Monitoring and classification of dimensional faults for automotive body assembly

Abstract

Sudden process changes occurring during automobile body assembly processes will influence the downstream assembly process and the functionality and final appearance of the vehicle. Furthermore, these faults could result in a decreased production rate and an increase in the cost if sudden process changes are so serious that the production line has to be stopped for investigation. Thus, sudden process changes should be detected and eliminated as soon as possible to prevent defective products from being produced and to reduce the cost of repairs/reworks. A monitoring algorithm is developed to detect, classify, and group process changes by analyzing the dimensional data of car bodies. The results of this monitoring algorithm can help diagnose the root causes of variation according to the locations of measurement points, body structure, assembly sequence, and tooling layout. Measurement data obtained from an optical coordinate measuring machine (OCMM) are used to demonstrate the monitoring technique.