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Video analytics for process & quality control

July 14, 2016
We tap in to the machines and sensors on the factory floor, look for patterns and anomalies, and create purpose-built software to process the quality data in real-time.

Dell recently hosted its Connect What Matters contest, which asked companies to submit their innovative IoT solutions using the Dell Edge Gateway device. Eigen Innovations was a gold-medal winner for its video-analytics solution that leverages thermal-imaging cameras and PLC/sensor data for real-time process and quality control.

“We work with customers who are doing complex manufacturing, involving automated multi-
layer assembly with adhesives, welds, coatings, etc., at high speeds,” said Greg Picot, director of product development with Eigen Innovations. “Traditionally, this type of manufacturing is challenging and costly to do automated quality control on, and there is still a heavy reliance on human inspection and destructive testing. We are able to tap in to the machines and sensors on the factory floor, look for patterns and anomalies with computerized machine learning, and create purpose-built software to process the quality data in real-time.”

Smart Industry: What’s special about your solution?

Greg: We recognized early on that things like Big Data analytics and machine learning can only take your solution so far; we are able to build up a certain level of specialized expertise looking at raw data, but by far, the best expertise is found on the factory floor. Each factory has experts at every stage and level of the production operation, and there is a collective intelligence that can be tapped within every plant. So, we’ve designed a solution that works with operators, enabling them to share input and feedback on the events Eigen detects, which in turn helps software get smarter, and helps the community on the factory floor get smarter. We think of this concept as Augmented Intelligence—our solution is bringing together connectivity between the machines, operators and software for an end-to-end experience that continually improves.

Smart Industry: What are applications for this solution?

Greg: Since the backbone of our solution is a machine-learning platform, it can be used in almost any application. That said, where the value comes through is in complex manufacturing processes where we are able to realize massive gains in efficiency and accuracy of detection not possible to achieve in a manual way. We find this a lot in the automotive and the food-processing industries, where we are primarily focused. We also have applications in construction materials and smelting. The applications are all real-time, quality-control monitoring for defect detection and avoidance.

Smart Industry: How critical is the real-time element of your solution?

Greg: We have applications that monitor conveyors moving product at 1,000’s of feet per minute, and require a defect-detection-and-avoidance cycle of seconds. In automotive, parts-fabrication is measured in seconds, and cost-per-unit can be significantly reduced for every second of efficiency in processing. Our solutions are closed-looped to the manufacturing equipment, where the real-time analytics processed on the edge must interrupt the manufacturing process in order to prevent costly defects from happening. Real-time capability is the most critical thing about our solution.

Smart Industry: How is predictive maintenance changing the world of manufacturing?

Greg: At this time, our use-case is more about monitoring and controlling the quality of product through the manufacturing process itself. However, there is obviously a direct correlation between the performance of the machine and the quality of its output. Where we see this going is converging the Big Data analytics on the machine performance with the data produced from the quality monitoring to make the machine more self-aware of its need for maintenance, based on the quality of what it’s producing.

Smart Industry: What will you do with the winnings from the Dell contest?

Greg: We are really honored and excited to be recognized by Dell this way. We are focused on adding value to our platform for customers, and the Dell award certainly helps contribute to that effort directly. However, we believe the access we gain to Dell facilities to help test our software—the go-to-market guidance and assistance, the strategic insights, the relationships we gained with Dell executives and leadership—are the most valuable part of this award, and we look forward to continuing to work with Dell as we build out more of the Eigen solution.

Smart Industry: What most excites you about the digital transformation of industry?

Greg: I think about it from the angle of how it’s exciting for the software-development industry. I think there’s a notion that computer programming meant working on something related to enterprise software or digital consumer software. With industrial IoT, especially, that idea is changing rapidly, as it requires a mix of skill sets from multiple disciplines working together. For many people used to developing “software-only” solutions, there’s an exciting and rewarding alternative where you’re building solutions that are tied directly to tangible assets and production operations, and the possibilities for innovation are endless.