Optimizing the port supply chain using predictive maintenance with Tom Pennington

Saving money in business operations is an effective and consolidated application of machine learning and AI called predictive maintenance.

In this episode of the AI and Digital Transformation Podcast by G.M.S.C. Consulting, together with Tom Pennington from VROC, we show you how predictive maintenance can lower both your warehouse cost and your asset's downtime, but only if good practices are followed.

Listen to our full episode, or check our chapter list below to make sure that you know everything you need to know to make your predictive maintenance project successful, with AI, of course.

Who is Tom Pennington?

For over 20 years, Tom has played a key role in completing the delivery of organizational and technology transformational strategies related to technology adoption, end-to-end automation, and new ways of working, with different companies across a wide range of technology sectors.

He was also a founding member of the CBA CIO Innovation Board, which focuses on assessing and implementing emerging technologies to deliver transformational value to the group.

At the moment, Tom Pennington is the Business Development Director for VROC, an AI company that offers clients transparency and autonomy when it comes to managing and optimizing their assets thanks to their platform and support.

Check out our show notes to know more about Tom and VROC.

Chapters

(00:06:14) Teaser

(00:56:08) Intro to VROC and Tom Pennington

(05:35:14) Lifecycle of a predictive maintenance and optimization project

(10:33:00) Data gathering, historical data, and client's data awareness

(13:35:00) Working with engineers and other teams involved in the supply chain

(15:33:00) AI is not always a black box, the value of indirect data

(19:06:00) Knowledge transfer on data between VROC and clients on adapting AI

(21:43:20) When should a business opt for a customizable AI platform?

(26:21:22) The real value of the autoML platform, the importance of training and educating clients about the platform

(31:18:00) Integrating your business metrics into the AI platform by understanding the entire ecosystem, Root cause analysis

(36:25:15) Should business and technical people work together from the very beginning when starting an AI project?

(39:01:00) Ideal customer for VROC

(41:18:18) Tom's Book Suggestion

(42:06:22) Closing remarks

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