Collaborative Research: Geometric Shape Error Control for High-Precision Additive Manufacturing

该奖项的目标是建立与广泛的加法制造(AM)工艺相关的几何形状的误差预测和控制方法。最终目标是克服直接数字化制造的一个主要障碍：当前AM工艺的尺寸精度不足。提出的研究策略是建立一个系统级的、智能的、高精度的形状误差补偿与控制的方法框架。研究计划包括四个研究任务：(1)复杂形状轮廓偏差的建模和预测；(2)轮廓偏差建模的有效实验设计和分析策略；(3)轮廓偏差的优化补偿和智能形状控制；(4)实验研究和验证。该项目的成功完成预计将显著提高AM制造产品的几何精度。这项研究将产生关于系统级或通用几何形状精度控制方法的新知识，以减少更广泛和更快采用AM技术的重复工作，以及高精度和智能的形状对形状补偿方法，以避免生产前的后处理和广泛的工艺校准工作。包括专利在内的研究成果将促进AM技术的更广泛和更快的采用，刺激制造业创新和创造就业机会。该研究项目将提供AM技术和制造教育的新课程。已经并将继续举办有教职员工和研究生参加的大学间讲习班和视频会议，以便进行协同合作。

The objective of this award is to establish methodologies for error prediction and control of geometric shapes associated with a wide range of additive manufacturing (AM) processes. The ultimate goal is to overcome a major barrier of direct digital manufacturing: inadequate dimensional accuracy in current AM processes. The proposed research strategy is to establish a methodological framework for system-level, smart, and high precision shape error compensation and control. The research plan consists of four research tasks: (1) modeling and prediction of profile deviations for complex shapes; (2) efficient experimental designs and analysis strategies for modeling profile deviations; (3) optimal compensation and smart shape-to-shape control of profile deviations, and (4) experimental investigation and validation. Successful completion of the project is expected to significantly improve the geometric accuracy of AM-built products. The research will produce new knowledge regarding system-level or universal geometric shape accuracy control methodologies to reduce duplicated efforts for wider and quicker adoption of AM technologies, and high-precision and smart shape-to-shape compensation methodologies to avoid post-processing and extensive process calibration efforts prior to production. The research outcomes including patents will facilitate wider and quicker adoption of AM technology, spurring manufacturing innovations and job creation. The research project will provide new curriculum on AM technology and manufacturing education. Inter-university workshops and video conferences involving faculty and graduate students have been and will continue to be organized for synergistic collaborations.