Data Analysis of Production Data for Continuous Casting of Aluminum Rolling Ingots

Abstract

Optimizing the manufacturing process to increase the product quality is a major challenge most industry branches just like aluminum production have to face. To continuously improve the production quality, it is necessary to develop new methods to identify parameters which may influence the product quality. Influencing parameters can be found at various production steps. Production data is recorded by numerous sensors throughout the entire manufacturing process. The goal is to develop methods for analysing the sensor data from each step of the production process to effectively identify specific patterns that may indicate critical process parameters along the production chain. The work shows feature extraction methods to find characteristics in the sensor data that could affect the product-quality.