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 at the University of Maryland have achieved a first in lithium-ion battery science: the development of a successful lithium-based battery using one material for all three core components of a battery -- anode, cathode, and electrolyte.
The online Bar Steel Fatigue Database for automotive design engineers has been updated for the fifth time and now contains 134 iterations, or grade/process combinations. It provides better predictability for designing parts with long-term reliability and durability.
FPGAs use programmable fabric to create custom logic, but this flexibility comes at a cost -- usually around 10 times more silicon real estate and 10 times the power dissipation. Can we really claim any FPGA is low power?
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