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Tuesday, May 14 • 2:30pm - 3:00pm
Industrial Sensor and IIoT Data and Meta-Data Management

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Industrial sensor data is Big Data and largely of time-series nature for asset intensive industries such as oil & gas, chemicals, paper & pulp, pharma, mining etc., including utility companies in electricity, gas and water production/generation and transmission/distribution. Attend this session as we review the challenges in sensor and IIoT (Industrial Internet of Things) data and meta-data management. This involves working with large volumes of high velocity data from automation and control systems with hundreds of thousands to millions of sensors; each sensor collecting measurements every minute, some every second or even few microseconds. The data may also be from CMS (condition monitoring systems) and several other disparate line-of-business data sources such as planning, work management, quality, weather, web pages etc. IIoT and edge devices now bring in even more data with their own new challenges during data collection, and the need to merge this data with legacy sensor data sets.

This presentation will focus on the lessons learnt during our 35+ years of working with data and information management in manufacturing operations (https://en.wikipedia.org/wiki/Manufacturing_operations_management). And, we will cover how data analytics (with machine learning when appropriate) and visualization are used in customer use cases in energy reduction, predictive maintenance and reliability, process yield improvement, product quality, and others.

A data infrastructure approach (scalable backbone) with a faceted and application-adapted digital model allows flexible and extensible methods for data collection, analysis, and visualization that are fit-for-purpose and finally, actionable insights. Also see https://en.wikipedia.org/wiki/OSIsoft


Gopal Gopalkrishnan

Solutions Architect, OSIsoft, LLC

Tuesday May 14, 2019 2:30pm - 3:00pm EDT
Freedom Ballroom II