UNS: Advancing Environmental Sustainability through Innovative Design and Operation of Digital Manufacturing Equipment

UNS：通过数字制造设备的创新设计和运营促进环境可持续性

• 批准号: 1512217
• 负责人: John Sutherland
• 金额: $ 50万
• 依托单位: Purdue University
• 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: 2015-05-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1512217&HistoricalAwards=false
• 关键词: UNS; Advancing; Environmental; Sustainability; through

1512217 (Sutherland). The overarching objective of this research is to generate knowledge needed to establish a new framework for the design and operation of digital manufacturing equipment for increased resource/energy efficiency and enhanced environmental sustainability. Research will be conducted in the following four thrusts: 1) Machine-level energy flow characterization, analysis, and optimization; 2) Energy conscious production planning and control on a digitalized shop floor; 3). Retrofitting and remanufacturing of Computer Numerical Controlled (CNC) machines; and 4) Sustainable design of CNC machines. The research will be jointly pursued by a highly qualified team consisting of researchers from both China and the United States. Professor Sutherland from Purdue University, a pioneer in the area of sustainable manufacturing, will lead the U.S. part of the team. Professor Shao from Huazhong University of Science and Technology, a renowned expert in digital manufacturing, will lead the Chinese part of the team in partnership with Harbin Institute of Technology and Hefei University of Technology. The team members expertise complements perfectly with each other to pursue seamless integration of sustainable manufacturing and digital manufacturing. Working together it is expected that the knowledge and technologies generated in this project will be disseminated to industry in a very timely manner. The data/information enabled sustainable manufacturing approach to be developed will enhance productivity, efficiency, and sustainability, a key for both the China and U.S. machine tool industries and their respective manufacturing sectors. This research represents one of the first efforts to take advantage of the emerging digital manufacturing paradigm with the goal of advancing environmental sustainability. The project will enhance understanding of resource and energy flows over the entire life cycle of digital manufacturing equipment, from design, manufacture, operation, maintenance, to remanufacturing, which in turn offers insight into the design and operation of this equipment for improved environmental performance. In particular, characterizing and modeling energy flows at both the machine and shop floor levels make it possible to develop dynamic scheduling procedures for better energy and power efficiency when facing uncertainties and within smart grid scenarios. Data mining-enabled automated LCA could lead to a completely new and highly efficient approach for conducting LCA on complicated products. This project will significantly improve the resource and energy efficiency of digital manufacturing equipment over its entire life cycle. This, in turn, will lead to significant cost saving and carbon emission reduction. In addition, the research findings will be infused into multiple courses within the industrial, mechanical, and environmental and ecological engineering curricula at Purdue, as well as corresponding schools/departments in partnering Chinese universities. These activities will increase the amount of sustainability-related educational materials in these curricula. During this project, the PIs will continue their efforts to recruit students from under-represented groups into engineering. Students working on this project will be encouraged to share their experiences via social media to generate interests in conducting research among their peers. By communicating with their counterparts in the other country, students are also expected to gain exposure to a different culture. To reach an even broader audience, all the findings, case studies, and teaching materials will be made available on manufacturingHUB.org.This grant is co-funded by the Global Venture Fund (GVF) of NSF's International Science and Engineering section (ISE), the CMMI Manufacturing Machines and Equipment program, and the CBET/ENG Environmental Sustainability program.

1512217（萨瑟兰）。这项研究的总体目标是产生所需的知识，以建立一个新的框架，设计和操作数字化制造设备，提高资源/能源效率和增强环境的可持续性。研究将在以下四个方面进行：1）机器级能量流表征，分析和优化; 2）数字化车间的节能生产规划和控制; 3）。计算机数控（CNC）机床的改造和再制造;以及4）CNC机床的可持续设计。这项研究将由一个由中国和美国研究人员组成的高素质团队共同进行。来自普渡大学的萨瑟兰教授是可持续制造领域的先驱，他将领导该团队的美国部分。来自华中科技大学的邵教授是一位著名的数字化制造专家，他将与哈尔滨工业大学和合肥工业大学合作，领导中国团队。团队成员的专业知识相互补充，以实现可持续制造和数字化制造的无缝集成。通过共同努力，预计该项目中产生的知识和技术将非常及时地传播给行业。开发的数据/信息支持的可持续制造方法将提高生产力，效率和可持续性，这对中国和美国机床行业及其各自的制造业都至关重要。 这项研究代表了利用新兴数字制造模式的首批努力之一，其目标是促进环境可持续性。该项目将加强对数字化制造设备整个生命周期的资源和能源流动的理解，从设计，制造，运营，维护到再制造，这反过来又提供了对该设备设计和运营的深入了解，以改善环境绩效。特别是，在机器和车间层面对能量流进行表征和建模，使得在面临不确定性和智能电网场景时开发动态调度程序以提高能源和电力效率成为可能。支持数据挖掘的自动化LCA可以为复杂产品的LCA提供一种全新的高效方法。该项目将显著提高数字化制造设备在整个生命周期中的资源和能源效率。这反过来又将导致显著的成本节约和碳排放减少。此外，研究成果将被注入普渡大学的工业、机械、环境和生态工程课程以及中国合作大学的相应学院/系的多个课程中。这些活动将增加这些课程中与可持续性有关的教育材料的数量。在这个项目期间，PI将继续努力从代表性不足的群体中招收学生进入工程学。将鼓励从事该项目的学生通过社交媒体分享他们的经验，以产生在同龄人中进行研究的兴趣。通过与其他国家的同行交流，学生也有望接触到不同的文化。为了达到更广泛的受众，所有的研究结果，案例研究和教学材料将在manufacturingHUB.org上提供。这项资助由NSF国际科学与工程部（伊势）的全球风险基金（GVF），CMMI制造机器和设备计划以及CBET/ENG环境可持续性计划共同资助。