SBIR Phase II: Analytical Modeling and Performance Prediction of Remanufactured Gearbox Components

本二期项目的创新点是开发基于物理的分析模型，通过预测(1)新部件性能和最佳再制造时间，(2)旧部件的再制造工艺资格，(3)预测再制造部件性能，来分析齿轮箱部件的安全性、寿命、可靠性和成本。当前的行业方法是基于传统方法来设计、制造、操作和退役资产，这些方法通常依赖于基于标准的估计、历史数据/领域经验、物理检查、测试、监控和检查。这个过程非常耗费时间和资源。此外，该过程通常没有考虑使用再制造过程来扩展/提高产品性能的机会。感知技术将解决这些问题并满足行业需求。第二阶段将扩展第一阶段的技术，在更全面的设计和分析框架中包括额外的变速箱材料，损坏模式和再制造过程，能够预测最佳的再制造时间和优化翻新操作，以延长组件的使用寿命。这种SBIR技术通过虚拟测试减少了物理测试，并将有助于高价值、高需求的旋翼飞机、汽车和风力涡轮机齿轮箱部件的再制造。因此，它减少了与制造相关的能源、材料资源和成本，并确保保持/改进产品性能。SBIR技术的广泛/商业影响是在航空航天、能源和运输行业的高美元资产中，这些行业依赖于高度设计（因此昂贵）的齿轮箱的可靠功能。我们新的基于先进制造伙伴关系的应用程序为美国制造业供应链提供了先行者和可持续的竞争优势，超过了6%的离岸劳动力优势。这一优势来自于高附加值资产的重用，优化了最长使用寿命，同时减少了与传统物理测试和分析方法相关的时间和成本。这是可能的，基于物理模型中包含的高级细节，（概念上）在微观结构水平上解码物质信息，就像人类基因组计划在DNA水平上解码遗传信息一样。我们的创新使客户能够快速，经济有效，准确地预测产品？S生命周期（设计、制造、运行、退化、维护、修理/再制造和退役）在材料、组件和装配/系统尺度上。我们预见到未来的机会，因为我们在NSF资助下开发的创新将使我们在提供软件和服务方面具有较低成本的竞争优势。我们部署这项技术的成本比该领域的传统公司低10倍。

The Innovation of this Phase II project is developing physics-based analytical models to analyze gearbox components for safety, longevity, reliability and cost by predicting (1) New component performance, and optimal time-to-remanufacture, (2) Qualification of used components for remanufacturing process, and (3) Predicting the remanufactured component performance. Current industry approach is to design, manufacture, operate, and retire assets based on traditional methods, which typically rely on standards-based estimates, historical data/domain experience, physical examination, testing, monitoring, and inspection. This process is extremely time and resource intensive. Further, this process often does not consider the opportunity to use remanufacturing processes to extend/enhance product performance. Sentient technology will address these issues and fulfill the industry requirements. Phase II will expand the Phase I technology to include additional gearbox materials, damage modes and remanufacturing processes in a more comprehensive design and analysis framework capable of predicting optimal time-to-remanufacture and optimizing refurbishing operations to extend the useful life of components. This SBIR technology reduces physical testing using virtual testing, and will assist in remanufacturing of high value, high demand rotorcraft, automotive and wind turbine gearbox components. Hence, it decreases the energy, material resources, and costs associated with manufacturing, and ensures that the product performance is maintained/improved.The broader/commercial impact of the SBIR technology is within aerospace, energy, and transportation industries on high dollar assets that rely on the reliable function of highly engineered (and thus expensive) gearboxes. Our new Advanced Manufacturing partnership based application provides the US manufacturing supply chain a first mover and a sustainable competitive advantage greater than the 6% offshore labor rate advantage. This advantage comes through reuse of high value-added assets optimized for maximum lifetime use, coupled with decreased time and costs associated with traditional physical testing and analysis methods. This is possible based on the high-level of detail included in physics-based models, which (conceptually) decode material information at the microstructure level just as the Human Genome Project decodes genetic information at the DNA level. Our innovation enables the customer to rapidly, cost effectively, and accurately predict a product?s lifecycle (design, manufacture, operation, degradation, maintenance, repair/remanufacture, and retirement) at the material, component, and assembly/system scales. We foresee a future opportunity due to the fact that our innovation developed under this NSF grant will give us a competitive advantage of lower costs to provide the software and service. Our cost to deploy the technology is 10X lower than traditional companies in this space.