SBIR Phase I:Development of an AI PCB Prototyping Service called FlashPCB

The broader impact of this SBIR Phase I project is to create an artificial intelligence-powered printed circuit board assembly (PCBA) service that facilitates innovation and economic growth in the United States. Prototyping PCBAs is a key element in the innovation process for all electronics from consumer goods to medical devices, but current PCBA prototyping services are limited by manual steps and supply chain shortages. The artificial intelligence innovation of this project will save the customers time through strategic automation, shortening innovation timelines, and bringing new products to market faster. Currently, China and other Asian countries are still dominating the PCBA market share, serving many customers from the United States. There is an opportunity to provide high-quality, cost-competitive manufacturing in the United States to better serve the market and meet the rising demand for PCBAs. Additionally, investment in domestic manufacturing will strengthen electronic manufacturing capabilities, reduce dependence on foreign markets, and protect intellectual property.The technical innovation of this project is the development of two artificial intelligence algorithms that work together to determine the optimal selection of components to be mounted on a customer’s printed circuit board. The first algorithm reads the design file and identifies the properties of the components that the user has specified for their design. The second algorithm takes these properties as its input and selects in stock parts for the components in the design which will then be mounted onto the printed circuit board. This is a cost and time saving innovation that uses state of the art artificial intelligence algorithms and encodes electrical engineering principles. The key objectives for this project are to understand the types and combinations of components that our customers are likely to use in their designs, to define and test the algorithm for component property identification, and to define and test the algorithm which will choose the optimal components used for the manufacture of PCBAs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.