+128% more productivity in laser metal deposition
How aiXopt increases productivity in a high-variance process while meeting quality specifications.
How aiXopt tunes the control loops of an existing milling machine to varying machine behavior and gets the most out of the hardware already in place.
The feed control of a CNC milling machine consists of a controller and a filter with parameters that even experienced machining experts can hardly relate to: prediction horizon, control horizon and weightings. At the same time the machine never behaves exactly like its model, since stiffness and damping vary with tool, material and wear. A setting designed on the nominal model met the overshoot limit in only half of the validation runs.
aiXopt's Small-Data AI tunes controller and filter together and deliberately evaluates every setting under the least favorable machine behavior. The result: settings that stayed within tolerance in every validation run, with better path accuracy than the hand-tuned starting parametrization. The existing control loops and hardware remain unchanged, they are simply used better.
How aiXopt increases productivity in a high-variance process while meeting quality specifications.
How aiXopt lowers the defect rate in a high-volume process.
How aiXopt tunes a process using nothing but qualitative feedback from the operators.
How aiXopt optimally tunes a process engineering system with multiple components, operating points and safety limits without putting the plant at risk.
How aiXopt tunes a multi-zone temperature control across the whole operating range instead of for a single operating point.
How aiXopt makes a path controller tunable through understandable objectives instead of controller parameters only experts understand.
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