Bob Percell, president of CAMotion, wants to put motion control within the reach of manufacturing processes that involve repetitive operations, but don't need expensive robotics. The company is using software algorithms developed at the Georgia Institute of Technology as the foundation of a motion-control system that will help manufacturers reduce labor involved with routine-inspection and material-handling tasks. Two types of algorithms are used in the CAMotion software. The first is a vibration-control algorithm that plans the robotic-axis trajectory. By damping out vibration, it allows use of lighter and less-expensive components. A learning algorithm helps the equipment improve its own performance. "Once the machine makes the moves through about five iterations, it learns the open loop, gets more accurate, and reduces the dynamic error by a factor of ten," says Purcell. The software also combines machine vision, encoders, and accelerometers for helping the system know its own location relative to the work. Percell says that software combined with smaller components can reduce automation costs from 10 to 30% in many applications.
The standards electrical machines and components are required to meet in the food processing industry are far more stringent than those in traditional plant construction. For specialized production environments such as these, components must not only resist thermal and physical stresses, but they must also be resistant to the chemicals used to sterilize equipment.
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