Open AccessAn approach for the identification of production process variables in cross-process chain production processes like battery cell production
Author(s) -
Andreas Aichele,
K Schäffer,
Alexander Sauer
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1193/1/012110
Subject(s) - production (economics) , identification (biology) , process (computing) , battery (electricity) , computer science , biochemical engineering , process engineering , engineering , power (physics) , botany , physics , macroeconomics , quantum mechanics , economics , biology , operating system
Europe is currently not competitive in battery cell production. In order to increase competitiveness, battery cell production must be made more efficient. A major factor in improving efficiency is the reduction of waste. This requires understanding the many dependencies between the production process variables within battery cell manufacturing. For clarifying these dependencies, knowledge of the variables is essential. The challenge here is to completely determine them. For this purpose, different tools and methods are applied. But, in the case of cross-process chain production processes like battery cell production, they quickly reach their limits because these tools are not suitable for the structure and properties of the respective processes. The aim of the approach presented here is to support a complete identification of all process variables of battery cell production in the best possible way.