Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0

Predictive Maintenance Architecture Development for Nuclear Infrastructure using Machine Learning

(2020) Hardik A. Gohel et al.   Nuclear Engineering and Technology

Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms

(2020) Jack C.P. Cheng et al.   AUTOMATION IN CONSTRUCTION

An integrated machine learning model for aircraft components rare failure prognostics with log-based dataset

(2020) Maren David Dangut et al.   ISA TRANSACTIONS

Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions

(2020) Martin W. Hoffmann et al.   SENSORS

An intelligent approach for data pre-processing and analysis in predictive maintenance with an industrial case study

(2020) Ebru Turanoglu Bekar et al.   Advances in Mechanical Engineering

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

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

Maintenance Models Applied to Wind Turbines. A Comprehensive Overview

(2019) Yuri Merizalde et al.   Energies

Thermal Imaging and Vibration-Based Multisensor Fault Detection for Rotating Machinery

(2019) Olivier Janssens et al.   IEEE Transactions on Industrial Informatics

Data-Driven Methods for Predictive Maintenance of Industrial Equipment: A Survey

(2019) Weiting Zhang et al.   IEEE Systems Journal

A new data analytics framework emphasising preprocessing of data to generate insights into complex manufacturing systems

(2019) Caoimhe M Carbery et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE

A new dynamic predictive maintenance framework using deep learning for failure prognostics

(2019) Khanh T.P. Nguyen et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

A systematic literature review of machine learning methods applied to predictive maintenance

(2019) Thyago P. Carvalho et al.   COMPUTERS & INDUSTRIAL ENGINEERING

Machine learning based concept drift detection for predictive maintenance

(2019) Jan Zenisek et al.   COMPUTERS & INDUSTRIAL ENGINEERING

Prediction of Motor Failure Time Using An Artificial Neural Network

(2019) Gustavo Scalabrini Sampaio et al.   SENSORS

Predictive Maintenance on the Machining Process and Machine Tool

(2019) Alberto Jimenez-Cortadi et al.   Applied Sciences-Basel

Dynamic control of intelligent parking guidance using neural network predictive control

(2018) Jong-Ho Shin et al.   COMPUTERS & INDUSTRIAL ENGINEERING

An HMM and polynomial regression based approach for remaining useful life and health state estimation of cutting tools

(2018) Akhilesh Kumar et al.   COMPUTERS & INDUSTRIAL ENGINEERING

Early Fault Detection of Machine Tools Based on Deep Learning and Dynamic Identification

(2018) Bo Luo et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Recursive Total Principle Component Regression Based Fault Detection and Its Application to Vehicular Cyber-Physical Systems

(2018) Yuchen Jiang et al.   IEEE Transactions on Industrial Informatics

Deep Learning for Infrared Thermal Image Based Machine Health Monitoring

(2018) Olivier Janssens et al.   IEEE-ASME TRANSACTIONS ON MECHATRONICS

Optimal maintenance policy incorporating system level and unit level for mechanical systems

(2018) Chaoqun Duan et al.   INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE

Fault detection of broken rotor bar in LS-PMSM using random forests

(2018) Juan C. Quiroz et al.   MEASUREMENT

A reliable technique for remaining useful life estimation of rolling element bearings using dynamic regression models

(2018) Wasim Ahmad et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Principal components analysis and track quality index: A machine learning approach

(2018) Ahmed Lasisi et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Real-time big data analytics for hard disk drive predictive maintenance

(2018) Chuan-Jun Su et al.   COMPUTERS & ELECTRICAL ENGINEERING

IDARTS – Towards intelligent data analysis and real-time supervision for industry 4.0

(2018) Ricardo Silva Peres et al.   COMPUTERS IN INDUSTRY

Fault Severity Monitoring of Rolling Bearings Based on Texture Feature Extraction of Sparse Time–Frequency Images

(2018) Yan Du et al.   Applied Sciences-Basel

Prognostics for an actuator based on an ensemble of support vector regression and particle filter

(2018) Runxia Guo et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING

A Manufacturing Big Data Solution for Active Preventive Maintenance

(2017) Jiafu Wan et al.   IEEE Transactions on Industrial Informatics

An ensemble classifier to predict track geometry degradation

(2017) Iván Cárdenas-Gallo et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

A big data driven sustainable manufacturing framework for condition-based maintenance prediction

(2017) Ajay Kumar et al.   Journal of Computational Science

Modeling preventive maintenance of manufacturing processes with probabilistic Boolean networks with interventions

(2016) Pedro J. Rivera Torres et al.   JOURNAL OF INTELLIGENT MANUFACTURING

An on-line weighted ensemble of regressor models to handle concept drifts

(2015) Symone Gomes Soares et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data

(2015) Rune Prytz et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis—Part I: Components and Subsystems

(2015) Wei Qiao et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

WPD-PCA-Based Laser Welding Process Monitoring and Defects Diagnosis by Using FNN and SVM

(2015) Deyong You et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Machine Learning for Predictive Maintenance: A Multiple Classifier Approach

(2015) Gian Antonio Susto et al.   IEEE Transactions on Industrial Informatics

Model development based on evolutionary framework for condition monitoring of a lathe machine

(2015) A. Garg et al.   MEASUREMENT

Machine learning approaches for improving condition-based maintenance of naval propulsion plants

(2014) Andrea Coraddu et al.   Proceedings of the Institution of Mechanical Engineers Part M-Journal of Engineering for the Maritime Environment

From Model, Signal to Knowledge: A Data-Driven Perspective of Fault Detection and Diagnosis

(2013) Xuewu Dai et al.   IEEE Transactions on Industrial Informatics

Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications

(2013) Jay Lee et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

An overview of time-based and condition-based maintenance in industrial application

(2012) Rosmaini Ahmad et al.   COMPUTERS & INDUSTRIAL ENGINEERING

A Predictive Maintenance System for Epitaxy Processes Based on Filtering and Prediction Techniques

(2012) Gian Antonio Susto et al.   IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING

LIBSVM

(2012) Chih-Chung Chang et al.   ACM Transactions on Intelligent Systems and Technology

A review of data mining applications for quality improvement in manufacturing industry

(2011) Gülser Köksal et al.   EXPERT SYSTEMS WITH APPLICATIONS

A data mining approach considering missing values for the optimization of semiconductor-manufacturing processes

(2011) Doh-Soon Kwak et al.   EXPERT SYSTEMS WITH APPLICATIONS

Fault classification technique for series compensated transmission line using support vector machine

(2009) Urmil B. Parikh et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS