Manufacturing, whether subtractive and additive, requires complex operations and process rules are not so easy to structure or define. CAM software have been developed to foster the optimization of manufacturing tasks. However knowledge management systems (KMS) are still fighting to formalize manufacturing practices. This paper deals with Additive Manufacturing (AM) knowledge which is still in construction in industries. It aims at proposing approach and method for AM knowledge structuration. A case study about the influence of supports onto the quality of EBM (Electron Beam Melting) metallic parts enables us to confirm the benefits of a collective elicitation. Two elements contribute to its success: the use of an influence matrix and an argumentative situation between experts. Furthermore, four categories of AM knowledge are identified (definitions, examples, influences, and rules broken down in Action Rules and State Rules). They proved to be useful for identifying and structuring AM knowledge in our case study.