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

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: Apr 17, 2020
• 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