EAGER: Cybermanufacturing: Real-Time Scheduling in Networked 3D Printers

EAGER：网络制造：网络 3D 打印机中的实时调度

• 批准号: 1547127
• 负责人: Nikhil Chopra
• 金额: $ 29.24万
• 依托单位: University of Maryland, College Park
• 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: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1547127&HistoricalAwards=false
• 关键词: EAGER; Cybermanufacturing; Real; Time; Scheduling

It is widely believed that the arrival of 3D printers in the 21st century will pave the way for the Maker revolution. This EArly-concept Grant for Exploratory Research (EAGER) project is aimed at investigating fundamental theoretical and practical issues in the cloud-based utilization of an ensemble of heterogeneous networked 3D printers. The development of cloud-based scheduling algorithms is expected to be important for several cyber-manufacturing systems. Additionally, the theoretical and practical insights developed for the decentralized 3D printing-as-a-service paradigm may have a significant impact on the manufacturing ecosystem at large. Several students are expected to directly and indirectly benefit from the research and enhanced curriculum.This two-year research effort will focus on developing a fundamental understanding of optimal job assignment in networked 3D printers. Specific objectives of the work include data collection and analysis of heterogeneous 3D print jobs on an existing test bed at University of Maryland, design of optimal routing, batching, and scheduling algorithms to minimize job completion times by efficient decentralized resource utilization, and deployment of the algorithms on a virtual simulator and existing 3D printing infrastructure at University of Maryland.

人们普遍认为，21世纪3D打印机的到来将为创客革命铺平道路。这个探索性研究（EAGER）项目的早期概念资助旨在研究基于云的异构网络3D打印机集成利用的基本理论和实践问题。基于云的调度算法的发展预计对几个网络制造系统是重要的。此外，为分散式3D打印即服务范式开发的理论和实践见解可能会对整个制造业生态系统产生重大影响。预计一些学生将直接或间接地从研究和改进的课程中受益。这项为期两年的研究工作将侧重于对网络3D打印机中最佳工作分配的基本理解。工作的具体目标包括在马里兰大学现有的测试平台上收集和分析异构3D打印作业的数据，设计最佳路由，批处理和调度算法，通过有效的分散资源利用来最小化作业完成时间，并在马里兰大学的虚拟模拟器和现有的3D打印基础设施上部署算法。