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Search Publications by: Paul Witherell (Fed)

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Displaying 26 - 50 of 85

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

SCALABLE THERMAL SIMULATION OF POWDER BED FUSION

October 1, 2020
Author(s)
Paul Witherell, Vadim Shapiro, Yaqi Zhang
Powder bed fusion (PBF) has become a widely used additive manufacturing (AM) technology to produce metallic parts. As the PBF process is driven by a moving heat source, consistency in part production, particularly when varying geometries, has proven

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

A NEIGHBORHOOD-BASED NEURAL NETWORK FOR MELT POOL PREDICTION AND CONTROL

September 1, 2020
Author(s)
Paul Witherell, Vadim Shapiro, Yaqi Zhang
One of the most prevalent additive manufacturing processes, the powder bed fusion process, is driven by a moving heat source that melts metals to build a part. This moving heat source, and the subsequent formation and moving of a melt pool, plays an

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

A Decision Support Methodology for Integrated Machining Process and Operation Plans for Sustainability and Productivity Assessment

April 12, 2020
Author(s)
Qais Hatim, Christopher Saldana, Guodong Shao, Duckbong Kim, KC Morris, Paul Witherell, Sudarsan Rachuri, Soundar Kumara
In this paper, a systematic methodology is presented to enable environmental sustainability and productivity performance assessment for integrated process and operation plans at the machine cell level of a manufacturing system. This approach determines

Automatic Volumetric Segmentation of Additive Manufacturing Defects with 3D U-Net

March 23, 2020
Author(s)
Vivian W. Wong, Max Ferguson, Kincho Law, Yung-Tsun Lee, Paul Witherell
Segmentation of defects in additive manufacturing is challenging, due to the poor contrast, small sizes and variation in appearance of defects. Automatic segmentation can however provide quality control for additive manufacturing. Over recent years, 3D

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

A Review Of Machine Learning Applications In Additive Manufacturing

August 17, 2019
Author(s)
Saadia A. Razvi, Shaw C. Feng, Anantha Narayanan Narayanan, Yung-Tsun Lee, Paul Witherell
Variability in product quality continues to pose a major barrier to the widespread application of additive manufacturing (AM) processes in production environment. Towards addressing this barrier, the monitoring of AM processes and the measuring of AM

TOWARDS EFFICIENT THERMAL SIMULATION OF POWDER BED FUSION ON PATH LEVEL

August 15, 2019
Author(s)
Paul W. Witherell
As a widely used additive manufacturing (AM) technology to produce metallic parts, powder bed fusion (PBF) is driven by a moving heat source. Thermal simulation is a critical tool to understand the mappings between manufacturing parameters (e.g. laser

2018 National Institute of Standards and Technology Environmental Scan

March 26, 2019
Author(s)
Jason E. Boehm, Heather Evans, Ajitkumar Jillavenkatesa, Maria Nadal, Mark A. Przybocki, Paul Witherell, Rebecca A. Zangmeister
The 2018 National Institute of Standards and Technology Environmental Scan provide an analysis of the external factors that can influence NIST and the fulfillment of its mission as the agency looks to create a strategic plan for the coming years. The

A DESIGN FOR ADDITIVE MANUFACTURING ONTOLOGY TO SUPPORT MANUFACTURABILITY ANALYSIS

October 1, 2018
Author(s)
Samyeon Kim, David W. Rosen, Paul Witherell, Hyunwoong Ko
Design for additive manufacturing (DFAM) provides design freedom for creating complex geometries and guides designers to ensure manufacturability of parts fabricated using additive manufacturing (AM) processes. However, there is a lack of formalized DFAM

A DOMAIN DRIVEN APPROACH TO METAMODELING IN ADDITIVE MANUFACTURING

September 6, 2017
Author(s)
Peter O. Denno, Yan Lu, Paul Witherell, Sundar Krishnamurty, Ian Grosse, Douglas Eddy
Recent studies have shown advantages to utilizing metamodeling techniques to mimic, analyze, and optimize system input-output relationships in Additive Manufacturing (AM). This paper addresses a key challenge in applying such metamodeling methods, namely

A Collaborative Data Management System for Additive Manufacturing

August 9, 2017
Author(s)
Yan Lu, Paul W. Witherell, M A. Donmez
As additive manufacturing (AM) continues to mature as a production technology, the limiting factors that have hindered its adoption in the past still exist, for example, process repeatability and material availability issues. Overcoming many of these

INVESTIGATING GREY-BOX MODELING FOR PREDICTIVE ANALYTICS IN SMART MANUFACTURING

August 8, 2017
Author(s)
Peter O. Denno, Yan Lu, Paul Witherell, Sundar Krishnamurty, Ian Grosse, Douglas Eddy
This paper develops a grey-box modeling approach that combines manufacturing knowledge-based (white-box) models with statistical (black-box) metamodels to improve model reusability and predictability. A white-box model can utilize different types of