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Selecting spare parts suitable for additive manufacturing: A design science approach

Chaudhuri, Atanu; Gerlich, Hasse Andreas; Jayaram, Jayanth; Ghadge, Abhijeet; Shack, Johan; Brix, Benjamin Hvidberg; Hoffbeck, Lau Holst; Ulriksen, Nikoloaj Bog

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Authors

Hasse Andreas Gerlich

Jayanth Jayaram

Abhijeet Ghadge

Johan Shack

Benjamin Hvidberg Brix

Lau Holst Hoffbeck

Nikoloaj Bog Ulriksen



Abstract

Additive manufacturing (AM) help in delivering spare parts within short lead times and thus avoid maintaining huge inventories. Companies exploring opportunities to produce spare parts using AM face challenges in identifying suitable spare parts. Moreover, a single method may not be applicable for all companies. An idiosyncratic approach needs to be adopted by considering the characteristics of parts in the portfolio. This study follows a design science approach to address an evident research gap by developing a process to identify spare parts suitable for AM. The case data were analysed using multi-criteria decision-making and cluster analysis techniques. The research contributes by developing and demonstrating a methodology to identify spare parts suitable for AM from a portfolio of a large number of spare parts, where adequate discrimination was not obtained by ranking all parts together. The study develops generic guidelines for spare parts selection for AM and outline the generalizability of the proposed methodology beyond the domain of part selection for AM.

Citation

Chaudhuri, A., Gerlich, H. A., Jayaram, J., Ghadge, A., Shack, J., Brix, B. H., …Ulriksen, N. B. (2021). Selecting spare parts suitable for additive manufacturing: A design science approach. Production Planning and Control, 32(8), 670-687. https://doi.org/10.1080/09537287.2020.1751890

Journal Article Type Article
Acceptance Date Mar 31, 2020
Online Publication Date Apr 27, 2020
Publication Date 2021
Deposit Date Apr 17, 2020
Publicly Available Date Mar 28, 2024
Journal Production Planning and Control
Print ISSN 0953-7287
Electronic ISSN 1366-5871
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
Volume 32
Issue 8
Pages 670-687
DOI https://doi.org/10.1080/09537287.2020.1751890
Public URL https://durham-repository.worktribe.com/output/1303983

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