Exploring the Impact of Dataset Accuracy on Machinery Functional Safety: Insights from an AI-Based Predictive Maintenance System

Padma Iyenghar, Padma Iyenghar

2024

Abstract

This paper focuses on the critical role of dataset accuracy in the context of machinery functional safety within an AI-based predictive maintenance system in a manufacturing setting. Through experiments introducing perturbations simulating real-world challenges, a decrease in performance metrics was observed—factors such as sensor noise, labeling errors, missing data, and outliers were identified as contributors to the compromise of the AI model’s accuracy. Implications for reliability and availability were discussed, emphasizing the need for high-quality datasets to minimize the risk of unplanned downtime. Recommendations include the implementation of robust data quality assurance processes and improved outlier detection mechanisms to ensure the reliability and availability of machinery in high-risk environments.

Paper Citation

in Harvard Style

Iyenghar P. (2024). Exploring the Impact of Dataset Accuracy on Machinery Functional Safety: Insights from an AI-Based Predictive Maintenance System. In Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE; ISBN 978-989-758-696-5, SciTePress, pages 484-497. DOI: 10.5220/0012683600003687

in Bibtex Style

@conference{enase24,
author={Padma Iyenghar},
title={Exploring the Impact of Dataset Accuracy on Machinery Functional Safety: Insights from an AI-Based Predictive Maintenance System},
booktitle={Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE},
year={2024},
pages={484-497},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012683600003687},
isbn={978-989-758-696-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE
TI - Exploring the Impact of Dataset Accuracy on Machinery Functional Safety: Insights from an AI-Based Predictive Maintenance System
SN - 978-989-758-696-5
AU - Iyenghar P.
PY - 2024
SP - 484
EP - 497
DO - 10.5220/0012683600003687
PB - SciTePress