Driving Weight Management : A Framework for Optimized Weight Prediction in Automotive Engineering

Sammanfattning

Today, the automotive industry faces complexity in managing vehicle configuration processes as the need for product customization increases. This thesis investigates the current weight management system used at Volvo Cars, with a focus on improving the abstraction processes of vehicle weight during configuration. Current processes are dependent on manual effort, expert judgment and complex variant expressions in the product data system. These limitations result in inefficiencies and inaccuracies in the weight management processes. Through a case study approach, including qualitative interviews with internal stakeholders, key pain points within current practices were identified. Combined with a literature search on product configuration, weight and variant management, and configuration systems, a framework approach has been presented. The framework aims at increasing the accuracy and efficiency of the weight management system, while reducing the need for manual labor. This is done through a proposed algorithm logic for automating the assignment of part weight to variant layer partial configurations which utilize existing product structures. The result contributes to the automotive industry with a better understanding of the challenges in weight management when dealing with high customization. Further, the results suggest actionable improvements that can support Volvo Cars in achieving automation in vehicle configuration processes.