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Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T01A001, June 10–14, 2019

Paper No: MSEC2019-2886

DOI: https://doi.org/10.1115/MSEC2019-2886

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Topics: Additive manufacturing, Ceramics

Proceedings Papers

A Decision-Level Data Fusion Approach to Surface Roughness Prediction

Yupeng Wei, Dazhong Wu, Janis Terpenny

Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T02A030, June 10–14, 2019

Paper No: MSEC2019-2976

DOI: https://doi.org/10.1115/MSEC2019-2976

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Topics: Additive manufacturing, Data fusion, Process monitoring, Surface roughness

Journal Articles

Prediction of Material Removal Rate for Chemical Mechanical Planarization Using Decision Tree-Based Ensemble Learning

Zhixiong Li, Dazhong Wu, Tianyu Yu

J. Manuf. Sci. Eng. March 2019, 141(3): 031003.

Paper No: MANU-18-1189

DOI: https://doi.org/10.1115/1.4042051

Published Online: January 17, 2019

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Topics: Algorithms, Modeling, Semiconductor wafers, Feature extraction, Physics

Journal Articles

Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning

Zhixiong Li, Kai Goebel, Dazhong Wu

J. Eng. Gas Turbines Power. April 2019, 141(4): 041008.

Paper No: GTP-18-1207

DOI: https://doi.org/10.1115/1.4041674

Published Online: November 16, 2018

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Topics: Aircraft engines, Algorithms, Feature selection, Modeling, Particle swarm optimization, Service life (Equipment), Optimization, Weight (Mass)

Proceedings Papers

Surface Roughness Prediction in Additive Manufacturing Using Machine Learning

Dazhong Wu, Yupeng Wei, Janis Terpenny

Proc. ASME. MSEC2018, Volume 3: Manufacturing Equipment and Systems, V003T02A018, June 18–22, 2018

Paper No: MSEC2018-6501

DOI: https://doi.org/10.1115/MSEC2018-6501

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Proceedings Papers

Predictive Modeling of Droplet Velocity and Size in Inkjet-Based Bioprinting

Dazhong Wu, Changxue Xu, Srikumar Krishnamoorthy

Proc. ASME. MSEC2018, Volume 3: Manufacturing Equipment and Systems, V003T02A028, June 18–22, 2018

Paper No: MSEC2018-6513

DOI: https://doi.org/10.1115/MSEC2018-6513

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Topics: Bioprinting, Drops, Modeling, Additive manufacturing, Biological tissues, Biomaterials, Biomedical engineering, Errors, Excitation, Experimental design

Journal Articles

Predictive Modeling of Droplet Formation Processes in Inkjet-Based Bioprinting

Dazhong Wu, Changxue Xu

J. Manuf. Sci. Eng. October 2018, 140(10): 101007.

Paper No: MANU-18-1269

DOI: https://doi.org/10.1115/1.4040619

Published Online: July 9, 2018

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Topics: Bioprinting, Drops, Modeling

Journal Articles

Cloud-Based Parallel Machine Learning for Tool Wear Prediction

Dazhong Wu, Connor Jennings, Janis Terpenny, Soundar Kumara, Robert X. Gao

J. Manuf. Sci. Eng. April 2018, 140(4): 041005.

Paper No: MANU-17-1344

DOI: https://doi.org/10.1115/1.4038002

Published Online: February 12, 2018

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Topics: Algorithms, Machine learning, Wear, Manufacturing, Milling, Cloud computing, Cutting, Sensors, Vibration

Proceedings Papers

Ensemble Prognostics With Degradation-Dependent Weights: Prediction of Remaining Useful Life for Aircraft Engines

Zhixiong Li, Dazhong Wu, Chao Hu, Janis Terpenny, Sheng Shen

Proc. ASME. IDETC-CIE2017, Volume 2A: 43rd Design Automation Conference, V02AT03A045, August 6–9, 2017

Paper No: DETC2017-68315

DOI: https://doi.org/10.1115/DETC2017-68315

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Topics: Aircraft engines, Algorithms, Engines, Service life (Equipment), Weight (Mass)

Proceedings Papers

Data-Driven Prognostics Using Random Forests: Prediction of Tool Wear

Dazhong Wu, Connor Jennings, Janis Terpenny, Robert Gao, Soundar Kumara

Proc. ASME. MSEC2017, Volume 3: Manufacturing Equipment and Systems, V003T04A048, June 4–8, 2017

Paper No: MSEC2017-2679

DOI: https://doi.org/10.1115/MSEC2017-2679

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Topics: Wear, Artificial neural networks, Manufacturing systems, Artificial intelligence, Algorithms, Failure, Machine learning, Machinery, Maintenance, Manufacturing

Journal Articles

A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

Dazhong Wu, Connor Jennings, Janis Terpenny, Robert X. Gao, Soundar Kumara

J. Manuf. Sci. Eng. July 2017, 139(7): 071018.

Paper No: MANU-16-1567

DOI: https://doi.org/10.1115/1.4036350

Published Online: April 18, 2017

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Topics: Algorithms, Artificial neural networks, Wear, Machine learning

Proceedings Papers

A Survey of Cloud-Based Design and Engineering Analysis Software Tools

Dazhong Wu, Janis Terpenny, Dirk Schaefer

Proc. ASME. IDETC-CIE2016, Volume 1A: 36th Computers and Information in Engineering Conference, V01AT02A016, August 21–24, 2016

Paper No: DETC2016-59341

DOI: https://doi.org/10.1115/DETC2016-59341

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Topics: Computer software, Design, Internet, Thread

Proceedings Papers

Forecasting Obsolescence Risk Using Machine Learning

Connor Jennings, Dazhong Wu, Janis Terpenny

Proc. ASME. MSEC2016, Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing, V002T04A033, June 27–July 1, 2016

Paper No: MSEC2016-8625

DOI: https://doi.org/10.1115/MSEC2016-8625

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Topics: Machine learning, Risk, Bills of materials, Design, Electronics, Innovation, Product design

Proceedings Papers

Fog-Enabled Architecture for Data-Driven Cyber-Manufacturing Systems

Dazhong Wu, Janis Terpenny, Li Zhang, Robert Gao, Thomas Kurfess

Proc. ASME. MSEC2016, Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing, V002T04A032, June 27–July 1, 2016

Paper No: MSEC2016-8559

DOI: https://doi.org/10.1115/MSEC2016-8559

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Topics: Manufacturing, Machinery, Internet of things, Maintenance, Cloud computing, Computer software, Cyber-physical systems, Data storage systems, Failure, Machine learning

Proceedings Papers

Performance Evaluation of Cloud-Based High Performance Computing for Finite Element Analysis

Dazhong Wu, Xi Liu, Steve Hebert, Wolfgang Gentzsch, Janis Terpenny

Proc. ASME. IDETC-CIE2015, Volume 1A: 35th Computers and Information in Engineering Conference, V01AT02A043, August 2–5, 2015

Paper No: DETC2015-46381

DOI: https://doi.org/10.1115/DETC2015-46381

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Topics: Finite element analysis, Performance evaluation, Cloud computing, Computer-aided engineering, Simulation, Bridges (Structures)

Journal Articles

Understanding Communication and Collaboration in Social Product Development Through Social Network Analysis

Dazhong Wu, David W. Rosen, Jitesh H. Panchal, Dirk Schaefer

J. Comput. Inf. Sci. Eng. March 2016, 16(1): 011001.

Paper No: JCISE-14-1066

DOI: https://doi.org/10.1115/1.4031890

Published Online: December 10, 2015

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Topics: Collaboration, Design, Engineering design, Teams, Engineers, Product development

Journal citation

NARROW

Constructing Robust and Reliable Health Indices and Improving the Accuracy of Remaining Useful Life Prediction

Remaining Useful Life Prediction of Bearings Using Ensemble Learning: The Impact of Diversity in Base Learners and Features

Predicting Flexural Strength of Additively Manufactured Continuous Carbon Fiber-Reinforced Polymer Composites Using Machine Learning

Data-Driven Predictive Modeling of Tensile Behavior of Parts Fabricated by Cooperative 3D Printing

A Review on Additive Manufacturing of Ceramics

A Decision-Level Data Fusion Approach to Surface Roughness Prediction

Prediction of Material Removal Rate for Chemical Mechanical Planarization Using Decision Tree-Based Ensemble Learning

Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning

Surface Roughness Prediction in Additive Manufacturing Using Machine Learning

Predictive Modeling of Droplet Velocity and Size in Inkjet-Based Bioprinting

Predictive Modeling of Droplet Formation Processes in Inkjet-Based Bioprinting

Cloud-Based Parallel Machine Learning for Tool Wear Prediction

Ensemble Prognostics With Degradation-Dependent Weights: Prediction of Remaining Useful Life for Aircraft Engines

Data-Driven Prognostics Using Random Forests: Prediction of Tool Wear

A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

A Survey of Cloud-Based Design and Engineering Analysis Software Tools

Forecasting Obsolescence Risk Using Machine Learning

Fog-Enabled Architecture for Data-Driven Cyber-Manufacturing Systems

Performance Evaluation of Cloud-Based High Performance Computing for Finite Element Analysis

Understanding Communication and Collaboration in Social Product Development Through Social Network Analysis

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