Strategy for knowledge transfer in AM as a hybrid process chain towards a transition from prototyping to commercialisation

Abstract

Additive Manufacturing (AM) has gained considerable foot-print as one of the key components in making the 4th in-dustrial revolution a reality. Unlike traditional subtractive manufacturing processes which account for ~ 95% waste of material, AM provides almost unchallenged and sustainable manufacturing capabilities to drastically improve manufac-turing efficiency due to its nature of adding material as op-posed to removing it. Thereby, reducing life-cycle material mass and energy consumed. The ability to produce function-al 3D parts with customized and complex geometries direct-ly from CAD model data is particularly attractive. While metal AM processes such as laser powder bed fusion (L-PBF) are al-ready producing customized metal parts in applications such as dental implants, the full benefits of the technology have not been fully realized. This necessitates a global drive to learn best practices in AM towards new avenues for impact in teaching and learning, and in accelerated lab-to-market transition. The key to this is understanding inputs and out-puts of fundamental AM process parameters. This knowledge will help designers and potential end-users of the technolo-gy to quickly identify parameters which are most influential to structural integrity of parts produced. Considering that very little research has been performed on knowledge trans-fer among AM researchers, business and higher education, this paper is aimed at capacity building in AM technology by helping inexperienced users in higher education understand the technology better. Thereby, contributing to the inclusive global drive for an accelerated transition from prototyping to commercialization. The method used involves a stand-ard systematic triangulation of the literature to categorise and describe fundamental process parameters which influ-ence structural integrity of parts produced by the L-PBF. The findings of this work yield new knowledge in three domains. Firstly, the influential input parameters of L-PBF are identified as powder-specific, laser-specific and machine specific pa-rameters. Secondly, various post-processing solutions which are often used address the drawbacks associated with the technology are mapped out as thermodynamic, mechanical, and chemical post-processing treatments. Thirdly, the L-PBF is conceptualized into a framework which can help reshape the role of designers by identifying AM as a hybrid process and knowing what to look for when looking to make functional parts using technology. In this way, the paper contributes a novel skillset and attitude required to convert digital capabili-ties such as AM into valuable tools and methods.