An overview of time-based and condition-based maintenance in industrial application
This paper presents an overview of two maintenance techniques widely discussed in the
literature: time-based maintenance (TBM) and condition-based maintenance (CBM). The …
literature: time-based maintenance (TBM) and condition-based maintenance (CBM). The …
A review of the use of artificial neural network models for energy and reliability prediction. A study of the solar PV, hydraulic and wind energy sources
J Ferrero Bermejo, JF Gómez Fernández… - Applied Sciences, 2019 - mdpi.com
The generation of energy from renewable sources is subjected to very dynamic changes in
environmental parameters and asset operating conditions. This is a very relevant issue to be …
environmental parameters and asset operating conditions. This is a very relevant issue to be …
[HTML][HTML] A Digital Twin predictive maintenance framework of air handling units based on automatic fault detection and diagnostics
The building industry consumes the most energy globally, making it a priority in energy
efficiency initiatives. Heating, ventilation, and air conditioning (HVAC) systems create the …
efficiency initiatives. Heating, ventilation, and air conditioning (HVAC) systems create the …
Data-driven predictive maintenance planning framework for MEP components based on BIM and IoT using machine learning algorithms
Facility managers usually conduct reactive maintenance or preventive maintenance
strategies in building maintenance management. However, there are some limitations that …
strategies in building maintenance management. However, there are some limitations that …
Multiobjective deep belief networks ensemble for remaining useful life estimation in prognostics
In numerous industrial applications where safety, efficiency, and reliability are among
primary concerns, condition-based maintenance (CBM) is often the most effective and …
primary concerns, condition-based maintenance (CBM) is often the most effective and …
Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
C Lu, ZY Wang, WL Qin, J Ma - Signal Processing, 2017 - Elsevier
Effective fault diagnosis has long been a research topic in the prognosis and health
management of rotary machinery engineered systems due to the benefits such as safety …
management of rotary machinery engineered systems due to the benefits such as safety …
A survey of data fusion in smart city applications
The advancement of various research sectors such as Internet of Things (IoT), Machine
Learning, Data Mining, Big Data, and Communication Technology has shed some light in …
Learning, Data Mining, Big Data, and Communication Technology has shed some light in …
Failure diagnosis using deep belief learning based health state classification
Effective health diagnosis provides multifarious benefits such as improved safety, improved
reliability and reduced costs for operation and maintenance of complex engineered systems …
reliability and reduced costs for operation and maintenance of complex engineered systems …
Cloud-enabled prognosis for manufacturing
Advanced manufacturing depends on the timely acquisition, distribution, and utilization of
information from machines and processes across spatial boundaries. These activities can …
information from machines and processes across spatial boundaries. These activities can …
A Review of the Digital Twin Technology in the AEC‐FM Industry
HH Hosamo, A Imran… - Advances in civil …, 2022 - Wiley Online Library
The Architecture, Engineering, Construction, and Facility Management (AEC‐FM) industry is
increasingly affected by digital technologies that monitor sensor network data and control …
increasingly affected by digital technologies that monitor sensor network data and control …