Leveraging Deep Learning and AI Applications in Manufacturing

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Do AI and Deep Learning belong on the factory floor or are they just for those with their heads in the clouds?  Is being “on the edge” actually a good thing when you want to improve quality and reduce costs?

As a manufacturer seeking to improve your production processes, you must consider these questions, and more. You face an array of technologies that promises to help you reach your goals, and  you must carefully evaluate your options before making any decisions. The fact is that manufacturers like you are successfully using AI and Deep Learning in their operations.

Come join us to hear real-world case studies about how a chemical factory, a glass factory and a fabric factory reduced their costs and increased their quality, and the role AI and Deep Learning played in those successes.

In addition we will also cover:

• Why the Cloud has limitations for AI and Deep Learning on the factory floor.
• Why on-premise is fashionable again; now they call it “edge computing.”
• Why factory-floor AI and Deep Learning need both a hybrid edge/cloud to truly deliver 4.0 Smart Factory capabilities

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Speakers  

David Breaugh, Regional Business Leader, Microsoft

Dave is the regional business lead for manufacturing industries across the Americas.  He and his team develop and deliver business transformation strategies to empower customers to create value and sustainable competitive advantage. Dave brings over 30 years of experience in automotive, aerospace, chemical, consumer goods, high tech, industrial, and medical device industries. His specialty is leading enterprise transformation, operational turnaround, and performance improvement programs enabled by technology. 

Philip van de Mortel, Global Sales Manager, Intel 

Phil is responsible for Intel’s go to market strategy and execution with Microsoft covering Intelligent Edge and IoT.  Phil has over 15 years of technical sales experience driving breakthrough sales engagements with multinational customers across multiple IOT and Compute industries. A history of defining, developing, delivering and enabling customers and ecosystems for Intel based solutions in a broad range of embedded and internet of things applications such as robotics, machine vision, industrial and manufacturing. 

Stephen Welch, VP of Data Science, Mariner 

Stephen leads a team developing deep-learning based solutions for manufacturing applications. Stephen strives to not just develop strong technology, but to explain and communicate results in clear and accessible ways.  He is an adjunct professor at UNCC and is the author of the educational YouTube channel Welch Labs, which has earned 200k+ subscribers and 10M+ views. Stephen holds 10+ US patents, and engineering degrees from Georgia Tech and UC Berkeley.  

Peter Darragh, EVP of Product Development, Mariner 

Peter’s first IoT project was converting sensor signals into alarm and location messages for an airbase’s fire-crews. Mid 80s Sold mid-range ERP systems. Late 80s Integrated process optimization apps with plant equipment. During the 90s integrated EDI and XML messaging to logistics systems. Early 00s Integrated automated warehousing and advanced demand planning into ERP. 2014 developed IoT and rules-engine applications for asset management. Since 2017, applying AI and IoT to manufacturing operations.

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