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Journal Articles

Special Issue: Symbiotic Human-AI Partnership for Next Generation Factories

Ehsan T Esfahani, Bin He, Chih-Hsing Chu, Ying Liu, Rahul Rai, Gaurav Ameta

J. Comput. Inf. Sci. Eng.

Paper No: JCISE-22-1165

DOI: https://doi.org/10.1115/1.4054673

Published Online: May 27, 2022

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Topics: Artificial intelligence, Collaboration, Design, Engineering systems and industry applications, Inspection, Machine learning, Manufacturing, User interfaces, Warehouses

Journal Articles

A Data-Driven Approach for Integrating Hedonic Quality and Pragmatic Quality in User Experience Modeling

Yanzhang Tong, Yan Liang, Irena Spasic, Yulia Hicks, Huicong Hu, Ying Liu

J. Comput. Inf. Sci. Eng. December 2022, 22(6): 061002.

Paper No: JCISE-21-1387

DOI: https://doi.org/10.1115/1.4054155

Published Online: May 10, 2022

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Topics: Modeling, Product design, Design

Journal Articles

Prediction of Remaining Useful Life Using Fused Deep Learning Models: A Case Study of Turbofan Engines

Yu Zheng, Xiangyu Bao, Fei Zhao, Chong Chen, Ying Liu, Bo Sun, Haotong Wang

J. Comput. Inf. Sci. Eng. October 2022, 22(5): 054501.

Paper No: JCISE-21-1296

DOI: https://doi.org/10.1115/1.4054090

Published Online: March 31, 2022

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Topics: Engines, Service life (Equipment), Turbofans, Feature extraction, Machine learning

Journal Articles

A Knowledge-Based Approach Toward Representation and Archiving of Aesthetic Information for Product Conceptual Design

Huicong Hu, Ying Liu, Wen Feng Lu, Xin Guo

J. Comput. Inf. Sci. Eng. August 2022, 22(4): 041011.

Paper No: JCISE-21-1401

DOI: https://doi.org/10.1115/1.4053674

Published Online: March 4, 2022

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Topics: Conceptual design, Design

Journal Articles

Prediction of Mechanical Properties of Three-Dimensional Printed Lattice Structures Through Machine Learning

Shuai Ma, Qian Tang, Ying Liu, Qixiang Feng

J. Comput. Inf. Sci. Eng. June 2022, 22(3): 031008.

Paper No: JCISE-21-1252

DOI: https://doi.org/10.1115/1.4053077

Published Online: December 16, 2021

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Topics: Elastic moduli, Errors, Machine learning, Mechanical properties, Three-dimensional models, Entropy, Yield strength, Design, Porosity

Proceedings Papers

Predicting Mechanical Properties of 3D Printed Lattice Structures

Shuai Ma, Qian Tang, Ying Liu, Qixiang Feng

Proc. ASME. IDETC-CIE2021, Volume 2: 41st Computers and Information in Engineering Conference (CIE), V002T02A053, August 17–19, 2021

Paper No: DETC2021-70249

DOI: https://doi.org/10.1115/DETC2021-70249

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Topics: Additive manufacturing, Machine learning, Mechanical properties

Proceedings Papers

Integrating Hedonic Quality for User Experience Modelling

Yanzhang Tong, Yan Liang, Ying Liu, Yulia Hicks, Irena Spasic

Proc. ASME. IDETC-CIE2021, Volume 2: 41st Computers and Information in Engineering Conference (CIE), V002T02A052, August 17–19, 2021

Paper No: DETC2021-69781

DOI: https://doi.org/10.1115/DETC2021-69781

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Topics: Design, Modeling, Product design, Data collection, Q-factor, Reflection

Proceedings Papers

Experimental Study of EPS Decomposition in Lost Foam Casting Process

Ying Liu, Sayavur I. Bakhtiyarov, Ruel A. Overfelt

Proc. ASME. IMECE2001, Rheology and Fluid Mechanics of Nonlinear Materials, 79-84, November 11–16, 2001

Paper No: IMECE2001/FED-24911

DOI: https://doi.org/10.1115/IMECE2001/FED-24911

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Topics: Casting, Differential scanning calorimetry, Heat, Heating, Pressure, Temperature

Proceedings Papers

Decomposed EPS Gases Pressure Measurements in Iron Lost Foam Casting Process

Ying Liu, Sayavur I. Bakhtiyarov, Ruel A. Overfelt

Proc. ASME. IMECE2001, Rheology and Fluid Mechanics of Nonlinear Materials, 71-78, November 11–16, 2001

Paper No: IMECE2001/FED-24910

DOI: https://doi.org/10.1115/IMECE2001/FED-24910

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Topics: Casting, Gases, Iron, Pressure measurement, Pressure, Temperature, Computer-aided engineering, Fluctuations (Physics), Freezing, Liquid metals

Proceedings Papers

S-CIMS: Towards Integrated and Environmentally Conscious Manufacturing Systems

Genbao Zhang, Ying Liu, Wei Tan, Zhongquan Huang

Proc. ASME. IDETC-CIE2001, Volume 1: 21st Computers and Information in Engineering Conference, 73-81, September 9–12, 2001

Paper No: DETC2001/CIE-21232

DOI: https://doi.org/10.1115/DETC2001/CIE-21232

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Topics: Computer-integrated manufacturing, Flow (Dynamics), Life cycle management, Manufacturing, Manufacturing systems, Sustainability, Sustainable development

Journal Articles

Effect of Cu on the Tribocorrosion Behavior of Antibacterial CoCrMo Alloys in Simulated Biological Environment

Xuefeng Song, Ying Liu, Xiaoyan Wang, Erlin Zhang

J. Tribol. July 2021, 143(7): 074501.

Paper No: TRIB-20-1172

DOI: https://doi.org/10.1115/1.4048726

Published Online: November 5, 2020

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Topics: Alloys, Corrosion, Wear, Copper

Includes: Supplementary data

Journal Articles

An Assessment of Quantitative Predictions of Deterministic Mixed Lubrication Solvers

Yuechang Wang, Abdel Dorgham, Ying Liu, Chun Wang, Mark C. T. Wilson, Anne Neville, Abdullah Azam

J. Tribol. January 2021, 143(1): 011601.

Paper No: TRIB-20-1109

DOI: https://doi.org/10.1115/1.4047586

Published Online: July 28, 2020

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Topics: Density, Film thickness, Lubrication, Pressure, Simulation, Surface roughness, Computation, Flow (Dynamics), Computer simulation

Includes: Supplementary data

Journal Articles

Special Issue: Machine Learning Applications in Manufacturing

Ying Liu, Rahul Rai, Anurag Purwar, Bin He, Mahesh Mani

J. Comput. Inf. Sci. Eng. April 2020, 20(2): 020301.

Paper No: JCISE-20-1041

DOI: https://doi.org/10.1115/1.4046427

Published Online: March 3, 2020

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Topics: Machine learning, Manufacturing, Artificial neural networks

Journal Articles

Data-Driven Concept Network for Inspiring Designers’ Idea Generation

Qiyu Liu, Kai Wang, Yan Li, Ying Liu

J. Comput. Inf. Sci. Eng. June 2020, 20(3): 031004.

Paper No: JCISE-19-1225

DOI: https://doi.org/10.1115/1.4046207

Published Online: February 19, 2020

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Topics: Design, Machine learning

Journal Articles

A Simulation Data-Driven Design Approach for Rapid Product Optimization

Yanli Shao, Huawei Zhu, Rui Wang, Ying Liu, Yusheng Liu

J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021008.

Paper No: JCISE-19-1176

DOI: https://doi.org/10.1115/1.4045527

Published Online: January 3, 2020

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Topics: Algorithms, Design, Optimization, Simulation, Data mining, Optimization algorithms, Weight (Mass)

Proceedings Papers

Bearing Capacities of Shallow Skirted Foundations After the Action of Multi-Directional Cyclic Displacements Considering Soil Degradation

Zhong Xiao, Donghai Zhang, Haixiao Liu, Ying Liu

Proc. ASME. OMAE2019, Volume 1: Offshore Technology; Offshore Geotechnics, V001T10A007, June 9–14, 2019

Paper No: OMAE2019-96036

DOI: https://doi.org/10.1115/OMAE2019-96036

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Topics: Bearings, Soil

Journal Articles

Special Issue: Machine Learning for Engineering Design

Jitesh H. Panchal, Mark Fuge, Ying Liu, Samy Missoum, Conrad Tucker

J. Mech. Des. November 2019, 141(11): 110301.

Paper No: MD-19-1579

DOI: https://doi.org/10.1115/1.4044690

Published Online: October 18, 2019

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Topics: Design, Engineering design, Machine learning, Optimization

Proceedings Papers

Voice of the Customer Oriented New Product Synthesis Over Knowledge Graphs

Feiwei Qin, Hairui Xu, Weicheng Zhang, Lin Yuan, Ming Li, Yusheng Liu, Ying Liu, Yong Chen

Proc. ASME. IDETC-CIE2018, Volume 1A: 38th Computers and Information in Engineering Conference, V01AT02A032, August 26–29, 2018

Paper No: DETC2018-85909

DOI: https://doi.org/10.1115/DETC2018-85909

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Topics: Design, Natural language processing, Product design, Sales

Proceedings Papers

Reliability Analysis Using Deep Learning

Chong Chen, Ying Liu, Xianfang Sun, Shixuan Wang, Carla Di Cairano-Gilfedder, Scott Titmus, Aris A. Syntetos

Proc. ASME. IDETC-CIE2018, Volume 1B: 38th Computers and Information in Engineering Conference, V01BT02A040, August 26–29, 2018

Paper No: DETC2018-86172

DOI: https://doi.org/10.1115/DETC2018-86172

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Topics: Event history analysis, Failure, Maintenance, Automobiles, Data mining, Design, Stress

Proceedings Papers

Integrating Intelligence and Knowledge of Human Factors to Facilitate Collaboration in Manufacturing

Harley Oliff, Ying Liu, Maneesh Kumar, Michael Williams

Proc. ASME. IDETC-CIE2018, Volume 1B: 38th Computers and Information in Engineering Conference, V01BT02A004, August 26–29, 2018

Paper No: DETC2018-85805

DOI: https://doi.org/10.1115/DETC2018-85805

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Topics: Collaboration, Human factors, Manufacturing, Robotics, Case studies, Control systems, Manufacturing systems, Uncertainty

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Journal citation

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Supplemental Material

Manuscript

Special Issue: Symbiotic Human-AI Partnership for Next Generation Factories

A Data-Driven Approach for Integrating Hedonic Quality and Pragmatic Quality in User Experience Modeling

Prediction of Remaining Useful Life Using Fused Deep Learning Models: A Case Study of Turbofan Engines

A Knowledge-Based Approach Toward Representation and Archiving of Aesthetic Information for Product Conceptual Design

Prediction of Mechanical Properties of Three-Dimensional Printed Lattice Structures Through Machine Learning

Predicting Mechanical Properties of 3D Printed Lattice Structures

Integrating Hedonic Quality for User Experience Modelling

Experimental Study of EPS Decomposition in Lost Foam Casting Process

Decomposed EPS Gases Pressure Measurements in Iron Lost Foam Casting Process

S-CIMS: Towards Integrated and Environmentally Conscious Manufacturing Systems

Effect of Cu on the Tribocorrosion Behavior of Antibacterial CoCrMo Alloys in Simulated Biological Environment

An Assessment of Quantitative Predictions of Deterministic Mixed Lubrication Solvers

Special Issue: Machine Learning Applications in Manufacturing

Data-Driven Concept Network for Inspiring Designers’ Idea Generation

A Simulation Data-Driven Design Approach for Rapid Product Optimization

Bearing Capacities of Shallow Skirted Foundations After the Action of Multi-Directional Cyclic Displacements Considering Soil Degradation

Special Issue: Machine Learning for Engineering Design

Voice of the Customer Oriented New Product Synthesis Over Knowledge Graphs

Reliability Analysis Using Deep Learning

Integrating Intelligence and Knowledge of Human Factors to Facilitate Collaboration in Manufacturing

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