Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction
Author | : Lingelbach, Yannick |
Publisher | : KIT Scientific Publishing |
Total Pages | : 278 |
Release | : 2024-07-24 |
ISBN-10 | : 9783731513520 |
ISBN-13 | : 3731513528 |
Rating | : 4/5 (528 Downloads) |
Download or read book Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction written by Lingelbach, Yannick and published by KIT Scientific Publishing. This book was released on 2024-07-24 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as material, production line, and quality assessment for preprocessing, feature extraction, and drift corrections. Machine learning is employed to devise robust prediction strategies for hardness. Its implementation in an industry pilot demonstrates the economic benefits of the framework. - This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as material, production line, and quality assessment for preprocessing, feature extraction, and drift corrections. Machine learning is employed to devise robust prediction strategies for hardness. Its implementation in an industry pilot demonstrates the economic benefits of the framework.