khazzan / toolwearID

Development of an in-situ digital inspection of tool wear for turning inserts. The model and training is based on EfficientNet and TensorFlow Lite. Input images are obtained from a digital microscope.

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In-situ Digital Inspection of Tool Wear

An open source model to detect and identify in-situ or in-process wear and tool damage on turning inserts

Motivation

Aim to integrate in-situ tool wear identification to make informaed decision on reconditioning and recycling of tool inserts (Hazzan KE, Pacella M, A novel laser machining strategy for cutting tool repair. Manuf Lett 2022; 32C:87-91. https://doi.org/10.1016/j.mfglet.2022.04.005)

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Development of an in-situ digital inspection of tool wear for turning inserts. The model and training is based on EfficientNet and TensorFlow Lite. Input images are obtained from a digital microscope.

License:Apache License 2.0


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