Anomaly detection for predictive maintenance in the cutting process is one of challenging problems shop-floor management. A modern machine learning approach, including deep learning, has been widely studied last decade. This study focuses on multimodality various time-series data extracting features status and proposes a multimodal variational autoencoder (MVAE) method. We collect time series v...

The cutting forces exerted by the cutting tool on the work piece during a machining action to be identified in order to control the tool wear and occurrence of vibration, thus to improve tool-life. Modeling of cutting force in milling is often needed in machining automation. The objective of this study is to predict the effects of cutting parameters on the variations of cutting forces during en...