Title: Mass Benchmarking Using Statistical Methods Applied to Automotive Closures
text: Understanding the lightweighting potential of materials is important in making strategic decisions for material selection for a new vehicle program. Frequently benchmarking is done to support these decisions by selecting a reference vehicle which is believed to be mass efficient, then using the teardown mass data to set targets for the vehicle under design. In this work, rather then considering a single benchmark vehicle or a small set of vehicles, we looked at a large sample of vehicles over a range of sizes and segments (approximately 200 vehicles). Statistical methods were used to identify mass drivers for each subsystem. Mass drivers are the attributes of the vehicle and subsystem which determine subsystem mass. Understanding mass-drivers allows comparisons across vehicle size, segments, and materials. Next, we identified those vehicles which had subsystems which were much lighter than the average after adjusting for mass drivers. This set was defined as mass-efficient designs. We then focused on the lightweighting gained by material selection for these mass-efficient designs. This paper focuses on four body closures systems: side door, hood, decklid, and hatchback door. Results include the identification of mass drivers and predictive equations for closure structure mass for both average designs and mass efficient designs; The influence of material selection on mass for both average and mass-efficient designs; and observations on the diminished mass savings achieved at the system level when there is a mass savings due to material substitution at the structure level.