The quality of an additive manufacturing product relies on processes that have been develop
Current additive manufacturing process planning for production relies heavily on knowledge gained through expensive trial and error processes. While such strategies work well for creating prototypes, they fall well short for the requirements for making functional or end-use parts. This presentation discusses some of the main challenges associated with manufacturing process planning and how variations in them can impact manufacturing yield. Then, we will discuss – through case studies – how, multiphysics simulation is bringing predictive analytics to the AM realm with a potential to unlock how parts are manufactured reliably.