TY - JOUR
T1 - Selecting spare parts suitable for additive manufacturing
T2 - a design science approach
AU - Chaudhuri, Atanu
AU - Gerlich, Hasse Andreas
AU - Jayaram, Jayanth
AU - Ghadge, Abhijeet
AU - Shack, Johan
AU - Brix, Benjamin Hvidberg
AU - Hoffbeck, Lau Holst
AU - Ulriksen, Nikolaj
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Additive manufacturing
KW - cluster analysis
KW - design science
KW - multi-criteria decision-making
KW - spare parts selection
UR - http://www.scopus.com/inward/record.url?scp=85084259284&partnerID=8YFLogxK
U2 - 10.1080/09537287.2020.1751890
DO - 10.1080/09537287.2020.1751890
M3 - Journal article
AN - SCOPUS:85084259284
SN - 0953-7287
VL - 32
SP - 670
EP - 687
JO - Production Planning and Control
JF - Production Planning and Control
IS - 8
ER -