Lead Time Estimation of a Drilling Factory with Machine and Deep Learning Algorithms: A Case Study

Alessandro Rizzuto, David Govi, Federico Schipani, Alessandro Lazzeri

2021

Abstract

This project is presented as a real case-study based on machine learning and deep learning algorithms which are compared for a clearer understanding of which procedure is more suitable to industrial drilling.The predictions are obtained by using algorithms with a pre-processed dataset which was made available by the industry. The losses of each algorithm together with the SHAP values are reported, in order to understand which features most influenced the final prediction.

Paper Citation

in Harvard Style

Rizzuto A., Govi D., Schipani F. and Lazzeri A. (2021). Lead Time Estimation of a Drilling Factory with Machine and Deep Learning Algorithms: A Case Study. In Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics - Volume 1: IN4PL, ISBN 978-989-758-535-7, pages 84-92. DOI: 10.5220/0010655000003062

in Bibtex Style

@conference{in4pl21,
author={Alessandro Rizzuto and David Govi and Federico Schipani and Alessandro Lazzeri},
title={Lead Time Estimation of a Drilling Factory with Machine and Deep Learning Algorithms: A Case Study},
booktitle={Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics - Volume 1: IN4PL,},
year={2021},
pages={84-92},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010655000003062},
isbn={978-989-758-535-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Innovative Intelligent Industrial Production and Logistics - Volume 1: IN4PL,
TI - Lead Time Estimation of a Drilling Factory with Machine and Deep Learning Algorithms: A Case Study
SN - 978-989-758-535-7
AU - Rizzuto A.
AU - Govi D.
AU - Schipani F.
AU - Lazzeri A.
PY - 2021
SP - 84
EP - 92
DO - 10.5220/0010655000003062