SBIR Phase II: FlashPCB Service Commercialization and AI Component Package Identification

SBIR第二阶段：FlashPCB服务商业化和AI组件封装识别

• 批准号: 2335464
• 负责人: Thomas Castner
• 金额: $ 100万
• 依托单位: GRAVEL CAPITAL LLC
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2335464&HistoricalAwards=false
• 关键词: SBIR; Phase; II; FlashPCB; Service

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to create an artificial intelligence-powered printed circuit board assembly (PCBA) service that allows new products to get to market faster and that allows engineers to develop more sophisticated designs by decreasing the time to iterate on PCBs designs. 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, other 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.This Small Business Innovation Research (SBIR) Phase II project will create a service that provides customers with a rapid PCBA prototyping service. The project employs computer vision and artificial intelligence techniques to ensure the manufacturability of customers’ designs and find components to satisfy the customers’ designs while ensuring the designs can be manufactured in a blistering three days. The project will automate many of the manual steps associated with quoting and manufacturing a PCBA. One of the most time-consuming steps of quoting a PCBA is determining a set of components that will satisfy a customer’s design and which can be sourced within the manufacturing time frame. Building on the component selection algorithm developed in the SBIR Phase I project, which reads the property text from the customer’s designs to find components that satisfy the customer’s specifications, will build a system for matching components to a footprint (the copper landing pad on the board onto which a component is soldered). This will allow for rapid quoting, component substitution, and manufacturability checks, all of which will make PCBA prototyping fast and easy for the customer.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.

这个小企业创新研究 (SBIR) 第二阶段项目的更广泛/商业影响是创建人工智能驱动的印刷电路板组装 (PCBA) 服务，使新产品更快地进入市场，并允许工程师开发更复杂的产品PCBA 原型设计是从消费品到医疗设备的所有电子产品创新过程中的关键要素，但当前的 PCBA 原型设计服务受到手动步骤和供应链短缺的限制。该项目的智能创新将通过战略自动化来节省客户的时间，缩短创新时间，并更快地将新产品推向市场。目前，其他国家仍然主导着PCBA市场份额，为来自美国的许多客户提供了机会。在美国提供高质量、具有成本竞争力的制造，以更好地服务市场并满足不断增长的PCBA需求。此外，对国内制造的投资将增强电子制造能力，减少对国外市场的依赖，并保护知识产权。小型企业创新研究 (SBIR)二期项目将打造为客户提供快速PCBA原型制作服务，该项目采用计算机视觉和人工智能技术，确保客户设计的可制造性，并在确保设计可制造的同时找到满足客户设计的组件。该项目将在短短三天内自动完成与 PCBA 报价和制造相关的许多手动步骤。 PCBA 报价中最耗时的步骤之一是确定一组能够满足客户设计和制造的组件。建立在 SBIR 第一阶段项目中开发的组件选择算法的基础上，该算法从客户的设计中读取属性文本以找到满足客户规格的组件，将构建一个用于匹配组件的系统。封装（板上焊接元件的铜焊盘），这将允许快速报价、元件替换和可制造性检查，所有这些都将使客户能够快速轻松地进行 PCBA 原型设计。该奖项反映了这一点。通过使用基金会的智力价值和更广泛的影响审查标准进行评估，NSF 的法定使命被认为值得支持。