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by The digiLab Team

Updated 28 March 2024

digiLab Co-Host ML Workshop at the Henry Royce Institute

Exploring Machine Learning and twinLab for Forging, Advanced Materials, and Manufacturing
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digiLab recently co-hosted an ML workshop at the prestigious Royce Discovery Centre, bringing together industry and academia to explore the intersection of machine learning (ML) with the domains of forging, advanced materials, and manufacturing. The event drew representatives from key institutions including the Henry Royce Institute, Rolls Royce, the University of Strathclyde, the University of Manchester, WH Tildesley Ltd, and the University of Sheffield.

The workshop, focused on the application of ML to address critical challenges from component testing to supply chain risks, featured an array of sessions designed to spark discussion and innovation. Highlights included:

  • ML for Industry: An exploration of how machine learning technologies are transforming manufacturing processes, enhancing efficiency, and driving the development of advanced materials/alloys.
  • Gaussian Processes: A review of this powerful statistical tool for making predictions and recommendations in uncertain conditions, crucial for materials science.
  • Using twinLab for Materials Science: our ML tool that enables users to build advanced probabilistic machine learning models for simulations, experiments, and sensor data with ease, offering unprecedented capabilities in predictive analysis and uncertainty quantification.
  • The Role of ML in Cost Reduction and Efficiency: A session dedicated to demonstrating how ML technologies can significantly lower costs, save time, and boost confidence in manufacturing outcomes.
  • Utilizing LLMs for Organizational Knowledge Retrieval: A look at how large language models (LLMs) are enabling organizations to efficiently access and leverage vast archives of institutional knowledge.

This workshop not only showcased the latest data-driven engineering technologies but also underscored the critical role that industry leaders and ground-breaking academics are playing in pushing the boundaries of materials science and manufacturing. By bringing together experts from diverse sectors, digiLab has facilitated a multidisciplinary dialogue that promises to catalyze further advancements in these fields.

We're excited to see where things go next!

About digiLab

digiLab operates as the ML partner for industry, with a team of over 30 experts in ML, AI, data science, and software engineering. As the world increasingly adopts data-driven approaches, digiLab leads in areas where data is uncertain or sparse, where other techniques cannot perform. Taking a Bayesian view of the world, digiLab believes in the value of eliciting expert opinion from engineers and scientists, while capturing the inherent uncertainty in modelled systems to enable informed and optimum decision making. digiLab’s flagship offering is twinLab, the ML platform which enables engineers to build fast emulators with built-in uncertainty quantification, supported by our solution engineering team and ML skills training.

Get in-touch: info@digilab.co.uk

The digiLab Team
We are a 30+ strong team of ML Experts, Software Developers, Solution Engineers, and Product Experts. As a spinout from the University of Exeter, we build on years of cutting-edge academic research. At our core is a commitment to helping engineering and infrastructure companies become data-driven.

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