Thursday, May 2025

05:00 PM - 08:00 PM

Room: 220A

Session: Artificial Intelligence Including Machine Learning for Imaging Posters

Control Chart Pattern Recognition Using Preprocessing Based on DTW and 1D-CNN for Anomaly Equipment Detection

Description:

This study proposes a Control Chart Pattern Recognition (CCPR) model integrating Dynamic Time Warping (DTW)-based preprocessing and a 1D-Convolutional Neural Network (1D-CNN). The model improves anomaly detection by identifying unique patterns among similar equipment, handling insufficient time-series data, and reducing unnecessary alerts. This SPC-AI approach enhances operational efficiency and reliability in complex production processes, particularly those with sequential characteristics, such as display manufacturing.