Progress has not come without some growing pains. Machine vision was first marketed as a new, must-see technology for manufacturing automation in the early 1980s, a lesser player amid the hype surrounding artificial intelligence and automated robotic assembly. The promise of a mechanical system -- hardware and software -- that would emulate the human eye was captivating in concept but created expectations that could not be immediately met. Start-ups were plagued by complex programming requirements, difficult installations, mediocre functionality and low reliability. The technology required to implement a system successfully was simply out of reach of most users.
After some lean years, the outlook once again looks bright for machine vision as products have matured, functionality has increased, suppliers have become smarter and the cost and complexity of systems has come down. Ten years ago machine vision systems cost $40,000 to $60,000, while today they run in the $5,000 to $20,000 range. They also offer vastly improved performance, offering much richer data at much higher speeds.
It is a common misperception that machine vision systems provide generic optical detection and processing capabilities. While every system includes essential functions, most customers require some level of customization in development and should be cautious of vendors claiming to have "one-size-fits-all" solutions. Systems perform best in their own tightly controlled, highly specialized environment.
Application requirements vary drastically by industry, but there are a number of components which are common to every machine vision system. Technology is evolving rapidly in all these areas, creating new opportunities on the manufacturing floor.
"Noisy" backgrounds with a lot of detail contained therein also tend to disqualify machine vision as an observational and analysis tool. Think of berries on a bush or apples on a tree, for example. Machine vision has to be told exactly what to look for, and the display of items of interest has to be optimized. A system works best set up under uniform, controlled lighting conditions, with objects positioned so that there is little or no background interference, and no interfering reflections.
Machine vision is most successful in the controlled environment of the factory floor, offering some important advantages over human vision in terms of cost, speed, precision, and physical demands. Systems are used to:
Machine vision excels at locating and examining objects with hard, well-defined edges and regular patterns. And its high speed processing capability gives it unquestioned superiority when it comes to looking at parts on today's fast-paced production lines. Although human inspectors can keep pace with visual inspection demands at a rate of a few hundred items per minute, they also tend to fatigue and miss flaws. With machine vision it is not uncommon to run thousands of parts past a camera per minute and resolve a dozen features on each piece for product conformance -- all in a matter of milliseconds. Machine vision systems ensure repeatable results and can run continuously 24 hours a day, seven days a week.
The potential applications for machine vision reach far beyond even those areas where human vision can be applied. These include conditions where light levels are too low or too bright for human vision, or where non-visible electromagnetic radiation such as x-rays or infrared is required. Machine vision systems can be applied in manufacturing clean rooms, and survive environments too hazardous for humans.
Outsourcing is a "megatrend" seen across all market segments as companies find that purchasing a custom-engineered machine vision system entails less risk than designing and manufacturing it themselves. System integrators and VARs have the integration expertise necessary to provide application specific solutions based on a thorough review of the requirements. Many specialize in serving a particular market niche such as food processing or pharmaceutical manufacturing. This allows them to focus their attention on a smaller range of needs.
Even then, putting together puzzle pieces from a variety of component vendors remains a costly, time-consuming task, mainly due to a lack of industry standards. According to industry analyst Nello Zeuch of the Automated Imaging Association (AIA), the cost of components accounts for less than one-third the cost of a machine vision system. The rest is spent on custom development, system integration and installation.
Moreover, the real costs of product development are often hidden in the lost opportunity cost of not getting a product to market on time. Studies have shown that, in today's fast-paced markets, the opportunity cost of a six-month delay in product development can far exceed both a 50 per cent development cost overrun and a ten per cent increase in manufacturing costs. With the help of an experienced system integrator or VAR, it is much more likely that schedules can be met.
Having the support of an outside source -- long after a product delivers -- is another advantage. Many companies do not have the in-house support required to get a system back up and running should problems arise. Nor do they have the expertise necessary to upgrade the system later with newer technology. A capable third-party supplier may willingly take responsibility for the whole system, providing an invaluable source of technical assistance and advice.
Meanwhile, users themselves can help ensure that a machine vision system meets their needs successfully. Whether the objective is making accurate measurements, controlling an operation or merely capturing an image, it is important for users to work through the design considerations with their supplier. That means understanding the technology, the application, and the limitations -- what a machine vision system can and cannot be expected to accomplish. Being able to quantify desired results is valuable, too. For example, what system throughput is required? What tolerances? And what are the physical requirements?
Finally, industry changes are to be expected and welcomed. A few key trends are shaping the future of the machine vision market. On the supply side, these include standardization and greater specialization among suppliers of components and services. Outsourcing will gain preference as companies continue to downsize and move away from developing custom, proprietary solutions in-house. And hardware prices are dropping rapidly. To be sure, overall system costs -- which include application software, integration and installation -- are not keeping pace due to the complexity of developing a custom fit. But better tools and interface standards will help the industry as a whole lower prices and meet its growth potential.
Another factor that is having positive impact on the industry is the growing sophistication of users. More comfortable with machine vision and with technology in general than just a few years ago, they are better equipped to communicate their needs to the industry. Vendors in turn are able to deliver more effective solutions. That interplay is what makes machine vision the exciting field it is today, full of more opportunity than ever to make good on a concept that was the stuff of science fiction just a decade or two ago.
George Fabel is the President and CEO of Imagenation Corporation, an international leader in the design and manufacture of machine vision components and subsystems. Prior to joining Imagenation, Fabel was President/CEO of CAChe Scientific, a chemical design application software company. He also served for ten years as Director of the Imaging Research Laboratory at Tektronix, Inc. He has a Ph.D. in Physics from Penn State University.
Sidebar Story
CyberOptics supplies the Sentry 2000, which is used right on the production line at PCB assembly plants to inspect the solder paste on boards immediately after screen printing. By detecting defects before components are placed, the Sentry 2000 helps users increase yields and reduce scrap and rework. Typically, the system is placed over the existing conveyor belt, directly after the solder paste screen printing operation. Using 3-D machine vision technology, the system captures a view of the area selected by the user and from that image extracts information pertaining to solder paste height, area and volume at multiple sites per board. Images are stored, allowing operators to go back and view the image of a rejected board after the fact to better understand the problem.
Before automatic in-line machine vision systems were made available, human inspectors would have to pull a board off-line and bring it to a manual inspection system that used a laser sensor to make the measurements. This method not only demanded a skilled operator, it meant measurements were made off-line rather than in-line as the Sentry 2000 does, at less cost than competitive machine-based solutions. Current customers are end-users such as IBM, Motorola and Lucent.
Rick Cash of CyberOptics, who is system engineer for the Sentry 2000, said the frame grabber is a critical component of the system. His requirements included low pixel jitter, excellent linearity, good software drivers and libraries, and compatibility with Windows NT. He evaluated frame grabbers from a number of companies and chose Imagenation Corporation's PX500 PCI bus frame grabber for "very high accuracy at a reasonable price."
Cash points out that excellent specs and competitive prices are not the only criteria to look at in selecting a vendor. He says that long-term vendor relationships and good support are vital to CyberOptics' success and has found Imagenation to be a partner who is responsive to their needs. "Imagenation is willing to work with us to find solutions to problems and to commit to deadlines," he said. "This is the main reason that Imagenation is our frame grabber supplier."
Reprinted with permission from Quality Digest. Copyright 1997 QCI International, P.O. Box 17169, Chico, CA 95927, (530) 893-4095, fax (530) 893-0395. All rights reserved.