Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0
出版年份 2020 全文链接
标题
Machine Learning in Predictive Maintenance towards Sustainable Smart Manufacturing in Industry 4.0
作者
关键词
-
出版物
Sustainability
Volume 12, Issue 19, Pages 8211
出版商
MDPI AG
发表日期
2020-10-05
DOI
10.3390/su12198211
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- 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
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