Prediction of Tool Wear Using Artificial Neural Networks during Turning of Hardened Steel

A novel method of assessing and predicting coated cutting tool wear during Inconel DA 718 turning

(2019) S. Capasso et al.   WEAR

Toward a new tribological approach to predict cutting tool wear

(2018) J. Rech et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

A novel approach for real-time prediction and prevention of tool chipping in intermittent turning machining

(2018) M. Hassan et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Review of tool condition monitoring methods in milling processes

(2018) Yuqing Zhou et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Gaussian process regression for tool wear prediction

(2018) Dongdong Kong et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Hidden semi-Markov model-based method for tool wear estimation in milling process

(2017) Dongdong Kong et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A real-time tool failure monitoring system based on cutting force analysis

(2017) Xuechun Shi et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Development of a dynamic surface roughness monitoring system based on artificial neural networks (ANN) in milling operation

(2015) AmirMahyar Khorasani et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool life estimation based on acoustic emission monitoring in end-milling of H13 mould-steel

(2015) O. Olufayo et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool condition monitoring (TCM) using neural networks

(2015) Tien-I Liu et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Force sensor based online tool wear monitoring using distributed Gaussian ARTMAP network

(2013) Guofeng Wang et al.   SENSORS AND ACTUATORS A-PHYSICAL