Footprint classification of electric components on printed circuit boards

Abstract

The market of Printed Circuit Boards (PCBs) is growing fast with the population of the Internet of Things. Therefore, PCB manufacturers require an effective design methodology to accelerate the PCB manufacturing processes. To design PCBs for new components, footprints which contain component information are needed to mount components on a PCB. However, current footprint design relies on experienced engineers and they may not maintain rule guidelines, which makes it a time-consuming work in the design flow. To achieve footprint design automation, analysis of footprint design rule is necessary and footprint classification can help sorting out design rules for different type of components. In this paper, we adopt both footprint and file name information to classify footprints. Through the proposed methodology, we can classify the footprint libraries with higher accuracy so as to achieve footprint design automation.