报告内容摘要

Although additive manufacturing (AM) or 3D printing holds great promise as a direct manufacturing technology, the dimensional geometric accuracy remains a critical issue, especially for freeform products with complex geometric shapes.  Efforts have long been attempted to improve the accuracy of AM built freeform products. But there is a lack of generic methodology transparent to specific AM processes.  This study fills the gap by establishing a general model predicting and compensating the in-plane (x-y plane) geometric deviation of AM built freeform products.  Built upon our previous predictive model and optimal compensation study for cylinder and polyhedron shapes, this work makes a breakthrough by directly predicting arbitrary freeform shape deviations from CAD design.

报告人简介

Qiang Huang received his Ph.D. degree in Industrial and Operations Engineering from the University of Michigan-Ann Arbor.  He is currently an Associate Professor and Gordon S. Marshall Early Career Chair in Engineering in the Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles. His research interests include Integrated Nanomanufacturing & Nanoinformatics, Scale-up Methodology, Predictive Modeling and Control for Additive Manufacturing, and Quality Control Paradigm for Additive Manufacturing. He received the prestigious US National Science Foundation CAREER award in 2011 and 2013 IEEE Transactions on Automation Science and Engineering Best Paper Award from IEEE Robotics and Automation Society. He has been an Associate Editor of the IEEE Transactions on Automation Science and Engineering since 2012 and has been a member of the scientific committee (Editorial Board) for the North American Manufacturing Research Institution (NAMRI) of SME, 2009–2011 and 2013-2015. He is a member of IEEE, INFORMS, IIE and ASME.

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