Machine learning in predictive maintenance towards sustainable smart manufacturing in industry 4.0
Recently, with the emergence of Industry 4.0 (I4. 0), smart systems, machine learning (ML)
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
A systematic literature review of machine learning methods applied to predictive maintenance
TP Carvalho, FA Soares, R Vita, RP Francisco… - Computers & Industrial …, 2019 - Elsevier
The amount of data extracted from production processes has increased exponentially due to
the proliferation of sensing technologies. When processed and analyzed, data can bring out …
the proliferation of sensing technologies. When processed and analyzed, data can bring out …
Adoption of machine learning technology for failure prediction in industrial maintenance: A systematic review
Failure prediction is the task of forecasting whether a material system of interest will fail at a
specific point of time in the future. This task attains significance for strategies of industrial …
specific point of time in the future. This task attains significance for strategies of industrial …
Risk-based and predictive maintenance planning of engineering infrastructure: existing quantitative techniques and future directions
Engineering infrastructure incorporate complex systems, hazardous materials and often
operated by human beings, making them prone to catastrophic accidents. Continuously …
operated by human beings, making them prone to catastrophic accidents. Continuously …
SOPHIA: An event-based IoT and machine learning architecture for predictive maintenance in industry 4.0
M Calabrese, M Cimmino, F Fiume, M Manfrin… - Information, 2020 - mdpi.com
Predictive Maintenance (PdM) is a prominent strategy comprising all the operational
techniques and actions required to ensure machine availability and to prevent a machine …
techniques and actions required to ensure machine availability and to prevent a machine …
Geothermal 4.0: AI-enabled geothermal reservoir development-current status, potentials, limitations, and ways forward
The development and operation of geothermal resources are known to be capital-intensive
due to their remote geographical location and extreme reservoir pressure & temperature …
due to their remote geographical location and extreme reservoir pressure & temperature …
Failure prediction using machine learning in a virtualised HPC system and application
Failure is an increasingly important issue in high performance computing and cloud
systems. As large-scale systems continue to grow in scale and complexity, mitigating the …
systems. As large-scale systems continue to grow in scale and complexity, mitigating the …
Optimizing predictive maintenance with machine learning for reliability improvement
Y Ren - ASCE-ASME Journal of Risk and …, 2021 - asmedigitalcollection.asme.org
Predictive maintenance, as a form of pro-active maintenance, has increasing usage and
shows significant superiority over the corrective and preventive maintenance. However …
shows significant superiority over the corrective and preventive maintenance. However …
A review on the advancements and challenges of artificial intelligence based models for predictive maintenance of water injection pumps in the oil and gas industry
This paper provides a comprehensive review on the Artificial Intelligence (AI) based models
for predictive maintenance (PdM) of water injection pumps (WIPs) in the oil and gas industry …
for predictive maintenance (PdM) of water injection pumps (WIPs) in the oil and gas industry …
Extracting failure time data from industrial maintenance records using text mining
Reliability modelling requires accurate failure time of an asset. In real industrial cases, such
data are often buried in different historical databases which were set up for purposes other …
data are often buried in different historical databases which were set up for purposes other …