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Search Publications by: Yan Lu (Fed)

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Displaying 26 - 50 of 71

Six-sigma Quality Management of Additive Manufacturing

November 26, 2020
Author(s)
Yan Lu, Hui Yang, Paul Witherell
Quality is a key determinant in deploying new processes, products or services, and influences the adoption of emerging manufacturing technologies. The advent of additive manufacturing (AM) as a manufacturing process has the potential to revolutionize a

Cognitive Automation and its Impact on Additive Manufacturing

October 15, 2020
Author(s)
Albert T. Jones, Zhuo Yang, Yan Lu
The English word manufacturing firstly appeared in 1683 and it was derived from Latin manu factus, meaning making by hand. For more than thousands of years now, and four Industrial Revolutions, the physical, and mostly mechanical processes, associated with

Standard Connections for IIoT Empowered Smart Manufacturing

September 12, 2020
Author(s)
Yan Lu, Paul W. Witherell, Albert W. Jones
The use of Industrial Internet-of-Things (IIoT) and related technology promises to transform manufacturing to the fourth Industry revolution era essentialized by "ubiquitous connectivity." IIoT allows new and unprecedented interactions amongst hardware

Nesting and Scheduling Problems for Additive Manufacturing: A Taxonomy and Review

August 21, 2020
Author(s)
Yosep Oh, Paul Witherell, Yan Lu, Timothy A. Sprock
With the trends of Industry 4.0 spanning physical and virtual worlds, Additive Manufacturing (AM) has been the mainstream for realizing complex geometries designed in computers. Meanwhile, a considerable number of AM studies have focused on effectively

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