Improving Battery Production Line using Simulink

Abstract: There is an increase in the demand in the Electric Vehicle segment owing to the focus on sustainability and reducing battery cost which also increases the demand for battery production globally. With this technology in its early stages being heavily challenged in terms of material supply, shorter time to market, and customer-specific variants it is essential to be able to have control and visibility on the production line to help facilitate critical decisions and improvements. This is approached through a structured simulation study that creates a digital twin of a battery production line. The production line is further optimized using a Genetic Algorithm (GA) to gain a better understanding. With the growing trends of Industry 4.0, it is essential to be able to use the right tools to facilitate the creation of a connected factory. Within the frame of the thesis work an investigation is performed with the use of Simulink and MATLAB as the software tools. The study emphasizes on the need for integration of simulation and optimization through its results. Three different scenarios were optimized where there is a potential increase of A% in the throughput with process and repair times as constraints. The model can be further investigated, and business-specific experiments can be simulated.