View in EDS HTML Full Text PDF Full Text

Additive manufacturing for operations and supply chain management: from technological promise to supply chain integration.

Saved in:
Bibliographic Details
Title: Additive manufacturing for operations and supply chain management: from technological promise to supply chain integration.
Authors: Peron, Mirco1 (AUTHOR) mirco.peron@neoma-bs.fr, Lolli, Francesco2 (AUTHOR), Bernard, Alain3 (AUTHOR), Kay, Michael4 (AUTHOR), Tiwari, Manoj5 (AUTHOR)
Source: International Journal of Production Research. May2026, Vol. 64 Issue 10, p3707-3717. 11p.
Subjects: Supply chain management, Operations management, Inventories, Intellectual property, Supply chain disruptions, Production planning, Innovation adoption, Rapid prototyping
Abstract: Additive manufacturing (AM) has emerged as a disruptive technology with the potential to reshape supply chain structures, enable on-demand production, and enhance resilience to disruptions. Yet its widespread adoption remains constrained by economic, operational, environmental, and intellectual property challenges. This special issue of the International Journal of Production Research brings together 21 papers that collectively advance the understanding of AM's role in operations and supply chain management. The contributions are organised into seven thematic areas: AM adoption decisions, supply chain resilience, spare parts and digital inventory, mobile AM and integrated production–delivery systems, scheduling and production planning, AM service platforms, and security and IP protection. Spanning analytical models, qualitative field studies, systematic reviews, and design science research across sectors including aerospace, automotive, healthcare, energy, and defence, the collection illustrates that realising AM's supply chain potential requires coordinated advances in technology, organisation, and supply chain design. This editorial introduces the special issue, synthesises the contributions, and identifies directions for future research. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 194394005
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Additive manufacturing for operations and supply chain management: from technological promise to supply chain integration.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Peron%2C+Mirco%22">Peron, Mirco</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mirco.peron@neoma-bs.fr</i><br /><searchLink fieldCode="AR" term="%22Lolli%2C+Francesco%22">Lolli, Francesco</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bernard%2C+Alain%22">Bernard, Alain</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kay%2C+Michael%22">Kay, Michael</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tiwari%2C+Manoj%22">Tiwari, Manoj</searchLink><relatesTo>5</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. May2026, Vol. 64 Issue 10, p3707-3717. 11p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Supply+chain+management%22">Supply chain management</searchLink><br /><searchLink fieldCode="DE" term="%22Operations+management%22">Operations management</searchLink><br /><searchLink fieldCode="DE" term="%22Inventories%22">Inventories</searchLink><br /><searchLink fieldCode="DE" term="%22Intellectual+property%22">Intellectual property</searchLink><br /><searchLink fieldCode="DE" term="%22Supply+chain+disruptions%22">Supply chain disruptions</searchLink><br /><searchLink fieldCode="DE" term="%22Production+planning%22">Production planning</searchLink><br /><searchLink fieldCode="DE" term="%22Innovation+adoption%22">Innovation adoption</searchLink><br /><searchLink fieldCode="DE" term="%22Rapid+prototyping%22">Rapid prototyping</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Additive manufacturing (AM) has emerged as a disruptive technology with the potential to reshape supply chain structures, enable on-demand production, and enhance resilience to disruptions. Yet its widespread adoption remains constrained by economic, operational, environmental, and intellectual property challenges. This special issue of the International Journal of Production Research brings together 21 papers that collectively advance the understanding of AM's role in operations and supply chain management. The contributions are organised into seven thematic areas: AM adoption decisions, supply chain resilience, spare parts and digital inventory, mobile AM and integrated production–delivery systems, scheduling and production planning, AM service platforms, and security and IP protection. Spanning analytical models, qualitative field studies, systematic reviews, and design science research across sectors including aerospace, automotive, healthcare, energy, and defence, the collection illustrates that realising AM's supply chain potential requires coordinated advances in technology, organisation, and supply chain design. This editorial introduces the special issue, synthesises the contributions, and identifies directions for future research. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=194394005
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/00207543.2026.2655024
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 3707
    Subjects:
      – SubjectFull: Supply chain management
        Type: general
      – SubjectFull: Operations management
        Type: general
      – SubjectFull: Inventories
        Type: general
      – SubjectFull: Intellectual property
        Type: general
      – SubjectFull: Supply chain disruptions
        Type: general
      – SubjectFull: Production planning
        Type: general
      – SubjectFull: Innovation adoption
        Type: general
      – SubjectFull: Rapid prototyping
        Type: general
    Titles:
      – TitleFull: Additive manufacturing for operations and supply chain management: from technological promise to supply chain integration.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Peron, Mirco
      – PersonEntity:
          Name:
            NameFull: Lolli, Francesco
      – PersonEntity:
          Name:
            NameFull: Bernard, Alain
      – PersonEntity:
          Name:
            NameFull: Kay, Michael
      – PersonEntity:
          Name:
            NameFull: Tiwari, Manoj
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 05
              Text: May2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 00207543
          Numbering:
            – Type: volume
              Value: 64
            – Type: issue
              Value: 10
          Titles:
            – TitleFull: International Journal of Production Research
              Type: main
ResultId 1