Automated Meat Processing

Tag: hydraulic pressure tool

The job of meat processing demands that workers wield heavy cutting equipment in difficult environments during long shifts. One study by David Caple & Associates suggests that 50% of all work-related injuries in meat processing are due to repetitive manual operations.
Seeking to offer a better and safer solution for various meat-processing operations, Jarvis Products took on one of the most challenging vision-system applications, visual servoing—using vision to guide a robot to a moving target so that an industrial operation can be accurately performed. Speed and robustness were essential to all the components, according to Dan Driscoll, automation engineering manager of Jarvis.

Jarvis developed the JR-50 robot for hock, or hoof, cutting based on a manual Jarvis 30CL cutter mounted on a Motoman six-axis robotic arm guided by a TYZX DeepSea G2 embedded vision system for real-time 3-D machine-vision robotic guidance. Hock cutting happens in the early stages of meat processing. A beef carcass is hung from a chain-driven suspended hook when it enters the hock-cutting station. Typically, a worker wielding a 30-lb 30CL hydraulic- or pneumatic-assisted hock cutter snips the hocks from the carcass before it moves on.
Designed to cut through bone and survive daily washdowns, the 30CL is a heavy, counter-weighted stainless-steel scissor cutter that can tire a strong man during an eight-hour shift. With the combination of a proprietary high-refresh-rate robot controller and high-speed 3-D vision guidance, the automated system for removing the hock from the beef has been accurately performed thousands of times at a major US meat-processing plant since late 2007.

To cut down on worker fatigue while improving safety and repeatability, Jarvis decided to mount the 30CL on the end of a Motoman 50-kg, six-axis robotic arm. “With the tool and associated hydraulic lines, we could get away with a 50-kg robot, but we had to develop our own robot controller. At the time, Motoman didn’t supply a controller that could update the trajectory as often as we needed to find a moving target,” explains Driscoll.
Fast frame rates and the use of 3-D rather than 2-D image data were critical design parameters for the vision system. As the hock-cutting process begins, the carcasses pass between two rub bars, which help to stabilize the swinging carcass. Driscoll added mechanical limits to the robot enclosure to further limit movement, but periodic starting and stopping of the line for upstream and downstream operations guaranteed that carcasses would swing. The vision system would have to be truly real-time 3-D vision. “We tried it with a 2-D vision system, but realized we had further to go,” Driscoll adds.
Better than real time
The vision system has to perform better than the robot’s tolerances if the system was going to succeed. “We selected the TYZX vision system because of the 50-frame/s rate,” Driscoll says. “We’re not there yet, but we hope to be, and that will allow us to update the robot at 50 Hz. We continuously modify the robot’s trajectory all the way until the cutter is ready to go. That’s what you have to do if you want to try to hit a moving target.”
Location coordinates for each hock in the field of view, which can include several animals at a time, are fed to the Jarvis controller over the Ethernet from the TYZX G2. The G2 is a stereo vision system that includes two Micron Technology 752 × 480-pixel CMOS sensors in a factory-calibrated enclosure to maintain the spacing required for accurate 3-D triangulation. It includes an AMCC 440GX PowerPC-based computer running an embedded Linux operating system, a Xilinx FPGA, and the TYZX DeepSea G2 application-specific integrated circuit and sufficient memory to support each chipset