Adoption of machine learning technology for failure prediction in industrial maintenance: A systematic review

Degradation stage classification via interpretable feature learning

(2021) Antonio L. Alfeo et al.   JOURNAL OF MANUFACTURING SYSTEMS

AKSNet: A novel convolutional neural network with adaptive kernel width and sparse regularization for machinery fault diagnosis

(2021) Zhuang Ye et al.   JOURNAL OF MANUFACTURING SYSTEMS

Big data analytics for intelligent manufacturing systems: A review

(2021) Junliang Wang et al.   JOURNAL OF MANUFACTURING SYSTEMS

LearningADD: Machine learning based acoustic defect detection in factory automation

(2021) Tao Zhang et al.   JOURNAL OF MANUFACTURING SYSTEMS

Health monitoring and fault prediction using a lightweight deep convolutional neural network optimized by Levy flight optimization algorithm

(2021) M. P. Rajakumar et al.   NEURAL COMPUTING & APPLICATIONS

Improving the accuracy of global forecasting models using time series data augmentation

(2021) Kasun Bandara et al.   PATTERN RECOGNITION

Data-driven exploratory models of an electric distribution network for fault prediction and diagnosis

(2020) Daniela Renga et al.   COMPUTING

Applications of machine learning to machine fault diagnosis: A review and roadmap

(2020) Yaguo Lei et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Online RBM: Growing Restricted Boltzmann Machine on the fly for unsupervised representation

(2020) Ramasamy Savitha et al.   APPLIED SOFT COMPUTING

Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics

(2020) Juan José Montero Jimenez et al.   JOURNAL OF MANUFACTURING SYSTEMS

Performance Degradation Prediction Based on a Gaussian Mixture Model and Optimized Support Vector Regression for an Aviation Piston Pump

(2020) Chuanqi Lu et al.   SENSORS

Machine Learning Approach Using MLP and SVM Algorithms for the Fault Prediction of a Centrifugal Pump in the Oil and Gas Industry

(2020) Pier Francesco Orrù et al.   Sustainability

A generic fault prognostics algorithm for manufacturing industries using unsupervised machine learning classifiers

(2020) Nikolaos Kolokas et al.   SIMULATION MODELLING PRACTICE AND THEORY

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

(2020) Zeki Murat Çınar et al.   Sustainability

Machine learning approach for pavement performance prediction

(2019) Pedro Marcelino et al.   International Journal of Pavement Engineering

A Process to Implement an Artificial Neural Network and Association Rules Techniques to Improve Asset Performance and Energy Efficiency

(2019) Adolfo Crespo Márquez et al.   Energies

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

(2019) Weiting Zhang et al.   IEEE Systems Journal

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

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

A Global Manufacturing Big Data Ecosystem for Fault Detection in Predictive Maintenance

(2019) Wenjin Yu et al.   IEEE Transactions on Industrial Informatics

Big data and stream processing platforms for Industry 4.0 requirements mapping for a predictive maintenance use case

(2019) Radhya Sahal et al.   JOURNAL OF MANUFACTURING SYSTEMS

A Robust Prescriptive Framework and Performance Metric for Diagnosing and Predicting Wind Turbine Faults Based on SCADA and Alarms Data with Case Study

(2018) Kevin Leahy et al.   Energies

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

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

Initiating predictive maintenance for a conveyor motor in a bottling plant using industry 4.0 concepts

(2018) Kahiomba Sonia Kiangala et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning

(2018) Yuyan Zhang et al.   JOURNAL OF MANUFACTURING SYSTEMS

Combining granular computing technique with deep learning for service planning under social manufacturing contexts

(2018) Jiewu Leng et al.   KNOWLEDGE-BASED SYSTEMS

Artificial intelligence for fault diagnosis of rotating machinery: A review

(2018) Ruonan Liu et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders

(2018) Haidong Shao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Diagnosis of the Hollow Ball Screw Preload Classification Using Machine Learning

(2018) Yi-Cheng Huang et al.   Applied Sciences-Basel

Deep learning and its applications to machine health monitoring

(2018) Rui Zhao et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Machine learning methods for wind turbine condition monitoring: A review

(2018) Adrian Stetco et al.   RENEWABLE ENERGY

Online feature learning for condition monitoring of rotating machinery

(2017) S. Martin-del-Campo et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Learning from class-imbalanced data: Review of methods and applications

(2017) Guo Haixiang et al.   EXPERT SYSTEMS WITH APPLICATIONS

Predictive maintenance based on event-log analysis: A case study

(2017) J. Wang et al.   IBM JOURNAL OF RESEARCH AND DEVELOPMENT

Machine Learning Model for Event-Based Prognostics in Gas Circulator Condition Monitoring

(2017) Jason J. A. Costello et al.   IEEE TRANSACTIONS ON RELIABILITY

The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance

(2017) Bram de Jonge et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Granular computing–based development of service process reference models in social manufacturing contexts

(2016) Jiewu Leng et al.   CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS

A quantum multi-agent based neural network model for failure prediction

(2016) Wei Wu et al.   Journal of Systems Science and Systems Engineering

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

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

Machine Learning for Predictive Maintenance: A Multiple Classifier Approach

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

Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

(2015) Jianbo Yu   JOURNAL OF SOUND AND VIBRATION

Machine learning: Trends, perspectives, and prospects

(2015) M. I. Jordan et al.   SCIENCE

The journal coverage of Web of Science and Scopus: a comparative analysis

(2015) Philippe Mongeon et al.   SCIENTOMETRICS

Improving rail network velocity: A machine learning approach to predictive maintenance

(2014) Hongfei Li et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

A survey on feature selection methods

(2013) Girish Chandrashekar et al.   COMPUTERS & ELECTRICAL ENGINEERING

An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics

(2013) Victoria López et al.   INFORMATION SCIENCES

LIBSVM

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

A Data-Mining Approach to Monitoring Wind Turbines

(2011) Andrew Kusiak et al.   IEEE Transactions on Sustainable Energy

GUIDELINES FOR IMPLEMENTING PREDICTIVE MAINTENANCE*

(2010) KATHLEEN E. MCKONE et al.   PRODUCTION AND OPERATIONS MANAGEMENT

Learning from Imbalanced Data

(2009) Haibo He et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement

(2009) David Moher et al.   PLOS MEDICINE