Does your business depend on the properties of materials or their processing to create parts? Are you exploring new alloy designs? Or qualifying materials for safety-critical applications such as aerospace? Or implementing innovative technologies such as Additive Manufacturing?
In all of these examples, you need to optimize many parameters. And you must do this based on data from varied sources: experiment, in-process and in-service tests, simulation. When consolidated, this data is complex and has gaps. Multi-parameter problems with sparse data are what Alchemite does uniquely well. Find out how Alchemite will save you time, eliminate errors, and help you innovate in your use of materials and processes.
Alloys and superalloys
The Alchemite technology is proven for the design, development, and refinement of alloys and related processes. Examples include designing new alloys for aero engine applications and heat exchangers, and tackling difficult materials problems such as wear resistance.
How can we ensure reliable, repeatable AM processes? WIth Alchemite, get more from your data. Build models that identify which parameters are the most important and help you to understand uncertainties. And get guidance on which changes in your processing setup are most likely to give you better results.
Virtual experiments for steels
Chromium makes steel corrosion-resistant and hard, but is also toxic and costly. Replacing Chromium often relies on trial-and-error experimentation. Alchemite can run ‘virtual experiments’ to propose low-chromium steels with the right property profile.
Deep learning for materials development and additive manufacturing
Find out how machine learning methods are being applied to solve key problems in the design, characterization, and processing of metal alloys and other advanced materials, with a case study from an additive manufacturing (AM) project involving Intellegens, Boeing, and the AMRC.