Machine Learning-Driven Classification of Polyethylene (HDPE, LDPE) via Raman Spectroscopy

Evangelos Stergiou, Fotios K. Konstantinidis, C. Stefani, G. Arvanitakis, Georgios Tsimiklis, Angelos Amditis

2025

Abstract

Polymer industries are currently focusing on developing new methods for identifying Polyethylene (PE) categories through rapid and non-destructive characterization techniques (NDT) to improve their production processes or recycling process control. However, NDT for classification is challenging for PE categories due to their identical chemical structures. This work presents a data-driven method for classifying PE to its two main categories, Low-Density Polyethylene (LDPE) and High-Density Polyethylene (HDPE). The method is using Raman spectroscopy, with the spectrums being processed to select the features, which are decisive for the classification of the different types of PE. PE samples in the form of granules are subjected to spectroscopic measurements, followed by data pre-processing in order for the signals to be enhanced. Using a Gradient Boosting model, the selected spectral features were used to train and validate the model. The model achieved an accuracy rate of 97 %, indicating the potential of the proposed method for rapid and accurate separation of LDPE and HDPE. This performance is not limited to PE granules but also to different plastic types (e.g. film, bottles, etc.). This approach offers a rapid method to classify polyethylene types, making the method suitable for industrial uses.

Paper Citation

in Harvard Style

Stergiou E., Konstantinidis F., Stefani C., Arvanitakis G., Tsimiklis G. and Amditis A. (2025). Machine Learning-Driven Classification of Polyethylene (HDPE, LDPE) via Raman Spectroscopy. In Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-730-6, SciTePress, pages 326-334. DOI: 10.5220/0013254000003905

in Bibtex Style

@conference{icpram25,
author={Evangelos Stergiou and Fotios Konstantinidis and C. Stefani and G. Arvanitakis and Georgios Tsimiklis and Angelos Amditis},
title={Machine Learning-Driven Classification of Polyethylene (HDPE, LDPE) via Raman Spectroscopy},
booktitle={Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2025},
pages={326-334},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013254000003905},
isbn={978-989-758-730-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Machine Learning-Driven Classification of Polyethylene (HDPE, LDPE) via Raman Spectroscopy
SN - 978-989-758-730-6
AU - Stergiou E.
AU - Konstantinidis F.
AU - Stefani C.
AU - Arvanitakis G.
AU - Tsimiklis G.
AU - Amditis A.
PY - 2025
SP - 326
EP - 334
DO - 10.5220/0013254000003905
PB - SciTePress