loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Nadeem Iftikhar and Adrian Mihai Dohot

Affiliation: Department of Computer Science, University College of Northern Denmark, Sofiendalsvej 60, Aalborg, Denmark

Keyword(s): Predictive Maintenance, Condition Monitoring, Smart Manufacturing, Sensor Data, Unlabeled Data, Unsupervised Machine Learning.

Abstract: An asset failure is costly for the manufacturing industry as it causes unplanned downtime. Unplanned downtime halts production lines, and can lead to productivity loss. One of the widely used methods to reduce downtime is to make use of condition based maintenance. The goal of condition based maintenance is to monitor as well as detect present and/or upcoming asset failures and thus reduce unplanned downtime. A newly emerged phenomena is to monitor the asset condition at real-time. Thus, this paper presents the techniques to process data-in-motion in order to monitor the health and condition of industrial assets in real-time. The techniques presented in this paper require no historical and/or labeled data and work well on streaming data.

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 3.143.255.57

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. and Dohot, A. M. (2022). Condition based Maintenance on Data Streams in Industry 4.0. 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 137-144. DOI: 10.5220/0011553500003329

@conference{in4pl22,
author={Nadeem Iftikhar and Adrian Mihai Dohot},
title={Condition based Maintenance on Data Streams in Industry 4.0},
booktitle={Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL},
year={2022},
pages={137-144},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011553500003329},
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 - Condition based Maintenance on Data Streams in Industry 4.0
SN - 978-989-758-612-5
IS - 2184-9285
AU - Iftikhar, N.
AU - Dohot, A.
PY - 2022
SP - 137
EP - 144
DO - 10.5220/0011553500003329
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic