Towards a Safer and Sustainable Manufacturing Process: Material classification in Laser Cutting Using Deep Learning

TL;DR

This paper introduces a deep learning-based speckle pattern analysis method for real-time material classification in laser cutting, enhancing safety and sustainability by accurately identifying materials regardless of laser color changes.

Contribution

It presents a novel CNN-based approach for material classification using speckle patterns that remains accurate across different laser colors, improving upon previous methods.

Findings

Achieved 98.30% accuracy on training data

Attained 96.88% validation accuracy

F1-score of 0.9643 on new material set

Abstract

Laser cutting is a widely adopted technology in material processing across various industries, but it generates a significant amount of dust, smoke, and aerosols during operation, posing a risk to both the environment and workers' health. Speckle sensing has emerged as a promising method to monitor the cutting process and identify material types in real-time. This paper proposes a material classification technique using a speckle pattern of the material's surface based on deep learning to monitor and control the laser cutting process. The proposed method involves training a convolutional neural network (CNN) on a dataset of laser speckle patterns to recognize distinct material types for safe and efficient cutting. Previous methods for material classification using speckle sensing may face issues when the color of the laser used to produce the speckle pattern is changed. Experiments conducted in this study demonstrate that the proposed method achieves high accuracy in material classification, even when the laser color is changed. The model achieved an accuracy of 98.30 % on the training set and 96.88% on the validation set. Furthermore, the model was evaluated on a set of 3000 new images for 30 different materials, achieving an F1-score of 0.9643. The proposed method provides a robust and accurate solution for material-aware laser cutting using speckle sensing.