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

合作研究：高精度增材制造的几何形状误差控制

• 批准号: 1334178
• 负责人: Tirthankar Dasgupta
• 金额: $ 11.5万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1334178&HistoricalAwards=false
• 关键词: Collaborative; Research; Geometric; Shape; Error

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.

该奖项的目的是建立与广泛的增材制造（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主要障碍：当前增材制造工艺的尺寸精度不足。提出的研究策略是建立一个系统级、智能和高精度形状误差补偿和控制的方法框架。研究计划包括四个研究任务：(1)复杂形状的轮廓偏差建模与预测；(2)有效的实验设计与分析策略；(3)轮廓偏差的最优补偿与智能控制；(4)实验研究与验证。该项目的成功完成有望显著提高am制造产品的几何精度。该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地采用增材制造技术的重复工作，以及高精度和智能形状到形状补偿方法，以避免生产前的后处理和广泛的过程校准工作。包括专利在内的研究成果将促进增材制造技术更广泛、更快的应用，刺激制造业创新和创造就业机会。该研究项目将为增材制造技术和制造教育提供新的课程。为了协同合作，已经并将继续组织有教师和研究生参加的大学间讲习班和视频会议。