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ampd

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    Chetan Sharma authored
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    assets
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    Automatic Modeling of Machining Processes

    A CNC controller that learns material characteristics and optimizes its own feeds and speeds.

    Project Status

    Finishing thesis writing.

    Current Goals

    The goal of this project is to make a system that faces a material using an endmill while simultaneously performing regression on sensor data to complete its model. This model is used to optimize subsequent passes (feedrate and WOC) by means of an objective function that weighs MMR against the chance of failure (deflection, breakage, spindle overload).

    Modeling

    Models for forces experienced during the cutting process and models for tool / machine failure are in software/models.py.

    The linear model converges well when given test data sweeps.

    Optimization

    The optimization systems are in software/models.py

    The system successfully finds optimal cutting parameters for most materials.

    A video demonstrating convergence

    More convergence graphs can be found in assets/ammp_graphs

    Hardware

    The hardware setup is finished. The machine is a Taig Micro Mill (kindly donated by Ted Hall).

    The spindle motor is an MDX servomotor from Applied Motion products.

    A 1D tool-force dynamometer was constructed using a Schneeberger frictionless slide and a disc-type preloaded load cell.

    The machine electronics are enclosed for safety.

    Software

    The machine controller is in the software folder. ammp.py contains the optimization loop.