Challenges & Opportunities in Machine Learning of Metallurgical Processes
Add to calOnline and Engineering Lecture Theatre 1, Engineering Building, University of Leicester
Prof Hongbiao Dong, The University of Leicester FREng, FIMMM</b>
The metals industry is facing many challenges, from productivity, capital investment cycle, margin squeeze, and the global challenge of decarbonization. The revolution in digital manufacturing, from the concept of Industry 4.0 is a key enabler in meeting these challenges and ensuring companies remain fit for the future. Recent advances in information technologies and data sciences enable data-driven-decision-making in metal manufacturing, which can significantly improve their operations and profitability. Most of the large manufacturing enterprises now start to benefit from this as they can collect more data that can be utilized to enhance their decision-making processes. Universities, and small and medium enterprises (SMEs) have limited data and resources, thus reducing the possible gains. In this talk, we propose a shared data analytic framework for university and industry to collaborate and share data, the data will be then jointly analyzed, feasibility and quality of data analytics and decision-making processes could be significantly enhanced.
Free IOM3 student membership for East Midlands students who attend this event
Attending EMMS technical meetings contributes to CPD.
Register to attend in person or online with Eventbrite:
Online: https://www.eventbrite.co.uk/e/emms-technical-talk-on-line-version-machine-learning-in-metallurgy-tickets-1045004455457?aff=oddtdtcreator
In person: https://www.eventbrite.co.uk/e/emms-technical-talk-in-person-machine-learning-in-metallurgy-tickets-1045011185587
