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Journal Articles

State of Health Estimation of Electric Vehicle Batteries Using Transformer-Based Neural Network

Yixin Zhao, Sara Behdad
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. October 2024, 146(10): 101703.
Paper No: JERT-24-1248
https://doi.org/10.1115/1.4065762
Published Online: July 18, 2024
View Article titled, State of Health Estimation of Electric Vehicle Batteries Using Transformer-Based Neural Network
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Topics: Batteries, Feature extraction, Artificial neural networks, Feature selection, Electric vehicle batteries, Temperature
Journal Articles

State-of-Health Estimation for Sustainable Electric Vehicle Batteries Using Temporal-Enhanced Self-Attention Graph Neural Networks

Yixin Zhao, Sara Behdad
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. June 2024, 146(6): 062102.
Paper No: JERT-23-1800
https://doi.org/10.1115/1.4065146
Published Online: April 3, 2024
View Article titled, State-of-Health Estimation for Sustainable Electric Vehicle Batteries Using Temporal-Enhanced Self-Attention Graph Neural Networks
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Topics: Artificial neural networks, Batteries, Construction, Sustainability
Journal Articles

Joint Special Issue: Advances in Design and Manufacturing for Sustainability

Mihaela Banu, Sara Behdad, Daniel Cooper, Karl Haapala, Chao Hu, Harrison Kim, Astrid Layton, Barbara S. Linke, Jie Zhang
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Guest Editorial
J. Mech. Des. February 2024, 146(2): 020301.
Paper No: MD-23-1879
https://doi.org/10.1115/1.4064362
Published Online: January 8, 2024
View Article titled, Joint Special Issue: Advances in Design and Manufacturing for Sustainability
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Topics: Design, Manufacturing, Sustainability
Journal Articles

Joint Special Section: Advances in Design and Manufacturing for Sustainability

Mihaela Banu, Sara Behdad, Daniel Cooper, Karl R. Haapala, Chao Hu, Harrison Kim, Astrid Layton, Barbara S. Linke, Jie Zhang
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Guest Editorial
J. Manuf. Sci. Eng. February 2024, 146(2): 020201.
Paper No: MANU-23-1762
https://doi.org/10.1115/1.4064363
Published Online: January 8, 2024
View Article titled, Joint Special Section: Advances in Design and Manufacturing for Sustainability
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Topics: Design, Manufacturing, Sustainability
Journal Articles

Early Prediction of Human Intention for Human–Robot Collaboration Using Transformer Network

Xinyao Zhang, Sibo Tian, Xiao Liang, Minghui Zheng, Sara Behdad
Journal: Journal of Computing and Information Science in Engineering
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. May 2024, 24(5): 051003.
Paper No: JCISE-23-1343
https://doi.org/10.1115/1.4064258
Published Online: January 8, 2024
View Article titled, Early Prediction of Human Intention for Human–Robot Collaboration Using Transformer Network
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Topics: Human-robot collaboration, Intent recognition, Manufacturing, Robots, Trajectories (Physics), Design
Journal Articles

A Review of Prospects and Opportunities in Disassembly With Human–Robot Collaboration

Meng-Lun Lee, Xiao Liang, Boyi Hu, Gulcan Onel, Sara Behdad, Minghui Zheng
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Review Articles
J. Manuf. Sci. Eng. February 2024, 146(2): 020902.
Paper No: MANU-23-1451
https://doi.org/10.1115/1.4063992
Published Online: December 4, 2023
View Article titled, A Review of Prospects and Opportunities in Disassembly With Human–Robot Collaboration
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Topics: Human-robot collaboration, Robotics, Robots, Safety, Path planning, Manufacturing, Economics
Proceedings Papers

State of Health Estimation of Electric Vehicle Batteries Using Transformer-Based Neural Network

Yixin Zhao, Sara Behdad
Proc. ASME. IDETC-CIE2023, Volume 5: 28th Design for Manufacturing and the Life Cycle Conference (DFMLC), V005T05A017, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-116426
https://doi.org/10.1115/DETC2023-116426
View Paper titled, State of Health Estimation of Electric Vehicle Batteries Using Transformer-Based Neural Network
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Topics: Artificial neural networks, Electric vehicle batteries, Electric vehicles, Lithium-ion batteries, Batteries, Fault diagnosis, NASA, Time series, Vehicles
Proceedings Papers

Early Prediction of Human Intention for Human-Robot Collaboration Using Transformer Network

Xinyao Zhang, Sibo Tian, Xiao Liang, Minghui Zheng, Sara Behdad
Proc. ASME. IDETC-CIE2023, Volume 2: 43rd Computers and Information in Engineering Conference (CIE), V002T02A035, August 20–23, 2023
Publisher: American Society of Mechanical Engineers
Paper No: DETC2023-116492
https://doi.org/10.1115/DETC2023-116492
View Paper titled, Early Prediction of Human Intention for Human-Robot Collaboration Using Transformer Network
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Topics: Human-robot collaboration, Manufacturing
Journal Articles

Automated Evaluation and Rating of Product Repairability Using Artificial Intelligence-Based Approaches

Hao-Yu Liao, Behzad Esmaeilian, Sara Behdad
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. February 2024, 146(2): 020901.
Paper No: MANU-23-1413
https://doi.org/10.1115/1.4063561
Published Online: November 1, 2023
View Article titled, Automated Evaluation and Rating of Product Repairability Using Artificial Intelligence-Based Approaches
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Topics: Design, Machine learning, Maintenance, Testing, X-rays, Sustainability, Ablation (Vaporization technology), Durability, Product design
Proceedings Papers

Forecasting the Range of Possible Human Hand Movement in Consumer Electronics Disassembly Using Machine Learning

Hao-Yu Liao, Yuhao Chen, Boyi Hu, Xiao Liang, Sara Behdad
Proc. ASME. MSEC2023, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T04A007, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-104792
https://doi.org/10.1115/MSEC2023-104792
View Paper titled, Forecasting the Range of Possible Human Hand Movement in Consumer Electronics Disassembly Using Machine Learning
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Topics: Artificial neural networks, Electronics, Machine learning, Safety, Collaboration, Computers, Errors, Hazardous substances, Human-robot collaboration, Measurement units and standards
Journal Articles

Automatic Screw Detection and Tool Recommendation System for Robotic Disassembly

Xinyao Zhang, Kareem Eltouny, Xiao Liang, Sara Behdad
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. March 2023, 145(3): 031008.
Paper No: MANU-22-1400
https://doi.org/10.1115/1.4056074
Published Online: December 2, 2022
View Article titled, Automatic Screw Detection and Tool Recommendation System for Robotic Disassembly
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Topics: Algorithms, Robotics, Screws, Electronics
Proceedings Papers

Human Hand Motion Prediction in Disassembly Operations

Hao-yu Liao, Minghui Zheng, Boyi Hu, Sara Behdad
Proc. ASME. IDETC-CIE2022, Volume 5: 27th Design for Manufacturing and the Life Cycle Conference (DFMLC), V005T05A021, August 14–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: DETC2022-89967
https://doi.org/10.1115/DETC2022-89967
View Paper titled, Human Hand Motion Prediction in Disassembly Operations
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Topics: Computers, Hazardous substances, Human-robot collaboration, Performance, Robotics, Robots, Safety, Trains
Journal Articles

Optimization-Based Disassembly Sequence Planning Under Uncertainty for Human–Robot Collaboration

Hao-yu Liao, Yuhao Chen, Boyi Hu, Sara Behdad
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. February 2023, 145(2): 022001.
Paper No: MD-22-1495
https://doi.org/10.1115/1.4055901
Published Online: November 1, 2022
View Article titled, Optimization-Based Disassembly Sequence Planning Under Uncertainty for Human–Robot Collaboration
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Topics: Human-robot collaboration, Optimization, Robots, Safety, Uncertainty, Sensitivity analysis, Computers
Proceedings Papers

Electric Vehicle Battery End-Of-Use Recovery Management: Degradation Prediction and Decision Making

Yixin Zhao, Sara Behdad
Proc. ASME. MSEC2022, Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing, V001T03A006, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-85536
https://doi.org/10.1115/MSEC2022-85536
View Paper titled, Electric Vehicle Battery End-Of-Use Recovery Management: Degradation Prediction and Decision Making
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Topics: Active materials, Batteries, Decision making, Economics , Electric vehicle batteries, Electric vehicles, Electrodes, Lithium-ion batteries, Maintenance, NASA
Proceedings Papers

Automatic Screw Detection and Tool Recommendation System for Robotic Disassembly

Xinyao Zhang, Kareem Eltouny, Xiao Liang, Sara Behdad
Proc. ASME. MSEC2022, Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing, V001T03A005, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-85403
https://doi.org/10.1115/MSEC2022-85403
View Paper titled, Automatic Screw Detection and Tool Recommendation System for Robotic Disassembly
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Topics: Robotics, Screws
Proceedings Papers

Optimization-Based Disassembly Sequence Planning Under Uncertainty for Human-Robot Collaboration

Hao-yu Liao, Yuhao Chen, Boyi Hu, Sara Behdad
Proc. ASME. MSEC2022, Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing, V001T03A004, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-85383
https://doi.org/10.1115/MSEC2022-85383
View Paper titled, Optimization-Based Disassembly Sequence Planning Under Uncertainty for Human-Robot Collaboration
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Topics: Human-robot collaboration, Optimization, Uncertainty
Journal Articles

A Graph Partitioning Technique to Optimize the Physical Integration of Functional Requirements for Axiomatic Design

Emilyn Green, Spenser Estrada, Praveen Kumare Gopalakrishnan, Sogol Jahanbekam, Sara Behdad
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. May 2022, 144(5): 051402.
Paper No: MD-21-1206
https://doi.org/10.1115/1.4052702
Published Online: December 6, 2021
View Article titled, A Graph Partitioning Technique to Optimize the Physical Integration of Functional Requirements for Axiomatic Design
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Topics: Algorithms, Design
Proceedings Papers

Deep Learning and Machine Learning Techniques to Classify Electrical and Electronic Equipment

Shuaizhou Hu, Xinyao Zhang, Hao-yu Liao, Xiao Liang, Minghui Zheng, Sara Behdad
Proc. ASME. IDETC-CIE2021, Volume 5: 26th Design for Manufacturing and the Life Cycle Conference (DFMLC), V005T05A029, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-71403
https://doi.org/10.1115/DETC2021-71403
View Paper titled, Deep Learning and Machine Learning Techniques to Classify Electrical and Electronic Equipment
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Topics: Electronic equipment, Laptop computers, Machine learning
Proceedings Papers

Machine Learning to Predict Medical Devices Repair and Maintenance Needs

Hao-yu Liao, Karthik Boregowda, Willie Cade, Sara Behdad
Proc. ASME. IDETC-CIE2021, Volume 5: 26th Design for Manufacturing and the Life Cycle Conference (DFMLC), V005T05A012, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-71333
https://doi.org/10.1115/DETC2021-71333
View Paper titled, Machine Learning to Predict Medical Devices Repair and Maintenance Needs
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Topics: Machine learning, Maintenance, Medical devices
Proceedings Papers

Electric Vehicle Battery Simulation: How Electrode Porosity and Thickness Impact Cost and Performance

Yixin Zhao, Sara Behdad
Proc. ASME. IDETC-CIE2021, Volume 5: 26th Design for Manufacturing and the Life Cycle Conference (DFMLC), V005T05A015, August 17–19, 2021
Publisher: American Society of Mechanical Engineers
Paper No: DETC2021-71511
https://doi.org/10.1115/DETC2021-71511
View Paper titled, Electric Vehicle Battery Simulation: How Electrode Porosity and Thickness Impact Cost and Performance
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Topics: Electric vehicle batteries, Electric vehicles, Electrodes, Lithium-ion batteries, Porosity, Simulation