to achieve supply chain resilience and environmental sustainability through AM. This study extends the AM literature to present an integrated approach towards simultaneously achieving resilience and environmental sustainability. The study reveals how the AM characteristics of design freedom, part consolidation and on-demand tool-less manufacturing aid in achieving the twin benefits. The research propositions could be taken by researchers interested in exploring the field further. The findings of this study will enable the decision-makers contemplating adopting AM, in making informed decisions and be better prepared.

Citation

Priyadarshini, J., Kr Singh, R., Mishra, R., Chaudhuri, A., & Kamble, S. (2023). Supply chain resilience and improving sustainability through additive manufacturing implementation: a systematic literature review and framework. Production Planning and Control, https://doi.org/10.1080/09537287.2023.2267507

• Journal Article Type: Article
• Acceptance Date: Sep 3, 2023
• Online Publication Date: Oct 26, 2023
• Publication Date: 2023
• Deposit Date: Oct 30, 2023
• Publicly Available Date: Oct 27, 2024
• Journal: Production Planning and Control
• Print ISSN: 0953-7287
• Electronic ISSN: 1366-5871
• Publisher: Taylor and Francis Group
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1080/09537287.2023.2267507
• Public URL: https://durham-repository.worktribe.com/output/1871079