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Search Publications by: Yan Lu (Fed)

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Displaying 76 - 100 of 138

Data-driven characterization of computational models for powder-bed-fusion additive manufacturing

July 31, 2020
Author(s)
Yan Lu, Zhuo Yang, Paul W. Witherell, Wentao Yan, Kevontrez Jones, Gregory Wagner, Wing-Kam Liu, Jason C. Fox
Computational modeling for additive manufacturing has proven to be a powerful tool to understand the physical mechanisms, predict fabrication quality, and guide design and optimization. Varieties of models have been developed with different assumptions and

FROM SCAN STRATEGY TO MELT POOL PREDICTION: A NEIGHBORING-EFFECT MODELING METHOD

April 23, 2020
Author(s)
Zhuo Yang, Yan Lu, Ho Yeung, Sundar Krishnamurty
The quality of AM built parts is highly correlated to the melt pool characteristics. Hence melt pool monitoring and control can potentially improve AM part quality. This paper presents a neighboring-effect modeling method (NBEM) that uses scan strategy to

DATA REGISTRATION FOR IN-SITU MONITORING OF LASER POWDER BED FUSION PROCESSES

November 11, 2019
Author(s)
Shaw C. Feng, Yan Lu, Albert W. Jones
Increasingly, a wide range of in-situ sensors are being instrumented on additive manufacturing (AM) machines. Researchers and manufacturers use these sensors to collect a variety of data to monitor process performance and part quality. The amount and speed

Machine Learning based Continuous Knowledge Engineering for Additive Manufacturing

September 19, 2019
Author(s)
Hyunwoong Ko, Yan Lu, Paul W. Witherell, Ndeye Y. Ndiaye
Additive manufacturing (AM) assisted by a digital twin is expected to revolutionize the realization of high-value and high-complexity functional parts on a global scale. With machine learning (ML) introduced in the AM digital twin, AM data are transformed

Foundations of information governance for smart manufacturing

June 11, 2019
Author(s)
KC Morris, Yan Lu, Simon P. Frechette
The manufacturing systems of the future will be even more heavily dependent on the data than they are today. More and more data and information are being collected and communicated throughout product development lifecycles and across manufacturing value

2018 NIST/OAGi Workshop: Enabling Composable Service-Oriented Manufacturing Systems

April 22, 2019
Author(s)
Nenad Ivezic, Boonserm Kulvatunyou, Michael P. Brundage, Yan Lu, Evan K. Wallace, Albert W. Jones
This report summarizes the results from the 2018 NIST/OAGi Workshop: Enabling Composable Service-Oriented Manufacturing Systems, which was held at the National Institute of Standards and Technology campus in Gaithersburg, MD, on April 23-24, 2018. This was

SELF-IMPROVING ADDITIVE MANUFACTURING KNOWLEDGE MANAGEMENT

August 26, 2018
Author(s)
Yan Lu, Zhuo Yang, Douglas Eddy, Sundar Krishnamurty
The current AM development environment is far from being mature. Both software applications and workflow management tools are very limited due to the lack of knowledge to support engineering decision makings. AM knowledge includes design rules, operation

A SUPER-METAMODELLING FRAMEWORK TO OPTIMIZE SYSTEM PREDICTABILITY

August 25, 2018
Author(s)
Yan Lu, Douglas Eddy, Sundar Krishnamurty, Ian Grosse
Statistical metamodels can robustly predict manufacturing process and engineering systems design results. Various techniques, such as Kriging, polynomial regression, artificial neural network and others, are each best suited for different scenarios that