Although additive manufacturing (AM) has been demonstrated to have significant potential in improving spare part delivery operations and has been adopted to a degree in the aviation and automotive industries, its use in spare part production is still limited in other fields due to a variety of implementation barriers. The purpose of this article is to assess the significance of previously reported barriers in the context of the machine-building industry.
Adoption barriers are identified from the literature and formulated as hypotheses, which are verified with a set of focus group interviews consisting of original equipment manufacturers (OEMs), AM service providers and quality inspection and insurance institutions. The results of the interviews are reported qualitatively, and the transcripts of the interviews are subjected to quantitative content analysis.
The article identifies distrust in quality, insufficient material and design knowledge among stakeholders and poor availability of design documentation on spare parts as the key barriers of adopting AM in the production of spare parts. The three key barriers are interconnected and training engineers to be proficient in design and material issues as well as producing high-quality design documentation will yield the highest increase in AM implementation in spare parts.
The article offers a unique approach as it investigates the subjective views of a cross-organizational group of industrial actors involved in the machine-building industry. The article contributes to the theory of digital spare parts by verifying and rejecting presented barriers of AM implementation and how they are interconnected.
The study was conducted as part of the Business from Digital Spare Parts (DIVALIITO) project funded by a consortium of companies and Business Finland.
Chekurov, S., Salmi, M., Verboeket, V., Puttonen, T., Riipinen, T. and Vaajoki, A. (2021), "Assessing industrial barriers of additively manufactured digital spare part implementation in the machine-building industry: a cross-organizational focus group interview study", Journal of Manufacturing Technology Management, Vol. 32 No. 4, pp. 909-931. https://doi.org/10.1108/JMTM-06-2020-0239
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