Achieving global climate targets necessitates the promotion of electromobility. Conversely, this has led to a concomitant increase in the number of battery systems. This increase prompts concerns regarding the sustainability and environmental impact of recycling processes. The disassembly of battery systems is an essential prerequisite for recycling or reuse. The ongoing deconstruction of battery systems underscores the necessity for a versatile system that can accommodate a wide array of battery model variants. Greater automation is imperative to enhance the cost-effectiveness and efficiency of disassembly. The implementation of lean management principles is imperative for the development of an enhanced disassembly system. This article demonstrates the integration of lean principles into the route optimization of an automated guided vehicle within a demonstrator system. The demonstrator system involves the automated disassembly of battery systems, from the pack to the module, supported by artificial intelligence, thereby facilitating enhanced structured disassembly. The primary focus of this study is to examine the implications of waste in relation to the existing route of the automated guided vehicle system. The experiments conducted provide a foundation for examining the route optimization of the entire concept and presenting the resulting reduction in waste of the automated guided vehicle system. Consequently, the optimized route of the demonstrator system tested in the experiments can be determined.