Computer-Aided Optimisation in Additive Manufacturing Processes: A State of the Art Survey

Abstract

Additive manufacturing (AM) is a field with both industrial and academic significance. Computer-aided optimisation has brought advances to this field over the years, but challenges and areas of improvement still remain. Design to execution inaccuracies, void formation, material anisotropy, and surface quality are examples of remaining challenges. These challenges can be improved via some of the trending optimisation topics, such as artificial intelligence (AI) and machine learning (ML); STL correction, replacement, or removal; slicing algorithms; and simulations. This paper reviews AM and its history with a special focus on the printing process and how it can be optimised using computer software. The most important new contribution is a survey of the present challenges connected with the prevailing optimisation topics. This can be seen as a foundation for future research. In addition, we suggest how certain challenges can be improved and show how such changes affect the printing process.