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CANADA'S LEADING INFORMATION SOURCE FOR THE METALWORKING INDUSTRY

CANADA'S LEADING INFORMATION SOURCE FOR THE METALWORKING INDUSTRY

Why you should be teaching your robots through Offline Robot Programming

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Robots have a costly downside that comes into play when they have to be taken down for updating or reprogramming. But there is a better way. IMAGE: courtesy TRUMPF

With the global industrial robotics market expected to total US$ 33.75 billion by the end of this year, it’s fair to say manufacturing has locked into the advantages of automation. But robots do have a downside and it can be a costly one.

That downside comes into play when the robots need to be programmed. Most metal manufacturers are currently taking their industrial robots down and updating or programming them via teach pendant, a laborious, time consuming and inefficient process which leads to lost revenue. Complex paths can require hundreds, if not thousands, of points that can take days to program manually. As Patrick Lazzaroni, technical sales support manager with Staubli Robotics, acknowledges, the traditional way to teach a point is to directly teach the robot but when you’re talking about thousands of points it’s often not feasible.

There is a better way, although it’s not yet well known. It’s called Offline Robot Programming (OLP) and it does essentially what it says: it takes robot programming “offline”, away from the teach pendant/robot cell,  allowing the user to generate the robotic code on another computer and upload it to the robot.

OLP may be relatively new on the robotics side but it’s burrowing on practices already in place for some time on the machining side, explains Cory John, software sales manager with Robotmaster, a Hypertherm Associates brand.

“Twenty years ago you were programming your three- or five-axis machines at the controller. Now almost everyone has gone from teaching it at the controller to bringing it into a CAD/CAM environment,” John points out. “You have a standard process to create your path out of the CAD/CAM software, bring it through simulation, and once you have a path that you like, you bring it out to your machine.”

With OLP new robot programs are created offline without interrupting the current program running. image: hypertherm
With OLP new robot programs are created offline without interrupting the current program running. IMAGE: courtesy Hypertherm

The OLP software for the robotic process is very similar. OLP software works with 3D CAD models to define tasks such as path planning, programming, and engineering. All the programming is completed in the virtual space using either OEM or 3rd party software, which allows for troubleshooting and problem solving before the robot has been installed. Programs can be created, simulated, and edited in the OLP environment, ensuring that the robot will perform as required once it is installed. OLP is particularly helpful in ensuring the right size robot is selected for the application, providing first time buyers with the confidence they have the right robot for their operational requirements. Subsequently when a robot needs to be reprogrammed, new programs can be created offline and uploaded to the robot, without interruption to the current program that is running.

“You typically have your machine running while you’re creating a new program. So the machine is running making parts while you’re developing the next generation part program offline. You’re minimizing the actual amount of time that you have to shut the machine down to actually teach and test,” explains Keith Luce, motion control programmer with Arc Specialties, an integrator. “It could take up to 500 points to actually track a path appropriately. You can imagine teaching every single one of those points with a joystick. It takes a considerable amount of time whereas with OLP software it could take five minutes to create that path.”

Luce and John Martin, vice president of operations at Arc Specialties, recently took part in a webinar about OLP, sharing their experiences with putting the software into place. Martin said he’s finding that OLP is paying dividends even before using it to reprogram robots. He’s using it in the initial sale of a project to fabricators and other customers.

“It’s a quick and easy way to get a customer up to speed on how our proposed system satisfies their need. We also use it during the design phase so you can see where the robot reach is and where the tooling needs to be,” Martin says.

Is there a typical size of company that is best suited for the advantages of OLP? John argues it’s not size that matters but rather the nature of the company’s operations. In a high-mix, low-volume environment this programming down time works against the flexibility of changing a robot to perform a different task.

“When I talk about the typical size of company, it really doesn’t matter. We’ve gone anywhere from a guy with one robot in the back shed to $300 billion aerospace companies using the software,” John says. “Really what we look for is are you doing production runs where you’re going to do the same thing over and over again for two years and never have to reteach the robot? Or are you doing runs of five or 500 or 1000 and every time you take that robot down it’s lost revenue. Small runs and the ability to adapt to changes to parts is really a big part of what OLP brings to the table.”

Of course, any time investment in a new software platform is a question, return on investment (ROI) is a consideration.

“Obviously the question is what am I going to get back for it? There are really two ROIs when looking at OLP,” says John. “One, is purely time. You have an engineer or a programmer, who if they’re doing it on a teach pendant – we have cases where it took them 15 hours before and now they’re doing it in 15 minutes. We’ve had some spaces in the aerospace industry where it took 30 something days to handle a program for a very complex part and we did it in about a day and a half with OLP. So you get the time savings. The second ROI is that every time you take that robot down, you’re losing money. You’re not creating parts. With OLP you keep your robot in production. “

There are further considerations, however, which can affect the ROI of an OLP investment. First is usability. The OLP should be easy to operate. Staff shouldn’t need advanced training in computer programming or robotics to operate it. Easy-to-use, intuitive software gets used more readily. Beginners can learn it quickly and grow into power users, making for minimal disruption to operations thus improving the ROI.

Most robot manufacturers have their own software specific to their brand. These are proprietary systems and are likely not compatible across multiple brands. Opting for an OLP that is robot brand agnostic provides the flexibility of using one language to create your path and exporting it in many different robot languages.

“In robotics every manufacturer has a different language that they post in. With robot diagnostic OLP the user doesn’t have to worry about that. The software will post to the correct language for the specific robot,” says John. “Maybe on your shop floor you have four different robot brands. If one of the robots needs to go down for servicing or be used for a different product, very easily you can take that program you already created for a Fanuc robot and move it to your Staubli robot. All you have to do is change out the cell, maybe fix any issues that have changed with the kinematics with the robot changing in the new cell, and just post it outright to the Staubli code. The ability to bounce back and forth between different robot brands is a big plus for agnostic OLP.”

OLP’s main challenge seems to be how few people in the industry know about it.

“Very often we have to introduce the concept and explain what it is. It’s not a concept that is fully known at this point,” attests Lazzaroni.

With so many advantages, however, that may not remain true for long. SMT

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