I-Corps: Predictive Technology for Failure Prevention of Industrial Machinery

I-Corps：工业机械故障预防的预测技术

• 批准号: 1243425
• 负责人: Jay Lee
• 金额: $ 5万
• 依托单位: University of Cincinnati Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1243425&HistoricalAwards=false
• 关键词: Corps; Predictive; Technology; Failure; Prevention

The proposed study focuses on the commercialization of predictive technology for failure prevention of industrial machinery. The commercialization of this technology has the potential to represent a significant development that will be leveraging years of scientific and engineering research in the area of Prognostics and Health Management (PHM). The enhanced reconfigurable and modularized software platform is an important step for achieving the goal of rapid and low-cost solutions for predicting and preventing failures in industrial machinery. The scope of the proposed effort during the I-Corps study addresses a significant need expressed by industry for having a commercialized solution for predictive maintenance. The successful demonstration during previous projects showed the feasibility of the technology. However, in order to demonstrate the full economic benefits regarding cost, asset availability, and downtime reduction that industry desires, the technology must be cast in a form that can be more easily deployed and implemented. Successful implementation of this technology in manufacturing facilities has the potential to result in lower cost and higher quality products, thus providing a benefit to the end users of the manufactured goods. In addition, manufactures who implement this technology will likely have a competitive advantage in the market place due to the higher quality and productivity they could achieve by preventing costly equipment failures.

拟议的研究重点是工业机械故障预防预测技术的商业化。这项技术的商业化有可能代表一个重大的发展，将利用多年的科学和工程研究领域的预测和健康管理（PHM）。增强的可重构和模块化软件平台是实现快速和低成本解决方案预测和预防工业机械故障目标的重要一步。I-Corps研究期间提出的工作范围解决了行业对预测性维护商业化解决方案的重大需求。在以往项目中的成功示范表明了该技术的可行性。然而，为了展示行业所期望的成本、资产可用性和停机时间减少方面的全部经济效益，该技术必须以更容易部署和实施的形式进行铸造。 在制造设施中成功实施这一技术有可能降低成本和提高产品质量，从而为制成品的最终用户带来好处。此外，实施这项技术的制造商可能会在市场上具有竞争优势，因为他们可以通过防止昂贵的设备故障来实现更高的质量和生产力。