Development and Implementation of Statistical Methods for Quality Optimization in the Large‐Format Lithium‐Ion Cells Production. Issue 2 (9th May 2019)

• Record Type: Journal Article
• Authors: Meyer, Oliver; Weihs, Claus; Mähr, Stefan; Tran, Hai-Yen; Kirchhof, Michael; Schnackenberg, Sarah; Neuhaus-Stern, Jennifer; Rößler, Stefan; Braunwarth, Wolfgang
• Other Names: Kwade Arno guestEditor.
• Is Part Of: Energy technology. Volume 8:Issue 2(2020:Feb.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-05-09
• Subjects: design of experiments -- data‐driven process optimization -- PHEV-1 cells production -- quality assurance -- waste reduction; Energy development -- Periodicals; Power resources -- Periodicals; 333.79
• DOI: 10.1002/ente.201900244
• Languages: English
• ISSNs: 2194-4288

Abstract

Abstract : Herein, two techniques to optimize the production process of large‐format lithium‐ion cells for plug‐in hybrid electric vehicles using data‐driven methods are introduced and demonstrated. The first approach uses standard settings of the quality influencing factors to maximize the number of produced electrode sheets that meet predefined quality specifications. The second approach uses statistical methods to determine the levels of the quality influencing factors of a certain process that optimizes all quality parameters of the corresponding product jointly. Abstract : This work introduces two techniques to optimize the production process of large‐format lithium‐ion cells using data‐driven methods. The first uses standard settings of the quality influencing factors to optimize the number and quality of produced electrode sheets. The second method determines the levels of the quality influencing factors, which optimize all quality parameters of the corresponding product jointly.