[Success Story]
Cognex Brings In-Sight To Machine Vision
Machine-vision technology continues to reinvent the production process, and In-Sight systems put it within everyone’s reach.
Chances are, many items that you use every day are made with the help of a machine-vision system. Whether it's a razor, soda cans, light bulbs, or the diaper on your baby, machine-vision technology is at the heart of that product's fabrication.
This technology allows computers to "see" by employing a specialized computer interfaced with a video camera. The system captures the image of an object being manufactured, analyzes that image, and then provides information about the object. Machine-vision systems identify products, inspect for defects, gauge part dimensions, and instruct other equipment like robotic arms to take some action—all at up to hundreds of parts per minute (for a better understanding of this technology, see "What Is Machine Vision?" p. 48).
A pioneer in cutting-edge machine-vision technology is Cognex Corp. (www.cognex.com), whose name is derived from Cognition Experts. The company doesn't have one landmark technology, but several (see DRILL DEEPER 7251, "Cognex Milestones," www.elecdesign.com). Last year, it shipped its 200,000th machine-vision system, representing nearly $1.5 billion in cumulative revenue since the company began operations in 1981.
Cognex's latest groundbreaking product, In-Sight, provides end users with no programming background an easy-to-use machine-vision tool that they can install in one or two applications. In-Sight is a comprehensive vision sensor rather than a vision system. It takes the individual machine-vision components—such as a camera, frame grabber, and computer—and integrates them into one package.
It's the first vision product to employ a spreadsheet for configuring vision applications, thereby entirely eliminating the need for complex programming or reliance on an external PC for setup. In-Sight is significant because it bridges the gap between single-purpose "smart cameras," which typically lack the power and flexibility to solve all but the simplest vision tasks, and general-purpose machine-vision systems, which are higher in price and can be more difficult to use.
At Cognex, the emphasis is on research and development. This follows from one of its founders, Robert Shillman, who left his post as a lecturer in human visual perception at the Massachusetts Institute of Technology to start Cognex. He wanted to go into business and fulfill the potential of his research by applying it to industrial automation. So, he took his life savings of $86,000 and invited two graduate students from MIT's famed Artificial Intelligence Lab, Bill Silver and Marilyn Matz, to join him in founding a new business venture. Today, Shillman is president, CEO, and chairman; Silver is senior vice president of research and development and chief technology officer; and Matz is senior vice president of engineering for the company's Modular Vision Systems Division.
"I started Cognex because I wanted to work each day in a particular type of company—one that had smart, energetic people who enjoyed what they were doing, who liked to have goals and to accomplish those goals," says Shillman. "And I wanted a physical environment that reflected the culture of the company, which I wanted to be dynamic. I also wanted to work for a company where the management would tolerate, or better yet, seek out outspoken and assertive people like myself who don't care about office politics but who care deeply about doing the right thing for customers. Well, I couldn't find such a company, so I had to create it."
"Machine vision is as necessary a part of advanced manufacturing as gears and motors," adds Silver. "Without it, many of the products we take for granted simply could not be manufactured, and without those products the modern world as we know it would be very different." The ramifications of machine vision are far-reaching (see "What Can Machine Vision Do?" p. 50).
How can manufacturers get machine vision to work on the factory floor as it does in the lab? Real-world manufacturing conditions, which are rarely evident in the lab, include inconsistent ambient lighting and optical distortion, as well as changes in component shapes and surface characteristics. These variations can interfere with a vision system's ability to "see."
"The answer to overcoming these hurdles is a strong collaboration among the automation equipment supplier, the machine-vision supplier, and the end users," says Matz. "It's critical that the machine-vision supplier is involved throughout the entire development process, so it can not only react to problems that occur but also help companies anticipate unforeseen problems. When the invention of new vision technologies is necessary to handle specific challenges, tight collaboration can help ensure that it begins early enough to avoid impacting the production schedule and the acceptance of the vision machine."
MAKING A DIFFERENCE The focus on research and development has produced many engineering breakthroughs. Cognex was among the first to identify codes embossed on rubber (tires) and etched on metal (circuit boards). It proved to a doubting industrial world that machine product identification could be done at the speeds required by manufacturing. A series of advances in conducting industrial pattern recognition, such as normalized correlation and then geometric pattern matching, changed the way objects are located in semiconductor manufacturing and electronic assembly. Overall, the breakthroughs increased accuracy in finding objects by a factor of 40 over a 10-year period.
The company made these advances because it has always been willing, from day one, to take risks. Initially, says Silver, it was the "idealism of youth" that sparked their desire to create machine-vision tools, despite the lack of information on the subject. "We saw a problem people wanted solved, and we were crazy enough to do it," he says. "We had our share of good luck too. Had we known how hard it would be, who knows if we would have given it a try?"
That philosophy, seeing a problem and working to resolve it no matter what, still prevails. "We have set the direction for what customers of machine vision expect and what suppliers produce. We've taken risks to produce new things before people had an idea they were possible or valuable commercially," says Silver (see DRILL DEEPER 7252, "A History Of Success," www.elecdesign.com).
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