EAGER: Cybermanufacturing: Software/Hardware Combined Acceleration for 3D Printing in Mass Customization

EAGER：网络制造：大规模定制中 3D 打印的软件/硬件组合加速

• 批准号: 1547167
• 负责人: Wenyao Xu
• 金额: $ 25万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1547167&HistoricalAwards=false
• 关键词: EAGER; Cybermanufacturing; Software; Hardware; Combined

Manufacturing and production have been big contributors to improved quality and sustainability of human life. Current market trends, such as consumer demand for variety, short product life cycles, high product quality and low cost, have resulted in the need for efficient, responsive, robust and sustainable manufacturing and production paradigm. 3D printing technologies hold the merit of affordability and customizability, while the key challenge in applying 3D printing for mass customization in real life is how to reduce the lead time per unit. The lead time of 3D printing a product unit comes from two sources, i.e., the pre-fabrication computation and manufacturing process. The pre-fabrication computation is increasingly significant and becomes the bottleneck in the manufacturing flow of mass customization in 3D Printing. This EArly-concept Grant for Exploratory Research (EAGER) project looks to address this problem through new computational methods with potential for two orders of magnitude reduction in time for pre-facbrication computation.This project aims to develop a transformative computational paradigm of 3D printing in mass customization. The project will pursue two novel and complementary objectives: 1) design a suite of quality-guaranteed geometric algorithms for the scalable and time-efficient pre-fabrication computation framework.; and 2) develop a low-complexity and efficient computing system to facilitate and accelerate the use of these methods and algorithms in Objective1. This new computer system focuses on domain-specific computing platforms as the next disruptive technology for power-performance-runtime efficiency improvement. Specifically, the team will develop accelerator-based architectures for computing primitives of geometric algorithms. This new hardware architecture will exploit the parallelism and customization to improve the efficiency of the new computational paradigm in 3D printing with less delay, lower complexity and higher computing power.

制造业和生产是改善人类生活质量和可持续性的重要贡献者。当前的市场趋势，例如消费者对多样性的需求，短产品生命周期，高产品质量和低成本的需求，导致需要高效，响应，健壮和可持续的制造和生产范式。 3D打印技术具有负担能力和可定制性的优点，而在现实生活中为大规模定制应用3D打印的主要挑战是如何减少每单位的提前时间。 3D打印产品单元的交货时间来自两个来源，即制动前计算和制造过程。预制前计算越来越重要，并成为3D打印中质量定制制造流中的瓶颈。 这项对探索性研究（急切）项目的早期概念赠款旨在通过新的计算方法来解决此问题，并有可能减少临时计算时间的时间数量级数量级。该项目旨在开发大规模定制中3D打印的变革性计算范式。该项目将追求两个新颖和互补的目标：1）设计一套质量保证的几何算法，用于可扩展且及时的预制计算框架。 2）开发低复杂性和有效的计算系统，以促进和加速目标1中这些方法和算法的使用。这个新的计算机系统将重点放在特定于域的计算平台上，这是用于提高功率绩效效率的下一个破坏性技术。 具体而言，该团队将开发基于加速器的架构，用于计算几何算法的原始词。这种新的硬件体系结构将利用并行性和自定义来提高3D打印中新计算范式的效率，延迟较小，复杂性和较高的计算能力。

项目成果

PrinTracker: Fingerprinting 3D Printers using Commodity Scanners

• DOI: 10.1145/3243734.3243735
• 发表时间: 2018-01-01
• 期刊: PROCEEDINGS OF THE 2018 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (CCS'18)
• 作者: Li, Zhengxiong;Rathore, Aditya Singh;Xu, Wenyao
• 通讯作者: Xu, Wenyao