Sensor-based mostly Modeling and Optimization of Additive Manufacturing

Presenter: Dr. Hui Yang, Professor of Industrial and Manufacturing
Engineering, Bioengineering, The Penn State College

*Summary*: Additive manufacturing (AM) supplies a greater degree of
versatility to make a 3D section with advanced geometries straight from
the style. On the other hand, the prevalent application of AM is now
hampered by technological problems in process repeatability and top quality
management. To greatly enhance the in-course of action facts visibility, innovative
sensing is more and more invested for real-time AM system checking.
The proliferation of in-situ sensing data calls for the development of
analytical solutions for the extraction of functions sensitive to layerwise
flaws, and the exploitation of pertinent awareness about defects for
in-system excellent management of AM builds. As a end result, there are
increasing interests and quick improvement of sensor-centered versions for
the characterization and estimation of layerwise problems in the past several
a long time. Having said that, there is a dearth of concentrated implementation of
Six-Sigma high quality administration approaches for excellent handle of AM
builds. In this converse, we existing new knowledge-driven analytical procedures,
such as deep studying, machine learning, and community science, to
characterize and design the interrelationships involving engineering
style, equipment environment, procedure variability and final make high quality.
Further more, this talk will exhibit the methodologies of ontology
analytics, style of experiments (DOE) and simulation investigation for AM
system improvements. In closing, new system command strategies will be
talked about to optimize the motion designs, at the time an anomaly is detected,
with particular consideration of lead time and electrical power intake.

*Biography*: Dr. Hui Yang is a Professor of Industrial and Production
Engineering, Bioengineering at Penn Point out, and is affiliated with Penn
Condition Most cancers Institute (PSCI), Medical and Translational Science
Institute (CTSI), Institute for Computational and Facts Sciences (ICDS),
CIMP-3D. Now, he serves as the PI and web site director of NSF Center
for Wellness Corporation Transformation (CHOT). Dr. Yang was the
president (2017-2018) of IISE Data Analytics and Details Methods
Modern society, the president (2015-2016) of INFORMS High quality, Stats and
Trustworthiness (QSR) culture, and the software chair of 2016 IISE Annual
Meeting. He is also a division editor for IISE Transactions
Healthcare Units Engineering, an associate editor for IISE
Transactions, IEEE Journal of Biomedical and Wellness Informatics (JBHI),
IEEE Transactions on Automation Science and Engineering (TASE), IEEE
Robotics and Automation Letters (RA-L), High quality Technological innovation &
Quantitative Management, and an Associate Editor for Proceedings of IEEE
Case, IEEE EMBC, and IEEE BHI.

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