Simple machine learning allied with data-driven methods for monitoring tool wear in machining processes

A novel method for accurately monitoring and predicting tool wear under varying cutting conditions based on meta-learning

(2019) Yingguang Li et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Heterogeneous data-driven hybrid machine learning for tool condition prognosis

(2019) Peng Wang et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

A Cyber-Physical Machine Tools Platform using OPC UA and MTConnect

(2019) Chao Liu et al.   JOURNAL OF MANUFACTURING SYSTEMS

Research on the Milling Tool Wear and Life Prediction by Establishing an Integrated Predictive Model

(2019) Yinfei Yang et al.   MEASUREMENT

Relevance vector machine for tool wear prediction

(2019) Dongdong Kong et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Toward Intelligent Machine Tool

(2019) Jihong Chen et al.   Engineering

Data-driven smart manufacturing: Tool wear monitoring with audio signals and machine learning

(2019) Zhixiong Li et al.   Journal of Manufacturing Processes

Tool wear monitoring using an online, automatic and low cost system based on local texture

(2018) María Teresa García-Ordás et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process

(2018) Fatemeh Aghazadeh et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

(2017) Dazhong Wu et al.   JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME

Cutting tool wear detection using multiclass logical analysis of data

(2017) Yasser Shaban et al.   MACHINING SCIENCE AND TECHNOLOGY

A computer vision approach to analyze and classify tool wear level in milling processes using shape descriptors and machine learning techniques

(2016) María Teresa García-Ordás et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Monitoring of tool wear using measured machining forces and neuro-fuzzy modelling approaches during machining of GFRP composites

(2015) A.I. Azmi   ADVANCES IN ENGINEERING SOFTWARE

Tool wear predictability estimation in milling based on multi-sensorial data

(2015) P. Stavropoulos et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Reliability assessment of cutting tool life based on surrogate approximation methods

(2014) Konstantinos Salonitis et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool wear monitoring using naïve Bayes classifiers

(2014) Jaydeep Karandikar et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool wear monitoring by machine learning techniques and singular spectrum analysis

(2010) Bovic Kilundu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING