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.
Californiaís plan to mandate an electric vehicle market isnít the first such undertaking and certainly wonít be the last. But as the Golden State ratchets up for its next big step toward zero-emission vehicle status in 2018, it might be wise to consider a bit of history.
A customer who was thermal printing strip steel had a problem: When the strip's speed increased, the thermo printer would catch fire. When he set a flame to a piece of the strip, he couldn't get it to burn. What was the problem?