Empowering Metal Additive Manufacturing through Simulation & Image-based Digital Twins
Wednesday, June 30, 2021 1:40 PM to 2:00 PM · 20 min. (Africa/Abidjan)
Stream#3
Information
Contributors:
Abstract:
Additive Manufacturing can be considered as a ‘slow revolution’ in industry. The potential advantages of the AM technology are clear, but the adoption of the technology in industry is progressing takes time, and can only progress step by step. Especially in the use of metal AM for highly regulated industries such as aerospace, users face several challenges. Among others, definition of optimized process settings for a particular geometry-material-machine combination and qualification of the process is a labor intensive process. After a short introduction to Materialise, this talk will present two important technologies that will play a major role in the further adoption of metal AM, namely simulation and data analytics. Yogesh Sovani will present how simulation plays a role in the different steps in the build preparation of AM. Tom Craeghs will introduce the Data Platform Materialise is working on, and will present more specifically how Image-Based Digital Twins of metal AM parts can be used for quality control purposes.
Abstract:
Additive Manufacturing can be considered as a ‘slow revolution’ in industry. The potential advantages of the AM technology are clear, but the adoption of the technology in industry is progressing takes time, and can only progress step by step. Especially in the use of metal AM for highly regulated industries such as aerospace, users face several challenges. Among others, definition of optimized process settings for a particular geometry-material-machine combination and qualification of the process is a labor intensive process. After a short introduction to Materialise, this talk will present two important technologies that will play a major role in the further adoption of metal AM, namely simulation and data analytics. Yogesh Sovani will present how simulation plays a role in the different steps in the build preparation of AM. Tom Craeghs will introduce the Data Platform Materialise is working on, and will present more specifically how Image-Based Digital Twins of metal AM parts can be used for quality control purposes.
