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How Novelis Applies Cutting-Edge Methodologies to Optimize Aluminum Design

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Archived series ("Inactive feed" status)

When? This feed was archived on July 01, 2023 22:18 (1y ago). Last successful fetch was on August 30, 2022 19:25 (2y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 337293408 series 3357717
Content provided by SigOpt. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SigOpt or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Aluminum design is an incredibly complicated business. Not only do you have to get the model design right—it also has to work in the real world. In fact, the aluminum soda can is one of the most engineered products in your house right now. In this episode, SigOpt’s Head of Engineering Michael McCourt talks with Vishwanath Hegadekatte, R&D Manager at Novelis, about how he's using tools like SigOpt to optimize aluminum production and design—as well as considering environmental impact to build better products and conserve resources.

  • 2:16 - Intros
  • 4:03 - Metrics for aluminum design
  • 4:50 - How Novelis is pioneering physics-informed machine learning
  • 6:40 - How Novelis uses SigOpt
  • 8:35 – Industry is on par with academia for physics-informed machine learning
  • 12:18 - "The optimum is not always the best choice"
  • 14:45 - What's next from Novelis

Learn more about Novelis: https://www.novelis.com

Learn more about SigOpt at sigopt.com and follow us on Twitter at twitter.com/sigopt

Subscribe to our YouTube channel to watch Experiment Exchange interviews https://www.youtube.com/channel/sigopt

  continue reading

9 episodes

Artwork
iconShare
 

Archived series ("Inactive feed" status)

When? This feed was archived on July 01, 2023 22:18 (1y ago). Last successful fetch was on August 30, 2022 19:25 (2y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 337293408 series 3357717
Content provided by SigOpt. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by SigOpt or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Aluminum design is an incredibly complicated business. Not only do you have to get the model design right—it also has to work in the real world. In fact, the aluminum soda can is one of the most engineered products in your house right now. In this episode, SigOpt’s Head of Engineering Michael McCourt talks with Vishwanath Hegadekatte, R&D Manager at Novelis, about how he's using tools like SigOpt to optimize aluminum production and design—as well as considering environmental impact to build better products and conserve resources.

  • 2:16 - Intros
  • 4:03 - Metrics for aluminum design
  • 4:50 - How Novelis is pioneering physics-informed machine learning
  • 6:40 - How Novelis uses SigOpt
  • 8:35 – Industry is on par with academia for physics-informed machine learning
  • 12:18 - "The optimum is not always the best choice"
  • 14:45 - What's next from Novelis

Learn more about Novelis: https://www.novelis.com

Learn more about SigOpt at sigopt.com and follow us on Twitter at twitter.com/sigopt

Subscribe to our YouTube channel to watch Experiment Exchange interviews https://www.youtube.com/channel/sigopt

  continue reading

9 episodes

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