A decision-support framework for selecting additive manufacturing technologies
Journal of Manufacturing Technology Management
ISSN: 1741-038X
Article publication date: 19 July 2023
Issue publication date: 24 October 2023
Abstract
Purpose
This study provides an up-to-date review of additive manufacturing (AM) technologies and guidance for selecting the most appropriate ones for specific applications, taking into account the main features, strengths, and limitations of the existing options.
Design/methodology/approach
A literature review on AM technologies was conducted to assess the current state-of-the-art. This was followed by a closer examination of different AM machines to gain a deeper insight into their main features and operational characteristics. The conclusions and data gathered were used to formulate a classification and decision-support framework.
Findings
The findings indicate the building blocks of the selection process for AM technologies. Furthermore, this work shows the suitability of the existing AM technologies for specific cases and points to opportunities for technological and decision-support improvements. Lastly, more standardization in AM would be beneficial for future research.
Practical implications
The proposed framework offers valuable support for decision-makers to select the most suitable AM technologies, as demonstrated through practical examples of its utilization. In addition, it can help researchers identify the limitations of AM by pinpointing applications where existing technologies fail to meet the requirements.
Originality/value
The study offers a novel classification and decision-support framework for selecting AM technologies, incorporating machine characteristics, process features, physical properties of printed parts, and costs as key features to evaluate the potential of AM. Additionally, it provides a deeper understanding of these features as well as the potential opportunities for AM and its impact on various industries.
Keywords
Acknowledgements
This research was supported by the doctoral Grant SFRH/BD/151417/2021 financed by the Portuguese Foundation for Science and Technology (FCT), under the MIT Portugal Program, by FEDER funds through the program COMPETE – Programa Operacional Factores de Competitividade, by national funds through FCT under the project UID/EMS/00285/2020 and by the Operational Programme for Competitivity and Internationalization of Portugal 2020 Partnership Agreement (PRODUTECH4S&C), grant number POCI-01-0247-FEDER-046102. The initial idea for this work was conceived by João Maranha, Paulo Nascimento, Tomaz Calcerano and Samuel Moniz. Paulo Nascimento investigated the theory and took responsibility for designing and elaborating the framework, under the supervision of Samuel Moniz, with valuable inputs from Cristóvão Silva. Data collection and handling were performed by Paulo Nascimento, with support from João Maranha. Paulo Nascimento took the lead in writing the manuscript, assisted by João Maranha and supervised by Samuel Moniz. Cristóvão Silva and Stefanie Mueller provided critical feedback to enhance the manuscript’s quality. All authors contributed to the discussion of the results.
Citation
Maranha, J., Nascimento, P.J., Calcerano, T.A., Silva, C., Mueller, S. and Moniz, S. (2023), "A decision-support framework for selecting additive manufacturing technologies", Journal of Manufacturing Technology Management, Vol. 34 No. 7, pp. 1279-1311. https://doi.org/10.1108/JMTM-02-2023-0047
Publisher
:Emerald Publishing Limited
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