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.
Researchers have been working on a number of alternative chemistries to lithium-ion for next-gen batteries, silicon-air among them. However, while the technology has been viewed as promising and cost-effective, to date researchers haven’t managed to develop a battery of this chemistry with a viable running time -- until now.
Norway-based additive manufacturing company Norsk Titanium is building what it says is the first industrial-scale 3D printing plant in the world for making aerospace-grade metal components. The New York state plant will produce 400 metric tons each year of aerospace-grade, structural titanium parts.
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