Data Categories, Data Quality and Allocation Procedures 982162

This paper discusses in detail how data categories, data quality and allocation procedures were defined and implemented in the USAMP LCI analysis of a generic automobile. These data-related parameters are important for all LCI analyses but are especially important for the USAMP LCI analysis of a complete automobile. Whereas most LCI analyses have been conducted on relatively simple product systems consisting of a single material made with a single manufacturing process, the USAMP product system consists of a vast, interconnected array of dissimilar materials, products and manufacturing processes coupled with complex use, maintenance and disposition life cycle stages. As a result of this complexity, data is necessarily collected from an equally wide range of potentially incompatible sources.

To achieve a coherent end result, it is imperative to not only define these data-related parameters but also to define them in terms that are applicable throughout the complex life cycle of an automobile. The sections on data quality and allocation procedures are segmented into the principal components of the generic vehicle LCI model, which includes raw material acquisition (steel, aluminum, plastics), part manufacturing and vehicle assembly, use of the automobile and the final end-of-life disposition. The details in these sections illustrate the challenges encountered in applying consistent data quality requirements and allocation procedures to a complex product system.

This paper is one of six SAE publications discussing the results and execution of the USCAR AMP Generic Vehicle LCI. The papers in this series are (Overview of results 982160, 982161, 982162, 982168, 982169, 982170).