Year: 2019
Type: article
Abstract: The development of lithium-ion batteries (LIBs) is facing challenges due to the high level of uncertainty in cause-effect-relationships (CERs) in the manufacturing process. This process is characterized as an interlinked chain of input, intermediate and quality properties, which determine the quality of LIBs. In order to reduce the ramp-up time for LIB production plants, an understanding of influencing properties must be established. Existing methods to investigate these properties are usually expert-based or assess individual process steps. Thus, this paper presents a method, which utilizes multivariate process capability indices for the identification of CERs and quality assurance in the field of LIB production. This data-driven approach was applied to and evaluated on the production data of the prototype line for prismatic LIBs at the BMW Group in Munich.
Source: Procedia CIRP
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W2953481809