CPS: Synergy: Cyber Enabled Manufacturing Systems (CeMs) for Small Lot Manufacture

该拨款为小批量制造的网络支持制造（CeMs）过程控制的开发提供资金，该过程控制将过程模型直接纳入控制算法。这样的模型可以用来适应物理产品和制造过程的变化，从而适应制造监测和控制算法，这样就可以很容易地适应变化的条件，而不需要大量的额外实验。该物理和网络制造过程控制系统的目标是合理设置制造公差，实时预测制造缺陷，实时控制过程以消除缺陷，以及对小批量制造进行实时监控。我们提出的实现这些目标的方法是高保真度，基于物理的模型，包括故障/缺陷模型，不确定性量化，实时运行的降阶模型，测量，实时预测，实时计算机体系结构，实时反解控制，以及通用制造过程的CeMs过程自动化。这项研究的结果将大大缩短生产新产品或改良产品的周期时间，提高制造过程的质量，同时减少浪费、能源使用和成本。这种精确控制算法的发展及其在制造过程中的应用可以为美国制造商提供竞争优势。也许更重要的是，参与这项研究的工程师的教育将为美国工业提供能够将这项技术应用于许多工业过程的员工。

This grant provides funding for the development of Cyber Enabled Manufacturing (CeMs) process control for small lot manufacturing that incorporates a model of the process directly into the control algorithm. Such a model can be used to accommodate changes in the physical product and the manufacturing process and thus the manufacturing monitoring and control algorithm, so that changing conditions are easily accommodated without extensive additional experiments. A set of objectives of this physics and cyber-enabled manufacturing process control system are rational setting of manufacturing tolerances, real time prediction of manufacturing defects, real time control of process to eliminate defects, and real time monitoring and control for small lot manufacturing. The methodologies we propose to achieve these goals are high fidelity, physics based models including models of faults/defects, uncertainty quantification, reduced order models that run in real time, measurement, real time prediction, real time computer architecture, real time control with inverse solutions, and automating the CeMs process for generic manufacturing processesIf successful, the results of this research will greatly reduce cycle time in producing new or modified products and improve the quality of manufacturing processes with accompanying reduction in waste, energy use, and cost. The development of such accurate control algorithms and their application to manufacturing processes can provide a competitive edge to US manufacturers. Perhaps more importantly, the education of engineers involved this research will supply US industry with employees who can apply this technology to many industrial processes.