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A methodology and experimental implementation for industrial robot health assessment via torque signature analysis
(MDPI AG, 2020)
This manuscript focuses on methodological and technological advances in the field of health assessment and predictive maintenance for industrial robots. We propose a non-intrusive methodology for industrial robot joint ...
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects
(Springer Science+Business Media, LLC, 2022)
Given the growing amount of industrial data in the 4th industrial revolution, deep learning solutions have become popular for predictive maintenance (PdM) tasks, which involve monitoring assets to anticipate their requirements ...
Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge
(Taylor and Francis, 2022)
The 4th industrial revolution has connected machines and industrial plants, facilitating process monitoring and the implementation of predictive maintenance (PdM) systems that can save up to 60% of maintenance costs. ...
Adaptable and Explainable Predictive Maintenance: Semi-Supervised Deep Learning for Anomaly Detection and Diagnosis in Press Machine Data
(MDPI, 2021)
Predictive maintenance (PdM) has the potential to reduce industrial costs by anticipating failures and extending the work life of components. Nowadays, factories are monitoring their assets and most collected data belong ...
A novel machine learning‐based methodology for tool wear prediction using acoustic emission signals
(MDPI, 2021)
There is an increasing trend in the industry of knowing in real-time the condition of their assets. In particular, tool wear is a critical aspect, which requires real-time monitoring to reduce costs and scrap in machining ...
