Efficient and Effective Dimension Control in Automotive Applications

摘要

In automotive industry, the production line for assembling mechanical parts of vehicles must place and weld hundreds of components on the right positions of the platform. The accuracy of deploying the components has great impact on the quality and performance of the produced vehicle. To ensure the assembly accuracy, a critical task in the production process is the so-called dimension quality control. The current state of practice in automotive industries is mainly based on a manual process where experienced engineers use production data to identify accuracy problems and suggest solutions for corrections on fixture adjustment in the assembly line. It is an extremely inefficient process, which typically takes the engineers around ten days for one batch of vehicles and a year to achieve the required assembly accuracy for final production. In this article, we present an automatic technique for dimension control. We formulate the dimension control problem as a constraint programming problem and present a refinement method to prune the exploration space. Our technique can not only identify the wrongly deployed parts leading to dimensional defects, but also provide high-quality fixture adjustment decisions. Experiments conducted on industrial production data from BMW Brilliance Automotive demonstrate the significantly improved efficiency and effectiveness of dimension control in automotive industries with our approach.