KNOWLEDGE-BASED EVALUATION OF PART ORIENTATION DESIRABILITY IN POWDER BED FUSION ADDITIVE MANUFACTURING

Abstract

AbstractIn powder bed fusion (PBF) additive manufacturing, the definition of part orientation is one of the most important steps as it affects the quality, the cost and the build time of products. Different works already attempted to propose methodologies for the assessment of optimal build orientation based on criteria such as the minimization of support volume. Elicitation works with industry experts have shown that they use much more varied rules to determine the orientation of parts. For instance, they do not treat the different surfaces of the part the same way (e.g., experts state that “priority surfaces of the part must be oriented close to vertical”). Today, the available tools do not allow integrating these kind of specifications. This paper discusses a knowledge-based methodology for the evaluation of part candidate orientations in PBF. Desirability function approach is used to translate companies’ expertise in the form action rules into mathematical functions that are tested on geometries to provide metrics for assisting the decision-making. A case study is presented to illustrate the use of this desirability function approach on complex part orientation problem.