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Shared Additive Manufacturing Network for Metal Remanufacturing: Cost-aware Hub Distribution and Order Allocation

  • Muyue Han
  • , Jing Zhao
  • , Lingxiang Yun
  • , Anika Akther
  • , Yiran Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With an increasing emphasis on sustainability, remanufacturing has become essential in conserving resources and extending product lifecycles within the manufacturing sector. Additive manufacturing (AM) offers significant advantages for metal remanufacturing across industries such as aerospace, defense, and marine by providing flexible, precise repairs that surpass traditional methods. However, the high capital costs associated with in-house AM facilities pose substantial challenges for many small- and medium-sized enterprises (SMEs). Recent research highlights AM’s potential within a distributed manufacturing model, facilitating shared manufacturing capacity that allows multiple clients to access AM-based repair and restoration services without the financial burden of maintaining in-house facilities. Despite these benefits, research on designing and optimizing shared AM networks at a systems level remains limited. In this study, we develop a mathematical model to optimize AM hub locations and order allocation, considering variable repair orders from geographically distributed locations and associated transportation logistics. A case study of AM hubs serving the metal part remanufacturing needs of machine shops in the state of North Carolina in the U.S. is conducted to assess the effectiveness of the proposed method. The results demonstrate that strategically located AM hubs significantly enhance cost-efficiency within the shared network, providing SMEs affordable access to advanced AM resources and promoting a shift towards a circular economy.

Original languageEnglish (US)
Title of host publicationFunctional Devices/Bioinspired Structures; Sustainability; Semiconductor Manufacturing; Surface Engineering; Clean Energy and E-Mobility Manufacturing; Machining and Deformation Processes; Welding and Joining Processes of Advanced Materials and Structures; Equipment Design, Control and Automation; Human Integration to Smart Manufacturing Systems; Thin Films and Coatings; Meso, Micro, Nano Subtractive and Formative Manufacturing; Explainable AI for Knowledge Discovery
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791889022
DOIs
StatePublished - 2025
EventASME 2025 20th International Manufacturing Science and Engineering Conference, MSEC 2025 - Greenville, United States
Duration: Jun 23 2025Jun 27 2025

Publication series

NameProceedings of ASME 2025 20th International Manufacturing Science and Engineering Conference, MSEC 2025
Volume2

Conference

ConferenceASME 2025 20th International Manufacturing Science and Engineering Conference, MSEC 2025
Country/TerritoryUnited States
CityGreenville
Period6/23/256/27/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  3. SDG 14 - Life Below Water
    SDG 14 Life Below Water

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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