Batteries manufacturing made smarter: Digital technologies and AI for the new Advanced Materials Battery Industrialisation Centre (AMBIC)
Event Details
Discover the digital technologies that can improve battery manufacturing
Batteries manufacturing is a complex process that heavily relies on operator experience. Digital technologies, AI, and simulation can help make products faster and more sustainably, reducing costs and increasing product quality. In this webinar, we will explore techniques that cover material development and design as well as the manufacturing process itself to showcase the impact digital technologies can have. The focus will be on applied and industry-tested solutions.
We will explore the following topics:
- Introduction to the UK’s new Advanced Materials Battery Industrialisation Centre (AMBIC), opening early 2025.
- Digitalisation for batteries manufacturing: Cost-effective approaches for predictive modelling of products and processes.
- AI and machine learning for battery manufacturing.
- Adaptive design of experiments (DoE) for batteries development.
- Advanced image analysis techniques for material design.
Agenda and timings for each speaker:
Time | Description | Person | Duration |
13:30 | Introduction to the Advanced Materials Battery Industrialisation Centre | Keri Goodwin, CPI | 5 mins |
13:35 | Digital technologies for battery manufacturing | Katharina Roettger, CPI | 10 mins |
13:45 | AI/ML model for batteries manufacturing | Mona Faraji Niri, WMG | 10 mins |
13:55 | Powering the future: adaptive experimental design for next-gen batteries | Joel Strickland, Intellegens | 10 mins |
14:05 | Visualisation of analytical data | Sam Cooper, Dyson School of Design Engineering | 10 mins |
14:15 | Q&A | Keri Goodwin, CPI | 15 mins |
14:30 | Finish | ||
Speakers
Katharina Roettger
Principal Scientist - Digital Technology
Katharina Roettger is a Principal Scientist with many years of experience working with digital technologies and is passionate about supporting UK companies to increase productivity and becoming more sustainable. Katharina joined CPI in 2016 and is currently working on soft sensor applications and predictive modelling for manufacturing.
Joel Strickland
Head of Technical Pre-Sales at Intellegens
Joel Strickland, Head of Technical Pre-Sales at Intellegens. Intellegens applies advanced machine learning to accelerate innovation for materials R&D. The Alchemite™ software enables you to extract maximum value from real-world experimental, process, and other data. Customers optimise products and processes, and save time and cost by achieving R&D objectives while reducing experimental workloads by up to 90%. The Alchemite™ method works for sparse, noisy data where other machine learning approaches fail. There have been successful applications across various materials-related processes in the battery space.
Mona Faraji Niri
Associate Professor of Battery Modelling at WMG
Mona Faraji Niri is an Associate Professor of Battery Modelling at WMG, a research fellow of the Faraday Institution, and a Fellow of the Alan Turing Institution in Artificial Intelligence and Data science. Mona specialises in modelling, control algorithms and machine learning for dynamical systems and has extensive experience in energy storage systems, li-ion batteries, battery management as well as electric vehicle powertrain. Her research interests also cover areas in optimisation of battery manufacturing processes via machine learning, and artificial intelligence.
Sam Cooper
Senior Lecturer at the Dyson School of Design Engineering
Sam Cooper is a Senior Lecturer at the Dyson School of Design Engineering, leader of the TLDR group, and member of the Electrochemical Science and Engineering Consortium. His work is primarily focused on the design of next-generation energy storage technologies and exploring the use of machine-learning approaches in this space.