Skip to main content

AI REGIO AI4CNC - A Federated Learning System Platform Development for CNCs

The AI4CNC experiment is designed to develop a Federated Learning System Platform for CNC machines to estimate tool wear through AI models and secure data sharing. The main objective is to use data from TEKNOPAR's CNC machines and sensors to estimate tool wear, replace tools at the optimum time to minimize costs and potential defects and address privacy concerns by proposing a Federated Learning (FL) model for CNC tool wear trained and executed on the edge. The AI4CNC experiment leverages federated learning to enable collaborative learning onedge devices while keeping the training data on the device. This approach aims to preserve data confidentiality and ownership by training a model using data collected from multiple CNCs at the real site of the experiment and then distributing the trained model to the data sources for edge execution. The goals were achieved by successfully implementing the planned activities and adjusting the approach to utilize sensor data instead of tool wear measurements for training AI models.