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Search Publications by: Paul Witherell (Fed)

Displaying 51 - 75 of 177

UNLEASHING THE POTENTIAL OF ADDITIVE MANUFACTURING: FAIR AM DATA MANAGEMENT PRINCIPLES

July 9, 2021

Author(s)

William Frazier, Yan Lu, Paul Witherell

The potential significance of FAIR data is hard to overstate, but equally hard to prove in totality. FAIR data can change the paradigm for research and development, qualification/certification, and acquisition, sustainment in AM. We can predict the

Ontology-driven Learning of Bayesian Network for Causal Inference and Quality Assurance in Additive Manufacturing

June 16, 2021

Author(s)

Ruimin Chen, Yan Lu, Paul Witherell, Timothy Simpson, Soundar Kumara, Hui Yang

Additive manufacturing (AM) enables the creation of complex geometries that are difficult to realize using conventional manufacturing techniques. Advanced sensing is increasingly being used to improve AM processes, and installing different sensors onto AM

Emerging Datasets and Analytics Opportunities in Metals Additive Manufacturing

April 30, 2021

Author(s)

Paul Witherell

Additive manufacturing (AM) technologies continue to mature, evolving into stalwarts of high- end production lines, particularly with metals AM. Technology maturation has been facilitated by efforts in materials characterization, process sensing, and part

Process Optimization under Uncertainty for Improving the Bond Quality of Polymer Filaments in Fused Filament Fabrication

February 1, 2021

Author(s)

Paul Witherell, Berkcan Kapusuzoglu, Matthew Sato, Sankaran Mahadevan

This paper develops a computational framework to optimize the process parameters such that the bond quality between extruded polymer filaments is maximized in fused filament fabrication (FFF). A one- dimensional heat transfer analysis providing an estimate

FUNCTIONAL REQUIREMENTS OF DATA ANALYTIC TOOLS AND SOFTWARE FOR METAL ADDITIVE MANUFACTURING

November 27, 2020

Author(s)

Shaw C. Feng, Paul Witherell, Moges Tesfaye

Additive manufacturing's (AM) transition to an accepted production technology has led to increasing demands on data requirements. Many of these advances have been made possible by an increase in in-situ sensing and ex-situ measurement devices. These new

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

Feature-level Data Fusion for Energy Consumption Analytics in Additive Manufacturing

September 1, 2020

Author(s)

Paul Witherell

The issue of Additive Manufacturing (AM) energy consumption attracts attention in both industry and academia, as the increasing trend of AM technologies being employed in the manufacturing industry. It is crucial to analyze, understand, and manage the

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

Hybrid Modeling Approach for Melt Pool Prediction in Laser Powder Bed Fusion Additive Manufacturing

August 16, 2020

Author(s)

Tesfaye M. Moges, Zhuo Yang, Kevontrez K. Jones, Shaw C. Feng, Paul W. Witherell, Yan Lu

Multi-scale multi-physics computational models are a promising tool to provide detailed insights to understand the process-structure-property-performance relationships in additive manufacturing (AM) processes. To take advantage of the strengths of both

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