Considerable investments are made in AM Research & Development to make high performance parts, research designs and materials, and optimize production processes. One of the central aims of this R&D is reducing the variability of processes and producing unique parts ‘right first time’, leaving no room for error. Progress in this area requires effective use of large quantities of specialist information. First, you must understand the fast-evolving landscape of machines and materials in order to set up a research or manufacturing project. These programs then generate huge amounts of data: material properties, process parameters, test data, simulation results, and on qualification of parts. How can we make best use of this data? And how can we best leverage process simulations, ensuring traceability for both virtual and test data?

To perfect our Additive Manufacturing processes, we must manage a magnitude of complex AM data, convert that into simulation-ready data, and deliver that information where it is needed. Simulation results need to be compared and calibrated to physical testing which can only be done successfully when information related to powders, builds, machine parameters, parts, and test information can be managed, visualized, and analyzed.

GRANTA MI can help to ensure that the history of your Additive Manufacturing testing and analysis is captured, providing full traceability and future-proofing Additive Manufacturing projects. To understand best practice for AM data management, see how GRANTA MI helps to fully understand the effect of your Additive Manufacturing materials and process parameters on the final part quality through the use of visualization and analysis tools.


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