- THE MAGAZINE
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“Envision makes what is invisible be visible,” says David J. Wang, CEO and CTO of Beet Analytics Technology (Plymouth, MI). “It leverages existing sensors in the system and uses them as timing devices to capture the heartbeat of any automated process. The amount of data that is captured and processed by Envision is massive. We overcome tremendous technical hurdles to make this new set of data available.”
In capturing the heartbeat, Envision’s solution “listens” to the rhythm of machine and automated operations, illuminates untapped and currently invisible process data to pinpoint possible problem areas before a critical failure and transforms how a system’s operational and quality performance is measured and managed. The software monitors and records every automated motion and process in real-time, acting as an EKG of sorts, comparing the actual process performance against design-intended cycle time to gauge the health of the system.
“Even though we are decades into the digital age, our manufacturing floors are still in the digital dark age. Every second, thousands or even millions of financial transactions, blogs, twitters, phone calls, SMS messages and others are recorded in the digital universe,” says Wang. “At the same second, millions of motions and operations are completed in tens of thousands of manufacturing processes or automated processes, yet there is no recorded digital trace.”
According to Wang, Envision makes digitizing these motions and operations possible, enabling them to be measured, analyzed, inspected and tested.
“With Envision,” says Wang, “we will be able to provide the ‘single point of truth’ of all manufacturing processes.”
For Beet Analytics Technology, the idea of “machine heartbeat” software was born in 2009.
“Control, safety and data network had recently and finally converged into one network thus opening the door for a new kind of automation diagnostics software that could leverage the power of the computer to give more intuitive, historic and predictive automation diagnostics to the end user,” says Wang.
A team comprised of control engineers and IT software developers-including the two main inventors of Envision, who combined have more than 36 years of combined experience in both control engineering and information technology-was formed to develop the concept into a software product in the second quarter of 2009.
“They were able to see this new possibility and created the foundation for Envision,” says Wang.
After 18 months of development, the beta version of the software was released and piloted on a major automaker’s assembly line in November 2010. Envision Version 1.0 was officially released October 2011 after more than two-and-a-half years of development.
According to Wang, the response to Envision has been extremely positive.
“During the last two decades, the advancement in software has not been focused on the shop floor or manufacturing. With the proliferation of computer-aided and ERP systems, the industry has been able to digitize most of the engineering, finance, purchasing and other back office operations in any given enterprises,” says Wang. “There is no enterprise system out there to digitize the real manufacturing processes down to every motion on the factory floor. There is a huge vacuum in applying information technology to help manufacturing getting better and smarter. The market is waiting for something like Envision.”
According to Wang, the software can be applied to any automated or semi-automated control process from an automated assembly line to a rollercoaster ride in an amusement park to just about any process with predefined sequence and time constraint.
“We have been piloting in an automotive OEM assembly factory for the last 12 months,” says Wang. “We have conducted proof of concept pilot with an electronic manufacturer.”
For more information, contact:
Beet Analytics Technology
45207 Helm Street, Plymouth, MI 48170
SpecificationsWeb-based software application.
Provides clear and in-depth automation intelligence. The software delivers the vast amount of previously untapped manufacturing data into clear, actionable information.
Captures and provides accurate in-depth component level cycle time performance.
Identifies areas for process improvement down to the component level.
Pinpoints critical areas for preventive maintenance.
Enables all users to monitor and analyze the system performance anywhere via the Web.