loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Nadeem Iftikhar ; Yi-Chen Lin and Finn Ebertsen Nordbjerg

Affiliation: Department of Computer Science, University College of Northern Denmark, Aalborg 9200, Denmark

Keyword(s): Predictive Maintenance, Condition Based Maintenance, Machine Learning, Industry 4.0, Time Series.

Abstract: Predictive maintenance normally uses machine learning to learn from existing data to find patterns that can assist in predicting equipment failures in advance. Predictive maintenance maximizes equipment’s lifespan by monitoring its condition thus reducing unplanned downtime and repair cost while increasing efficiency and overall productive capacity. This paper first presents the machine learning based methods to predict unplanned failures before they occur. Afterwards, to confront the everlasting downtime problem, it discusses anomaly detection in greater detail. It also explains the selection criteria of these methods. In addition, the techniques presented in this paper have been tested by using well-known data-sets with promising results.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.226.222.12

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Iftikhar, N.; Lin, Y. and Nordbjerg, F. (2022). Machine Learning based Predictive Maintenance in Manufacturing Industry. In Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL; ISBN 978-989-758-612-5; ISSN 2184-9285, SciTePress, pages 85-93. DOI: 10.5220/0011537300003329

@conference{in4pl22,
author={Nadeem Iftikhar. and Yi{-}Chen Lin. and Finn Ebertsen Nordbjerg.},
title={Machine Learning based Predictive Maintenance in Manufacturing Industry},
booktitle={Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL},
year={2022},
pages={85-93},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011537300003329},
isbn={978-989-758-612-5},
issn={2184-9285},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL
TI - Machine Learning based Predictive Maintenance in Manufacturing Industry
SN - 978-989-758-612-5
IS - 2184-9285
AU - Iftikhar, N.
AU - Lin, Y.
AU - Nordbjerg, F.
PY - 2022
SP - 85
EP - 93
DO - 10.5220/0011537300003329
PB - SciTePress