Collaboration aims to advance additive manufacturing through machine learning

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A partnership aims to integrate machine learning methods into Additive Manufacturing (AM) workflows to accelerate the development of reliable and repeatable processes. 

Machine learning specialist Intellegens and engineering simulation software provider Ansys aim to provide ‘deliver deep insights to Additive Manufacturing workflows’ through the combination of software components. Intellegens’ machine learning technology, Alchemite, will be embedded within the Ansys materials data management platform, Granta MI.

Integrating these technologies will make it easier for engineers to analyse data and search for key process/property relationships and to continuously improve models as the data is updated.

Rob Davis, director of product management, at Ansys: ‘Intellegens’ machine learning technology offers a ready-made solution to key data analysis challenges faced by our Additive Manufacturing customers. Integration with Ansys Granta MI creates a unified workflow for capturing and applying results from AM testing, simulation, and production.’

The combination of the two companies’ technologies will make it quick and easy for AM project teams to analyse data from an experiment, simulation, or production - generating models that capture vital insights. These models are used to optimise process parameters and powders, improving the quality of AM parts while potentially cutting time to market.

Alchemite deep learning algorithms very rapidly find relationships within complex datasets, even when that data is ‘sparse’ (i.e., has many empty values). This makes Alchemite ideal for AM teams seeking to exploit data brought together from multiple sources. It extracts all possible knowledge from the data to identify the critical combinations of factors that ultimately control the performance of AM parts. 

Alchemite needs no prior knowledge of which parameters are likely to be important - a significant advantage in this emerging technology area. Applications throughout the AM workflow include:

  • Process parameter optimisation for AM processes
  • Computational design of AM materials
  • Failure analysis and quality control
  • Data validation and gap-filling
  • Assisted Design of Experiments (DoE) for AM

Granta MI is used for materials data management in engineering enterprises and is applied in AM applications to capture AM data. This includes data on the properties of powders and raw materials, machine build parameters, post-build processing data, test results for AM parts, and simulation data from the Ansys AM simulation suite. Integrating Alchemite into this system will make it easier for engineers to analyse the full range of this data in the search for key process/property relationships and to continuously improve models as the data is updated.

Dr Gareth Conduit, CTO at Intellegens: ‘Merging the data management capabilities of Ansys’ Granta MI with the machine learning prowess of Alchemite is a perfect fit, promising to deliver deep insights to Additive Manufacturing workflows. We look forward to working with the global Ansys network to deliver the benefits of machine learning to many more AM project teams.’

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10 June 2022

Staff Scientist Daniele Filippetto working on the High Repetition-Rate Electron Scattering Apparatus. (Credit: Thor Swift/Berkeley Lab)

03 August 2022

Credit: stockphoto mania/Shutterstock

10 June 2022