GOALI: Closed-Loop Control for Precision Extrusion of High-Viscosity Fluids in Robotic Manufacturing

这一学术与工业联系机会(GOALI)奖支持与流体沉积制造过程相关的新知识的研究。直接墨水书写(DIW)是一种三维(3D)打印形式，其中3D对象是通过以逐层方式沉积液体材料来构建的。这种制造工艺在组织工程、定制矫形器和假肢、用于微电子的机器人粘合剂输送、电动汽车制造和航空航天组装操作中具有潜在的应用。尽管最近在该领域取得了进展，但由于使用高粘度流体的固有困难，目前的DIW方法存在制造时间慢、部件缺陷和结构完整性问题。为了充分发挥DIW制造的潜力，这项研究将促进人们对DIW高粘度流体的准确和快速输送的理解和技术。该奖项还支持招募和支持机器人和添加剂制造社区中不同和代表性不足的群体的努力。通过工业和学术合作伙伴的合作，新的知识和研究成果将被纳入密歇根大学的制造和机器人课程，并将在工业界分享。该项目将建立在与课外和当地工程小组的合作基础上，进一步让学生接触制造和机器人集成的核心工具。流体沉积过程的预测和实时反馈控制对于提高DIW技术的速度、精度和可靠性至关重要。DIW制造领域的现有进展仅限于开环执行，并基于专家和特定于设备的流体特性、输送泵、管道、喷嘴和刀具路径的知识进行详尽的调整。在科学理解高粘度流体输送机制方面的这些限制导致沉积缺陷，如拐角鼓起、由于早/晚启动/晚停止而导致的不精确，以及由于下垂、串接和空洞形成而导致的结构问题。为了弥合DIW技术的这一差距，该项目将把计算流体动力学建模、模型预测控制和用于集成高粘度流体沉积的全局规划优化算法与喷嘴运动路径规划相结合。作为该项目的一部分，研究团队将开发1)适用于实时反馈控制的计算高效的高粘流建模，2)平台无关的高粘度流体沉积的闭环最优控制器，以及3)由流体动力学提供信息的共同优化的工具和沉积路径规划。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Grant Opportunity for Academic Liaison with Industry (GOALI) award supports research that contributes new knowledge related to a fluid deposition manufacturing process. Direct ink writing (DIW) is a form of three-dimensional (3D) printing in which a 3D object is built up by depositing liquid material in a layer-by-layer fashion. This manufacturing process has potential applications in tissue engineering, custom orthotics and prosthetics, robotic adhesive delivery for microelectronics, electric vehicle manufacturing, and aerospace assembly operations. Despite recent advances in the field, current DIW methods suffer from slow manufacturing times, part defects, and structural integrity issues due to the inherent difficulty of working with high-viscosity fluids. To realize the full potential of DIW manufacturing, this research will advance the understanding and technology to enable the precise and rapid delivery of high-viscosity fluids for DIW. This award also supports efforts to recruit and support diverse and underrepresented groups in the robotics and additive manufacturing communities. Through the collaboration of the industrial and academic partners, new knowledge and research outcomes will be incorporated into manufacturing and robotics courses at the University of Michigan and will be shared in the industrial community. The project will build on collaboration with extracurricular and local engineering groups to further expose students to the core tools of manufacturing and robotic integration.Predictive and real-time feedback control of the fluid deposition process is essential for advancing the speed, precision, and reliability of DIW technologies. Existing progress in the field of DIW manufacturing is limited to open-loop execution with exhaustive tuning based on expert and equipment-specific knowledge of the fluid properties, delivery pumps, pipes, nozzles, and toolpaths. These limitations in scientific understanding of high-viscosity fluid delivery mechanics lead to deposition defects such as corner bulging, imprecisions due to early/late start-stops, and structural issues due to drooping, stringing, and void formation. To bridge this gap in DIW technology, this project will integrate computational fluid dynamics modeling, model-predictive control, and global planning optimization algorithms for integrated high-viscosity fluid deposition with nozzle motion path planning. As part of this project, the research team will develop 1) computationally efficient high-viscous flow modeling that is amenable to real-time feedback control, 2) a platform-agnostic and closed-loop optimal controller for high-viscosity fluid deposition, and 3) co-optimized tool and deposition path planning that is informed by fluid dynamics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.