Vision in the pressroom

By Greg Farnum

Using machine vision in the pressroom is not new. The 1980s witnessed a raft of applications, primarily on the front end of the process as an aid to robotic handling of sheet-metal blanks prior to stamping--and almost exclusively in the auto industry.

It was a labor-saving, quality-enhancing technology whose time, seemingly, had come. By the end of the decade, though, the vogue for vision in stamping and forming had faded and the rate of new applications had dwindled to a trickle.

Long-time vision pros freely admit that in the '80s vision technology was oversold at a time when it was simply not mature enough for many of the applications. With these early systems the computing power needed to analyze images was limited. Lighting, which these systems needed just like a fish needs water, was often obscured by the hazy, dusty atmosphere within the plants. Additionally, the fact that system components were typically not factory hardened and integration with neighboring systems was cumbersome and time-consuming made for unhappy customers. So what has changed?

Just about everything, says Nello Zeuch, president of Vision Systems International, a vision integrator based in Yardley, Pa. "We now have cost-effective solid-state cameras. Back in the late '80s and early '90s solid-state cameras were so expensive they were rarely used. Instead, people used vacuum-tube cameras that had difficulties in the industrial environment."

Today's solid-state cameras provide higher-resolution images than vacuum tube models. In effect, they can see better, even in less-than-optimal conditions. Couple this with the fact that the greater computing power of today's vision systems enables them to run powerful algorithms that help compensate for lighting variations, and suddenly lighting is no longer the Achilles heel of machine vision.

Vision systems of the '80s and early '90s were largely the preserve of major manufacturers because they carried a major price tag. Today, many vision components sell at a fraction of their price of just a few years ago, and the cost of vision systems has reflected that decline. And that brings the issue back to pressworking, where cost is a foremost concern of Peter Stephan, program manager for stamping and sheet metal for Fanuc Robotics America Inc.

Stephan reports that there has been steady growth in the demand for his company's vision-guided robotic press tending systems. He attributes this to a number of factors. "For one thing, there is the increased robustness of the vision hardware and software," he says. "Also, more people have now seen these applications in use, so they aren't so nervous about applying this technology." And there is also, he says, the chance to rack up big savings.

Saving on alignment
In addition to the expected labor savings, Stephan notes that "if you're eliminating mechanical alignment devices you're achieving savings in the thousands of dollars," and that, he says, is what his systems excel at. "Destacking and blank alignment have been our main applications for this technology. That's because blank alignment has typically become somewhat complex."

Stephan points out that frequently a stack of blanks will be brought to the press in an orientation that will not allow it to be correctly loaded onto the die. The parts may be skewed right to left or in an angular orientation coming off the stacks. Then there's the fact that parts are often transferred through a lubricator or washed prior to loading, which can also make maintaining part orientation difficult. "In the past," he says, "manufacturers wanted to use automation to load parts directly from a stack into the first die, but couldn't. A centering system was needed to accommodate part varieties."

Centering systems come in many flavors, such as belt transfers, stops, back stops and side pushers. Other more expensive options employ servo motors to automatically set up the centering operation. The centering systems for large transfer or tandem line presses are engineered to handle a wide variety of parts and are thus more complex and more expensive. Replacing systems like these with a vision-guided robotic system can result in significant savings, Stephan insists, and increase the flexibility of press operations. He is quick to note that Fanuc employs its own vision systems, such as the iRVision system, which is integrated with Fanuc's R-J3iC robot controller. Billed as a ready-to-use robotic vision package, it requires only a camera and a cable and no additional vision hardware.

This pre-integration saves time and headaches, as Brian Boatner, product marketing manager for In-Sight vision sensors for Cognex, explains. "The easier it is to configure tight, seamless communications between the vision and the robot controller, the faster the application can be deployed."

Vision sensors exemplify the direction in which vision technology has been evolving. Relatively easy to deploy and costing, in some cases, as low as $1,000 to $2,000, these low-end vision products are remarkably powerful. "In terms of their capabilities," notes Zeuch, "today's vision sensors are equivalent to a full-blown vision system of 20 years ago."

What you need to know
"In many cases," notes Boatner, who feels that knowledge of the process can help potential vision users make more intelligent decisions, "Robot manufacturers use proprietary-bus architectures that complicate communications setup and use. To address this issue, it's important that the vision software include robot drivers, sample code (code that runs both on the vision system and the robot controller) and other tools that make it easy to properly format communication ports and data strings with minimal effort. Such tools make it easy for robotic systems integrators to set up communications between the vision system and a wide variety of robots without complex programming."

Setting up communications between a vision system and robot, says Boatner, is one of three key processes in deploying a vision-guided robot application. Another is calibrating or equating the vision system's pixel-based coordinate system with the robot's coordinate system. This vision-to-robot calibration is vital to maintaining system accuracy and repeatability. It's also a challenge, he says, "because it involves more than coming up with a scaling factor that relates pixels to a measured dimension. If there's optical distortion from the lens, or perspective changes due to camera mounting angle, the vision software must include special algorithms to correct for these image distortions."

And that's precisely what Cognex does. "In the past, calibration has been somewhat cumbersome, but standard practices have evolved to facilitate the task," says Boatner. "For instance, with our latest software we implemented a wizard-based dialogue to guide users through the process of correlating image pixels to robot coordinates using a variety of techniques. The process is simple, but the result is very powerful. These are algorithms that formerly ran on a PC, but can now be deployed on one of our In-Site vision sensors."

The third step is training the system to recognize the part you are looking for--pattern recognition in the lingo of the machine vision industry. This isn't as simple as it sounds, for the appearance of a part might vary due to a number of factors, such as inconsistent or poor lighting, vibration, variations in the production process and oil or cleaning solvents on the surface of the part, which are major sources of variation in stamping applications.

"Oil on parts, that's where a vision system is really tested," says Boatner. "Anyone can set up a machine vision system in a lab and have it run successfully, but to operate in real-world conditions the vision system has to withstand those changes to the part." To address this, many vision companies supply pattern recognition software. For Cognex it's PatMax. Algorithm intensive, the PatMax software formerly had to be run on a PC; now it runs on the company's In-Site vision sensors, another example of the "smaller, cheaper, more powerful" trend that has characterized the vision industry in recent years.

A look at the future?
Up to this point, both in this article and in stamping plants, the emphasis has been on destacking and alignment, operations performed at the front end of the stamping process. And there's a good reason for this. "The issues involved with getting sheet material from a stack and into a press are actually pretty simple, and we've seen significant interest in this," says Ben Dawson, director of strategic development for vision provider ipd, a Dalsa group. "The stack is essentially planar, which makes that one of the simpler applications for a vision system. It's only when you want to take that formed part and perform subsequent operations that the vision issues become more complex." Those are the issues that Karl Sachs is attempting to solve.

Sachs is president of Robot and Vision Mfg. With some help from Kuka Robotics, he has engineered a vision-guided, robotic, press tending system that destacks and feeds parts on the front end of the process, but also picks up formed parts on the fly as they come out of the press. "On the fly," or moving, is the key here. Sachs says there are no systems currently in use in U.S. pressrooms that pick up on the fly. As the part leaves the press on an exit conveyor, an overhead camera transfers movement and part skew information to the robot, enabling the robot to successfully grip the part even if it lies off-center on the moving conveyor. The system has been successfully demonstrated with an exit conveyor moving at 160 fpm.

However, on a contrary note to all of this, Tom Sipple, handling technology leader at Motoman, says, "Vision has its place, but if it's possible to locate the part mechanically that's probably going to be the lower-cost solution, and it will probably be more effective in terms of cycle time. So, a mechanical solution would be the preference. If, after a final operation, such as a final trim operation, parts become dislocated, then vision has a role to play in locating the part, but it's easier to maintain orientation, maintain position, than it is to get it back again.

"When it comes to blank stack, you've got to be pretty creative if you're going to use vision to aid in destacking. The stack might not be exactly where it is supposed to be, or the blanks may not be uniformly placed in the stack, so you have a potential for misreading. Also, vision could slow the process down.

"Vision can be very beneficial in some processes, but it's a whole lot easier simply not to lose location. In most pressroom applications the robot is used to picking up the part right after the part comes off the die, so in that case you know the position." FFJ

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