End-to-End Additive Manufacturing

I recently attended the Analyst Day for SIMULIA, the CAE simulation brand for Dassault Systèmés (DS). Simulation has been a long-term commitment for DS, and it has steadily expanded this area for many years from CATIA analysis to the acquisition of Abaqus and the formation of the SIMULIA brand in 2005. DS basically regards itself as scientific company, not just PLM, and their brands reflect this. SIMULIA is more than just simulation, but a Multiphysics (structural, thermal, fluid dynamics, etc.) and scientific solution set across multiple engineering, biological, chemical, and physics disciplines. Moreover, the SIMULIA brand now coordinates and complements DS brands like BIOVIA for bio-sciences and material science simulation at the molecular and quantum levels. This is the science-based approach they are bring to additive manufacturing.

While the main topics covered at this analyst day included simulation for the digital thread/twin and IoT, and electric car development, the area that I found very interesting and the focus for this blog was the end-to-end additive manufacturing (AM) and the AM strategy of a digitally connected, science-based simulation of this process.

Additive Manufacturing is a Process

What this end-to-end approach involves is producing printed parts with a process that begins with the material (metal powder, resins, etc.) and materials science-based simulation, and progresses to generative design, where the part geometry is based on the functional requirements of the part (Functional Generative Designer) and a design model is generated specifically to be printed.   Next comes process planning for manufacturing the part (Additive Manufacturing Programmer) which includes planning for the build plate configuration, support structures, slicing and scan path generation, and post processing for the printing machine tool path used.

What I found extremely significant in this AM process was that each step in the process from material composition, to generative design, to manufacturing planning, to programming could be simulated in 3D. The simulation was by process family whether it was powder bed fusion, direct energy deposition, or polymer extrusion, and 3D simulation of the vendor specific AM machine tool and path. The basic idea was to simulate any process, any material, and any machine.

Additionally, there was simulation for other post-processing functions such as removing the part from the build plate, distortion/shape compensation for heat treating and cooling, and cutter simulation for conventional machining processes for hybrid machine tools.

Multiple Scientific Disciplines Brought to the AM Process 

DS SIMULIA described the overall process as going from “atoms to parts”, in that it included a material microscale (before printing) to simulate material behavior and properties (thermal, mechanical, grain) and composition (metal, alloys, polymer, composite, ceramic). This is where the DS brand BIOVIA came into play with materials science simulation at the atomic level. Material evolution (during printing) involved simulation of the printing process like raw material melting and metallic transformation simulation, and material performance (after printing) like shape compensation and in-service fatigue simulation.

What I found most impressive was the combination of multiple scientific disciplines, like material science, generative design, process planning, and multi-physics based simulation. DS and its SIMULIA and BIOVIA brands appear to be taking AM process technology to another level.