Selection of additive manufacturing technologies in productive systems: a decision support model

• Autor(a) principal: Calderaro,Douglas Rhoden
• Data de Publicação: 2020
• Outros Autores: Lacerda,Daniel Pacheco, Veit,Douglas Rafael
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Gestão & Produção
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0104-530X2020000300302
• topic: Additive Manufacturing; Competitive criteria; Production systems; Conjoint analysis; Analytic Hierarchy Process

Abstract: Additive Manufacturing (AM) has seen continued growth in adoption by organizations in recent years, changing production processes, supply chain, maintenance, product development and the global economy. There are several Additive Manufacturing technologies and equipment on the market, however, there are no guidelines, benchmarking or decision support tools for proper selection. After a systematic review of the literature, the lack of propositions that act during the development of the product and process was evidenced. This research focuses on the selection of Additive Manufacturing technologies for a production system. The general objective being to propose a decision support model based on the characteristics of additive technologies and competitive criteria, resulting in a choice aligned with the guidelines of organizations and their production systems. For the operationalization of the model, the AHP techniques and conjoint analysis were used together, where the characteristics of the Additive Manufacturing technologies were related to the competitive criteria for the model to indicate the recommended technology to the production system or organization in question. Finally, the artifact recommended the right technology in three distinct situations, from a vendor, user, and expert point of view. Thus, this research contributes to both academia and business by developing a functional artifact of additive manufacturing technology selection. Also, by contributing to the increased availability of information on the nine most commonly used additive technologies in industry.