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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.
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Chaudhuri et al. (2020) studied this question.
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