Anderson Ferreira de Lima, Walter Cardoso Satyro, J. C. Contador, Marco Aurelio Fragomeni, R. F. Gonçalves, M. Martens, F. H. Pereira
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The “V” model for decision analysis of additive manufacturing implementation
PurposeThis study aims to broaden the understanding of the additive manufacturing (AM) body of knowledge, presenting a model better suited to the current level of technological development that supports the decision to implement AM in industries, based on the experience of companies in the industry of orthopedic medical implants.Design/methodology/approachBased on the design-science research, the model for the decision to adopt the AM was designed and submitted to experts from the industry of orthopedic implants in Brazil for refinement. For the empirical test of the final model, interviews were used in a company that was considering implementing AM and in another that was not, to evaluate the model.FindingsThe model considers seven dimensions for decision analysis of AM implementation: legal constraints, financial, technological, operational, organizational, supply chain and external factors, being subdivided into 42 criteria that play a relevant role in the implementation decision. The analysis factor of each dimension and criteria are also presented.Originality/valueThe model seeks to be as complete as possible and can be used by various industrial productive sectors, incorporating the analysis of the requirements of health regulatory agencies, suitable for the analysis of the decision to implement AM for the manufacturing of medical implants, not found in other models.
期刊介绍:
The Journal of Manufacturing Technology Management (JMTM) aspires to be the premier destination for impactful manufacturing-related research. JMTM provides comprehensive international coverage of topics pertaining to the management of manufacturing technology, focusing on bridging theoretical advancements with practical applications to enhance manufacturing practices.
JMTM seeks articles grounded in empirical evidence, such as surveys, case studies, and action research, to ensure relevance and applicability. All submissions should include a thorough literature review to contextualize the study within the field and clearly demonstrate how the research contributes significantly and originally by comparing and contrasting its findings with existing knowledge. Articles should directly address management of manufacturing technology and offer insights with broad applicability.