Current issues in industrial analytics
Predictive quality case study; technology and market overview
Attendees are eligible for a certificate of completion.
Industrial analytics are used to identify and recognize machine operational and behavior patterns, make fast and accurate predictions and empower confident decision making, according to the Industrial Internet Consortium.
In this webcast we’ll review a predictive quality and process optimization use case involving a plastics fabrication company, Toray Plastics America. Mike Malone, principal process engineer, streamlined access to blending components data contextualized with process data.
Using IIoT sensors and industrial analytics, Toray monitors film temperatures, polymer pressures, and machine feeds and contextualizes mixing and blending data. Visualizations and alerts make digesting the resulting information intuitive.
To date, only a small percentage of industrial companies incorporate machine data in their analytics process for decision support and intelligent operations.
That’s bound to change, said a recent report from senior analyst Blake Griffin of Interact Analysis, especially when it comes to motor-driven systems and rotating equipment, with cloud-based maintenance service packages using a SaaS business model.
In this webcast’s two presentations we’ll present 1) practical, technically nuanced information on how to get started with industrial analytics and 2) needed context about the markets, technologies and uses of industrial analytics.
- Tips on getting started with industrial analytics
- Typical elements of an industrial analytics solution
- Evaluate market and technology updates
Michael Malone, principal process engineer, Toray Plastics America
Blake Griffin, senior analyst, Interact Analysis
Kevin Parker, Content Manager, CFE Media and Technology