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Robot picking up parts

Vibration affects all machines that move, including robots. Ulendo is a startup that launched with a vibration compensation algorithm for fused filament fabrication (FFF) 3D printers and is now working to apply it to robots.

Any machine that moves deals with vibration, whether it’s a 3D printer, machine tool or robot. It’s typically managed to the point that many do not even realize that vibration is a problem, but with proper strategies to deal with vibration, machines can run faster and more efficiently. Ulendo is an Ann Arbor, Michigan-based startup that produces software solutions for manufacturing automation. The company launched with a product that’s now called Ulendo VC (for “vibration compensation”), which applies an algorithm to fused filament fabrication (FFF) 3D printers, counteracting the machine’s vibration patterns and enabling it to run up to five times faster while maintaining part quality.

Since the launch of Ulendo VC, the company has expanded into laser powder bed fusion (LPBF) additive manufacturing with Ulendo HC (heat compensation), which optimizes the path of an LPBF machine’s laser to reduce heat-induced deformation and stress. It’s also offering Ulendo Calibration-as-a-Service, which applies its vibration compensation to end-users’ extrusion 3D printers (as opposed to working with machine suppliers, as is the case with Ulendo VC). The company is also broadening its reach to include machines outside the 3D printing space with its fourth product: vibration compensation for robots.

Founder Chinedum Okwudire describes one application involving cameras mounted on robot arms for inspection. The cameras vibrated when the robots stopped moving and had to wait 30 times longer than it took to move the robot into position to stop vibrating enough to take a clear image. Provided by Ulendo. 

Not-So-Good Vibrations

Vibration affects robots in much the same way as 3D printers. “It's the same problem showing up in different ways for different applications,” explains Ulendo founder and University of Michigan mechanical engineering professor Chinedum Okwudire. He describes one use case where an automotive manufacturer was using robots mounted with cameras to complete visual inspection tasks. When the robots moved into position and stopped, the robots, and therefore the cameras, continued to vibrate. “You can't take the image while the camera is vibrating, because you get a blurry image, so they’d have to wait for the camera to stop vibrating,” he explains. This resulted in much longer cycle times — he says the camera took 30 times longer to stop vibrating enough to take a photo than it took for the robot to move the camera into position. Longer cycle times can mean significant losses in productivity. And Okwudire points out that as development and adoption of AI increases, so will demand for applications such as these.

Vibration can also damage delicate parts, as in the case of electronics assembly applications. The silicon wafers used in semiconductors are fragile, so any vibrations that occur as a robot places a wafer into a cassette could damage the wafer. “They have to go very slowly to avoid that,” Okwudire explains.

Moving the robot slower is the most common vibration mitigation strategy. Adding friction to damp vibration is another option, though this causes additional wear and tear on the robot and increases energy needs. Reducing payload is another common method to reduce vibration in robotics. In fact, Okwudire says experts often recommend robots and cobots carry payloads that are half the weight of the listed maximum payload to reduce vibration. This “is a big issue for robotics where payload really matters,” he notes.

Person programming robot with teach pendant

Ulendo’s VC algorithm works by creating a “calibration map” that predicts how the machine will vibrate, and then adjusting its movement to offset the vibration (so if the machine veers to the right, VC adjusts its motion to the left and the machine will go straight). However, applying VC to robots is more complicated than 3D printers because a robot’s calibration map will change based on its payload and position.

Vibration Compensation

Ulendo’s solution actually compensates for a machine’s vibrations instead of working around them. It does this by “tricking the machine,” as Okwudire describes it. Traditionally, Ulendo measures the machine’s vibration patterns and creates a “calibration map” that predicts how the machine will vibrate and calculates how to offset that motion. So, if a machine veers to the left instead of going straight, Ulendo VC-R (vibration compensation for robots) adjusts the path to the right, which cancels out the leftward motion and causes the machine to go straight.

However, Okwudire notes that robots are a much more complex application for the underlying vibration compensation algorithm than 3D printers. Extrusion 3D printers have a constant payload (the printer nozzle), and limited motion (usually three axes). Robots, on the other hand, can have varying payloads and many more axes of motion. The robot’s vibration patterns change based on its position and what it’s holding, making vibration more difficult to predict and compensate. However, some robotics applications involve payloads that don’t change, as in the cases of the robots with the camera and silicon wafers. Given that the vibration will only vary based on the robot’s position, these applications are good starting points for Ulendo VC-R. 

For situations where the payload changes between jobs, as in the case of a machine tending robot that’s switching from one part to another, Okwudire says vibration compensation would function much like the calibration-as-a-service product it offers for 3D printers — the robot would re-calibrate the vibration map between tasks.

In the most complex scenario, the payload is constantly changing throughout the course of the job, such as pick-and-place tasks with an assortment of objects. Okwudire says AI or machine learning approaches could make this possible but adds that this would be further in the future.

Okwudire acknowledges that other software products in the robotics space are designed to handle vibration compensation in repeating tasks. He notes that these products are only suitable for robots that perform the same motion repeatedly. Any deviation from the motion or task for which they were calibrated would require the robots to be recalibrated. Ulendo aims to set itself apart by creating a solution that doesn’t need robots to be calibrated for each new motion or task.

Person programming cobot with teach pendant

Vibration compensation could make lower-cost robots and cobots safer and more efficient, making automation more available to a wider range of manufacturers.

Democratizing Robots

Vibration compensation would enable robots to move faster and handle heavier payloads without changing the robot’s hardware, meaning they could handle more tasks. This is especially true for collaborative robots, which have extra compliance in their joints. This makes them safer, but also increases vibration, sometimes to the point that these robots are unusable. Okwudire describes one 3D printer manufacturer that purchased a cobot to aid in production of its 3D printers. The cobot wasn’t precise enough for production, so it was relegated to serving beer to employees. Vibration compensation can ensure these cobots are both safe and efficient.

As with 3D printers, vibration compensation can make lower-cost robots and cobots more powerful in terms of speeds and payloads. Okwudire says Ulendo is working with a company that’s developing a low-cost robot in the $10-15,000 range for small and medium-sized manufacturers. Vibration compensation software will be key in ensuring the robot is safe, low-cost and precise and will help “democratize robots in manufacturing,” he says.

A calibration-as-a-service model will also enable manufacturers to get more use out of the robots they already have. “There are robots in the field already that have been used for a couple of years, and we can breathe new life into them,” says CEO Brenda Jones. “That means manufacturers who have made a big investment in these robots, when they need to expand capacity, instead of buying new robots, they can just increase the throughput or the capabilities of their existing investments.”

About the Author

Julia Hider is a senior editor for Modern Machine Shop, where she writes about the metalworking industry. She also serves as the robotics and autonomy correspondent for parent company Gardner Business Media. To find more of her content, SUBSCRIBE HERE.

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