Journal
CIRP ANNALS-MANUFACTURING TECHNOLOGY
Volume 69, Issue 1, Pages 21-24Publisher
ELSEVIER
DOI: 10.1016/j.cirp.2020.04.090
Keywords
Machine learning; Energy efficiency; Battery production
Funding
- German BMWi [03ETE017A]
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Energy efficiency in manufacturing plays a crucial role in decreasing manufacturing costs and reducing environmental footprint. This is particularly important for producing battery cells with novel processes due to their cost-sensitivity and high potential impact on the environment. Therefore, design and operation of these processes are critical and require a high level of process and machine specific understanding. A methodology based on machine learning is presented, which has the capability of identifying improvement potentials using machine and process specific influencing factors. A battery production case is used to demonstrate the accuracy, transferability and validity of the methodology. (C) 2020 CIRP. Published by Elsevier Ltd. All rights reserved.
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