IpX True North Podcast

Pt 2: Maintaining the Physics Model within AI & ML with Arnaud Hubaux, ASML

June 04, 2021 IpX - Institute for Process Excellence Episode 8
IpX True North Podcast
Pt 2: Maintaining the Physics Model within AI & ML with Arnaud Hubaux, ASML
Chapters
IpX True North Podcast
Pt 2: Maintaining the Physics Model within AI & ML with Arnaud Hubaux, ASML
Jun 04, 2021 Episode 8
IpX - Institute for Process Excellence

In this second part episode of the True North Podcast, IpX Director of MBE, Max Gravel and Senior Technical Program Manager, ASML, Arnaud Hubaux continue their discussion on the challenges of maintaining the physics model in AI/ML with rapidly changing datasets. 

Arnaud describes the need for an enterprise-level AI/ML framework that considers the complete lifecycle change to expand beyond niche use-cases and realize the dream of a fully automated product line. Max and Arnaud discuss where to start when implementing AI and the role of CM in maturing the adoption of AI in a manufacturing environment. Hear more on:

  • The need for the impact analysis to stretch beyond the walls of the company into the environment where it will be running.
  • The perceived unpredictability of AI/ML and the reluctance to deploy in a manufacturing environment.
  • The importance of building in safety mechanisms to prevent financial loss in case of AI/ML failure.
  • How CM establishes gates and checks when releasing a change to make sure the proper qualifications are implemented.
  • AI/ML sustainability and the need to look beyond short-term benefits into the complete lifecycle of a product.

Connect with IpX to hear from more industry thought leaders and to learn about the True North service model for improving your organization. https://ipxhq.com/

Show Notes

In this second part episode of the True North Podcast, IpX Director of MBE, Max Gravel and Senior Technical Program Manager, ASML, Arnaud Hubaux continue their discussion on the challenges of maintaining the physics model in AI/ML with rapidly changing datasets. 

Arnaud describes the need for an enterprise-level AI/ML framework that considers the complete lifecycle change to expand beyond niche use-cases and realize the dream of a fully automated product line. Max and Arnaud discuss where to start when implementing AI and the role of CM in maturing the adoption of AI in a manufacturing environment. Hear more on:

  • The need for the impact analysis to stretch beyond the walls of the company into the environment where it will be running.
  • The perceived unpredictability of AI/ML and the reluctance to deploy in a manufacturing environment.
  • The importance of building in safety mechanisms to prevent financial loss in case of AI/ML failure.
  • How CM establishes gates and checks when releasing a change to make sure the proper qualifications are implemented.
  • AI/ML sustainability and the need to look beyond short-term benefits into the complete lifecycle of a product.

Connect with IpX to hear from more industry thought leaders and to learn about the True North service model for improving your organization. https://ipxhq.com/