Evaluation of Quality Methods on the Lithium Ion Battery Cells Ramp-Up

Abstract

Electromobility and lithium-ion batteries (LIB) in particular offer an opportunity to lower the environmental impact of vehicles, to reduce the number of vehicles with combustion engines over the next few years and to enable low-emissions or local emissions-free mobility. In order to successfully and efficiently produce LIB to meet this increased demand and the required high-quality standards, quality methods (QM) must be implemented in the manufacturing process. QM serve to ensure the conformity of processes and product, which can lead to benefits, such as reducing the scrap rate and the ramp-up time. Since the implementation of QM is usually very time- and cost-intensive, it is important for companies to know whether its use is worthwhile and, if so, which methods should be implemented. The increasing number of QM developed in the past few years makes this choice difficult. In this thesis, a methodology is presented to overcome this dilemma by reviewing existing approaches and assessing their gaps. The methodology systematically assists the user in selecting the most appropriate QM and enables a quantitative forecast of its benefits for the user’s specific application case. The tool is based on the cause-effect chain that is generated when a method is first implemented. By combining expert opinions about the existence and strength of these cause-effect correlations with the Shortest Path First algorithm and the Depth First Search algorithm, the methodology generates several possible results based on which algorithm is chosen. The methodology is validated by applying it to two different QM in the context of LIB production and comparing the results. This validation indicates that the methodology can determine which QM is more suitable for a given problem and which defined factors will be influenced more by the considered QM.