I-UCRC: The University of Texas at Austin Site of the I-UCRC on Intelligent Maintenance Systems

I-UCRC：德克萨斯大学奥斯汀分校 I-UCRC 智能维护系统网站

• 批准号: 1266279
• 负责人: Dragan Djurdjanovic
• 金额: $ 30万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1266279&HistoricalAwards=false
• 关键词: UCRC; University; Texas; Austin; Site

The University of Texas at Austin site for the I/UCRC for Intelligent Maintenance Systems (IMS) intends to pursue and understand methods addressing the scientific and practical challenges of condition-based and predictive maintenance of complex engineering systems. The site plans to expand the on-going IMS research with new ideas and foci including predictive maintenance in semiconductor manufacturing, vehicle technologies, oil industry, renewable energy, power plants and biomedicine. The University of Texas at Austin site intends to complement existing IMS efforts through focus on new approaches to diagnostics and prognostics in complex engineering systems, utilization of advanced diagnostics and predictive maintenance methods for monitoring of systems in a human body, and maintenance decision-making in distributed systems, with limited availability of distributed resources and uncertain supply and demand characteristics. It is estimated that the US economy spends more than $1 trillion for maintenance of critical assets, with more than 33% of these costs being wasted on ineffective maintenance. Optimization of these maintenance systems has the potential to greatly improve overall industrial productivity. The University of Texas at Austin Site of IMS intends to extend the research outcomes it brings to the center to new industries that have formerly not benefited from predictive maintenance research. The site plans to broadly disseminate research results through regular meetings with industrial partners, short courses on diagnostics and maintenance open to industry and academe, regular participation and publication in relevant conferences, and partnerships with universities in the US and abroad. They intend to actively promote diversity among students and researchers by leveraging the tremendous infrastructure UT offers in this regard.

德克萨斯大学奥斯汀分校 I/UCRC 智能维护系统 (IMS) 站点旨在探索和理解解决复杂工程系统基于状态和预测维护的科学和实际挑战的方法。 该网站计划通过新的想法和重点来扩展正在进行的 IMS 研究，包括半导体制造、车辆技术、石油工业、可再生能源、发电厂和生物医学领域的预测性维护。德克萨斯大学奥斯汀分校打算通过关注复杂工程系统中诊断和预测的新方法、利用先进的诊断和预测性维护方法来监测人体系统以及分布式系统中的维护决策（分布式资源可用性有限且供需特征不确定）来补充现有的 IMS 工作。 据估计，美国经济花费超过 1 万亿美元用于关键资产的维护，其中超过 33% 的成本浪费在无效的维护上。这些维护系统的优化有可能大大提高整体工业生产力。 德克萨斯大学奥斯汀分校 IMS 打算将其为该中心带来的研究成果扩展到以前未从预测性维护研究中受益的新行业。该网站计划通过与工业合作伙伴定期举行会议、向工业界和学术界开放的诊断和维护短期课程、定期参加相关会议并发表论文以及与美国和国外的大学建立合作伙伴关系来广泛传播研究成果。他们打算利用 UT 在这方面提供的庞大基础设施，积极促进学生和研究人员的多样性。