Decision-Making in Additive Manufacturing Supply Chains: A Systematic Literature Review

Additive Manufacturing (AM) is reshaping supply chain (SC) structures by enabling decentralised production, digital inventories, and on-demand manufacturing. These transformations demand new decision-making approaches to manage disruptions in SC configuration, inventory management, supplier selection, and manufacturing design. This study systematically reviews 27 peer-reviewed studies to assess decision-support tools—such as optimisation models, simulation techniques, and multi-criteria decision-making (MCDM) frameworks—used to facilitate AM integration. A structured mapping is proposed to map AM-induced SC changes to appropriate decision tools. The findings provide structured insights to enhance SC performance, adaptability, and resilience in AM-enabled environments.

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Publication Details

Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.09.113
Primary Topic
Additive Manufacturing and 3D Printing Technologies
Type
article
Field-Weighted Citation Impact
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article

Decision-Making in Additive Manufacturing Supply Chains: A Systematic Literature Review

Aristides Matopoulos, Banu Y. Ekren, Dana I. Abu-Abdoun
IFAC-PapersOnLine
Additive Manufacturing and 3D Printing Technologies
article

Decision-Making in Additive Manufacturing Supply Chains: A Systematic Literature Review

Aristides Matopoulos, Banu Y. Ekren, Dana I. Abu-Abdoun
article en

Abstract

Additive Manufacturing (AM) is reshaping supply chain (SC) structures by enabling decentralised production, digital inventories, and on-demand manufacturing. These transformations demand new decision-making approaches to manage disruptions in SC configuration, inventory management, supplier selection, and manufacturing design. This study systematically reviews 27 peer-reviewed studies to assess decision-support tools—such as optimisation models, simulation techniques, and multi-criteria decision-making (MCDM) frameworks—used to facilitate AM integration. A structured mapping is proposed to map AM-induced SC changes to appropriate decision tools. The findings provide structured insights to enhance SC performance, adaptability, and resilience in AM-enabled environments.

IFAC-PapersOnLineVol. 59(10)
Yaşar University (TR), Cranfield University (GB)
Openalex Percentile: Top 71%
Additive Manufacturing and 3D Printing Technologies
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