Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectives

As global awareness of resource scarcity and environmental concerns grows, sustainable manufacturing practices have become imperative. Additive manufacturing (AM), with its high material efficiency and design flexibility, presents a promising pathway toward sustainable industrial transformation. Thi...

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Main Authors: Jinlong Su, Wei Long Ng, Jia An, Wai Yee Yeong, Chee Kai Chua, Swee Leong Sing
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Virtual and Physical Prototyping
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/17452759.2024.2438899
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author Jinlong Su
Wei Long Ng
Jia An
Wai Yee Yeong
Chee Kai Chua
Swee Leong Sing
author_facet Jinlong Su
Wei Long Ng
Jia An
Wai Yee Yeong
Chee Kai Chua
Swee Leong Sing
author_sort Jinlong Su
collection DOAJ
description As global awareness of resource scarcity and environmental concerns grows, sustainable manufacturing practices have become imperative. Additive manufacturing (AM), with its high material efficiency and design flexibility, presents a promising pathway toward sustainable industrial transformation. This review explores AM's role in sustainability across its lifecycle: design for AM, in AM, and after AM. In the design for AM phase, strategies such as topology optimisation, part consolidation, and cellular structures reduce material usage and enhance durability. During AM, in-situ process monitoring and closed-loop control improve process reliability, reducing energy consumption and failure rates. Meanwhile, the adoption of sustainable materials—metals, polymers, concretes, and biomaterials—further strengthens AM's potential to advance sustainability. After AM, applications such as repair, remanufacturing, and recycling extend product lifecycles and reduce environmental impact, aligning with circular economy principles. Future perspectives include the integration of artificial intelligence for in-process control and sustainable material development, along with regulatory and circular economy frameworks critical to sustainable AM deployment. Lastly, emerging research trends in advancing sustainability through AM are reviewed. Overall, this review provides a roadmap for academia and industry, offering strategies and insights to maximise AM's contribution to a more sustainable and responsible manufacturing future.
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spelling doaj-art-61d36aac73ec428fb8264f13ce6fdfe92024-12-10T03:30:56ZengTaylor & Francis GroupVirtual and Physical Prototyping1745-27591745-27672024-12-0119110.1080/17452759.2024.2438899Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectivesJinlong Su0Wei Long Ng1Jia An2Wai Yee Yeong3Chee Kai Chua4Swee Leong Sing5Department of Mechanical Engineering, National University of Singapore, SingaporeSingapore Centre for 3D Printing (SC3DP), School of Mechanical and Aerospace Engineering, Nanyang Technological University, SingaporeEngineering Product Development Pillar, Singapore University of Technology and Design, SingaporeSingapore Centre for 3D Printing (SC3DP), School of Mechanical and Aerospace Engineering, Nanyang Technological University, SingaporeEngineering Product Development Pillar, Singapore University of Technology and Design, SingaporeDepartment of Mechanical Engineering, National University of Singapore, SingaporeAs global awareness of resource scarcity and environmental concerns grows, sustainable manufacturing practices have become imperative. Additive manufacturing (AM), with its high material efficiency and design flexibility, presents a promising pathway toward sustainable industrial transformation. This review explores AM's role in sustainability across its lifecycle: design for AM, in AM, and after AM. In the design for AM phase, strategies such as topology optimisation, part consolidation, and cellular structures reduce material usage and enhance durability. During AM, in-situ process monitoring and closed-loop control improve process reliability, reducing energy consumption and failure rates. Meanwhile, the adoption of sustainable materials—metals, polymers, concretes, and biomaterials—further strengthens AM's potential to advance sustainability. After AM, applications such as repair, remanufacturing, and recycling extend product lifecycles and reduce environmental impact, aligning with circular economy principles. Future perspectives include the integration of artificial intelligence for in-process control and sustainable material development, along with regulatory and circular economy frameworks critical to sustainable AM deployment. Lastly, emerging research trends in advancing sustainability through AM are reviewed. Overall, this review provides a roadmap for academia and industry, offering strategies and insights to maximise AM's contribution to a more sustainable and responsible manufacturing future.https://www.tandfonline.com/doi/10.1080/17452759.2024.2438899Additive manufacturing3D printingsustainabilitylife cycle assessmentartificial intelligence
spellingShingle Jinlong Su
Wei Long Ng
Jia An
Wai Yee Yeong
Chee Kai Chua
Swee Leong Sing
Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectives
Virtual and Physical Prototyping
Additive manufacturing
3D printing
sustainability
life cycle assessment
artificial intelligence
title Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectives
title_full Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectives
title_fullStr Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectives
title_full_unstemmed Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectives
title_short Achieving sustainability by additive manufacturing: a state-of-the-art review and perspectives
title_sort achieving sustainability by additive manufacturing a state of the art review and perspectives
topic Additive manufacturing
3D printing
sustainability
life cycle assessment
artificial intelligence
url https://www.tandfonline.com/doi/10.1080/17452759.2024.2438899
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