MS-SSPCANet: A powerful deep learning framework for tool wear prediction

Deep learning-based tool wear prediction and its application for machining process using multi-scale feature fusion and channel attention mechanism

(2021) Xingwei Xu et al.   MEASUREMENT

Sound singularity analysis for milling tool condition monitoring towards sustainable manufacturing

(2021) Chang'an Zhou et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A robust condition monitoring methodology for grinding wheel wear identification using Hilbert Huang transform

(2021) Supriyo Mahata et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

A Meta-Invariant Feature Space Method for Accurate Tool Wear Prediction Under Cross Conditions

(2021) Changqing Liu et al.   IEEE Transactions on Industrial Informatics

A hybrid information model based on long short-term memory network for tool condition monitoring

(2020) Weili Cai et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Big data analytics for smart factories of the future

(2020) Robert X. Gao et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Randomized Non-linear PCA Networks

(2020) Mohammadreza Qaraei et al.   INFORMATION SCIENCES

A novel ResNet-based model structure and its applications in machine health monitoring

(2020) Jian Duan et al.   JOURNAL OF VIBRATION AND CONTROL

In-process tool condition forecasting based on a deep learning method

(2020) Huibin Sun et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Feature selection for predicting tool wear of machine tools

(2020) Wen-Nan Cheng et al.   The International Journal of Advanced Manufacturing Technology

Multi-frequency-bands deep CNN model for tool wear prediction

(2020) Jian Duan et al.   MEASUREMENT SCIENCE and TECHNOLOGY

A hybrid predictive maintenance approach for CNC machine tool driven by Digital Twin

(2020) Weichao Luo et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Intelligent analysis of tool wear state using stacked denoising autoencoder with online sequential-extreme learning machine

(2020) Jiayu Ou et al.   MEASUREMENT

Tool wear monitoring in micromilling using Support Vector Machine with vibration and sound sensors

(2020) Milla Caroline Gomes et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

A Review of Indirect Tool Condition Monitoring Systems and Decision-Making Methods in Turning: Critical Analysis and Trends

(2020) Mustafa Kuntoğlu et al.   SENSORS

Sensors selection for tool failure detection during machining processes: A simple accurate classification model

(2020) Mohamed Abubakr et al.   CIRP Journal of Manufacturing Science and Technology

Real-time tool wear monitoring using thin-film thermocouple

(2020) Tianxiang Li et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

A Switching Hidden Semi-Markov Model for Degradation Process and Its Application to Time-Varying Tool Wear Monitoring

(2020) Tongshun Liu et al.   IEEE Transactions on Industrial Informatics

Two-Dimensional Principal Component Analysis-Based Convolutional Autoencoder for Wafer Map Defect Detection

(2020) Jianbo Yu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

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

Tool wear monitoring and prediction based on sound signal

(2019) Meng-Kun Liu et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool wear classification using time series imaging and deep learning

(2019) Giovanna Martínez-Arellano et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Tool wear predicting based on multi-domain feature fusion by deep convolutional neural network in milling operations

(2019) Zhiwen Huang et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Time varying and condition adaptive hidden Markov model for tool wear state estimation and remaining useful life prediction in micro-milling

(2019) Weijian Li et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Deep heterogeneous GRU model for predictive analytics in smart manufacturing: Application to tool wear prediction

(2019) Jinjiang Wang et al.   COMPUTERS IN INDUSTRY

Monitoring of a machining process using kernel principal component analysis and kernel density estimation

(2019) Wo Jae Lee et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Tool condition monitoring techniques in milling process — a review

(2019) T. Mohanraj et al.   Journal of Materials Research and Technology-JMR&T

A method of NC machine tools intelligent monitoring system in smart factories

(2019) Wei Liu et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

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

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

Manufacturing big data ecosystem: A systematic literature review

(2019) Yesheng Cui et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Big Data Oriented Smart Tool Condition Monitoring System

(2019) Kunpeng Zhu et al.   IEEE Transactions on Industrial Informatics

Tool Wear Prediction via Multidimensional Stacked Sparse Autoencoders With Feature Fusion

(2019) Chengming Shi et al.   IEEE Transactions on Industrial Informatics

Tool Wear Estimation in End Milling of Titanium Alloy Using NPE and a Novel WOA-SVM Model

(2019) Dongdong Kong et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Squeeze-and-Excitation Networks

(2019) Jie Hu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

An Enhanced Deep Learning-Based Fusion Prognostic Method for RUL Prediction

(2019) Cheng-Geng Huang et al.   IEEE TRANSACTIONS ON RELIABILITY

PCANet: An energy perspective

(2018) Jiasong Wu et al.   NEUROCOMPUTING

A Selective Overview of Sparse Principal Component Analysis

(2018) Hui Zou et al.   PROCEEDINGS OF THE IEEE

FPCANet: Fisher discrimination for Principal Component Analysis Network

(2018) Kai Sun et al.   KNOWLEDGE-BASED SYSTEMS

Tool condition monitoring in interrupted cutting with acceleration sensors

(2017) Juho Ratava et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Tool wear monitoring and prognostics challenges: a comparison of connectionist methods toward an adaptive ensemble model

(2016) Kamran Javed et al.   JOURNAL OF INTELLIGENT MANUFACTURING

PCANet: A Simple Deep Learning Baseline for Image Classification?

(2015) Tsung-Han Chan et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition

(2015) Kaiming He et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE