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Authors: Efe Demir and Sencer Sultanoğlu

Affiliation: Eliar Electronics Corp., Istanbul, Turkey

Keyword(s): Predictive Maintenance, Flexible Impeller Pumps, Prophet Algorithm, Data-Driven Approach, Textile Industry, Fabric Dyeing Efficiency, Machine Learning.

Abstract: This article presents a data-driven approach aimed at improving the efficiency of fabric dyeing operations in the textile industry. It specifically focuses on the predictive maintenance of flexible impeller pumps (FIP) and the application of the Prophet algorithm. The study extensively explores the potential of machine learning and data analytics to increase operational efficiency and enable early failure detection. By using the Facebook Prophet model and time series data for early detection of wear and tear, it offers an approach to maintain pump efficiency without installing new hardware, relying solely on data.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Demir, E. and Sultanoğlu, S. (2024). A Data-Driven Approach for Predictive Maintenance of Impellers in Flexible Impeller Pumps Using Prophet. In Proceedings of the 13th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-707-8; ISSN 2184-285X, SciTePress, pages 245-252. DOI: 10.5220/0012710100003756

@conference{data24,
author={Efe Demir and Sencer Sultanoğlu},
title={A Data-Driven Approach for Predictive Maintenance of Impellers in Flexible Impeller Pumps Using Prophet},
booktitle={Proceedings of the 13th International Conference on Data Science, Technology and Applications - DATA},
year={2024},
pages={245-252},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012710100003756},
isbn={978-989-758-707-8},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Data Science, Technology and Applications - DATA
TI - A Data-Driven Approach for Predictive Maintenance of Impellers in Flexible Impeller Pumps Using Prophet
SN - 978-989-758-707-8
IS - 2184-285X
AU - Demir, E.
AU - Sultanoğlu, S.
PY - 2024
SP - 245
EP - 252
DO - 10.5220/0012710100003756
PB - SciTePress