Additive Manufacturing Working Group

 Motivation

  • Based on the many discussions during the VMAP User Forum 2025, we see that there is a great demand to standardize the data associated with additive manufacturing process.
  • Some of the VMAP SC Members are part of projects where there is a specific focus on additive manufacturing processes. Projects like Pioneer, Restore, Gear-Up, ALABAMA, Valid3D
  • Many of the project partners are actively seeking to start a working group where the community can come together and build some guidelines and standards for the storage of additive manufacturing data both simulation and measurement/monitoring.


Goals

  • Standardized Data Exchange between simulation and AM print machines : Seamless data exchange between simulation software using the VMAP format, allowing consistent and compatible export/import of material properties, boundary conditions, load cases, and results.
  • Interoperability with Multiphysics Software : In Multiphysics workflows (e.g., structural, thermal, fluid simulations), interoperability with other software like CFD tools is essential. Communication with simulation environments using VMAP enables streamlined multi-physics simulations.
  • Material Property Transfer : Simulation workflows often require transferring complex material models with various properties. The VMAP wrapper would standardize the data structure for seamless transfer between software.
  • Efficient Data Management : Facilitate data organization for easier storage, retrieval, and management in cloud or local environments. This is especially true for large-scale simulations or iterative design processes.
  • User-friendly interface for Engineers : A VMAP wrapper with an intuitive interface would facilitate quick integration into their workflow, reducing the learning curve and minimizing data transfer errors.
  • Data Structuring and Labeling : The VMAP wrapper should organize and label simulation data to meet ML model requirements by tagging variables (e.g., material properties, load conditions, results) and providing metadata. This structure allows ML algorithms to process data effectively without manual reformatting.
  • Bidirectional Data Flow : A robust VMAP wrapper should export simulation data to ML models and allow feedback from ML predictions back into the simulation. This creates iterative learning, where ML optimizes parameters and configurations in future runs.
  • Incorporating data from measurement and experiment to validate/calibrate (material) model


First Meeting

coming up soon...