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Speaker "Sanket Amberkar" Details Back

 

Topic

How Machine Learning is Addressing Industrial IoT

Abstract

The adoption of manufacturing analytics is expected to grow from 15% to nearly 55% by 2020. Data generated by manufacturing or process operations is very rich in information that can provide actionable insights to reduce downtime and improve the throughput and quality of the products produced. As companies start to digitize their industrial operations as part of their IIoT initiatives, they are learning that they are rich in operational data but poor in the ability to analyze such massive amounts of it. Machine learning has emerged as a leading approach to maximize the value of this operational data. Machine learning enhances this by not just recognizing defined patterns, but by its ability to learn and discover new ones and correlate them to operational events. This session will discuss how machine learning is being applied to address these and use cases from various industrial examples.

Profile

Sanket leads marketing at Falkonry and is responsible for the company’s positioning, thought leadership and go to market strategy. Sanket has over 20 years of experience in the high tech, energy, industrial and automotive markets in areas ranging from of product development to market strategy. Prior to Falkonry, he was VP of Product Marketing for Innovation & New Ventures at Flex, where he brought to market its Innovation services and launched the LabIX startup initiative. Earlier he led marketing and product development teams at Cisco and Delphi. Sanket holds Master’s degrees in Electrical Engineering and Business Administration – both from the University of Michigan. He is a frequent industry speaker and holds thirteen U.S. patents.