A Study of Additive Manufacturing Technology as a Manufacturing Tool of the Automotive Industry

Abstract

Additive manufacturing technology has developed aggressively over recent years, and has been spotlighted as an innovative production method having potential to change the manufacturing businesses in a variety of industries. Particularly, in the automotive industry, AM technology has been recognized as an innovative manufacturing tool. This study introduces current cases of additive manufacturing applications in the automotive industry. The AM applications are classified according to manufacturing usage, such as prototype, mass-production and vehicles. Subsequently, we explain an assisting tool to help 3D printer users in the automotive industry who need to decide on the right pairing of AM machines and material, and the proper auto parts and tools, in a way that is effective and efficient In fact, the large sized automotive companies mostly operate a variety of AM machines to manufacture all sorts of vehicles components and tools. However, the engineers and designers experience difficulties selecting the appropriate AM machines with materials. This tool is developed to reduce trial errors which occur when the users select the proper pair of AM machine with material. The last section of this thesis includes a study on dimensional deformations in AM technology for the automotive industry. In particular, selective laser sintering (SLS) 3D printers, known to offer high engineering properties and durability of printed products, are popularly operated in vehicle development processes. However the SLS machine causes bending deformations due to thermal deformation. In this research, we aim to investigate and analyze the deformation patterns of SLS 3D printed samples depending on their measured surfaces on each X and Y direction and their locations in the build platform (3D Systems’ sPro60 SD). We also developed a compensating algorithm for minimizing the bending deformation in the SLS process by analyzing the quadratic regression model representing the bending deformations of samples numerically.