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Proceedings Papers

Does Design Proficiency Matter in Engineering Design Teams? A Computational Model and Experiments

Ethan Brownell, Jonathan Cagan, Kenneth Kotovsky

Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A041, August 14–17, 2022

Paper No: DETC2022-89318

DOI: https://doi.org/10.1115/DETC2022-89318

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Topics: Computer simulation, Design, Engineering design, Teams

Proceedings Papers

A Real-Time Artificial Intelligence Process Manager for Engineering Design

Joshua T. Gyory, Nicolás F. Soria Zurita, Jay D. Martin, Corey M. Balon, Christopher McComb, Kenneth Kotovsky, Jonathan Cagan

Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A018, August 14–17, 2022

Paper No: DETC2022-88609

DOI: https://doi.org/10.1115/DETC2022-88609

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Topics: Artificial intelligence, Engineering design, Teams, Design, Performance, Path planning

Proceedings Papers

Collaborative Design Decision-Making With Artificial Intelligence: Exploring the Evolution and Impact of Human Confidence in AI and in Themselves

Leah Chong, Ayush Raina, Kosa Goucher-Lambert, Kenneth Kotovsky, Jonathan Cagan

Proc. ASME. IDETC-CIE2022, Volume 6: 34th International Conference on Design Theory and Methodology (DTM), V006T06A021, August 14–17, 2022

Paper No: DETC2022-88574

DOI: https://doi.org/10.1115/DETC2022-88574

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Topics: Artificial intelligence, Collaboration, Decision making, Design

Journal Articles

The Evolution and Impact of Human Confidence in Artificial Intelligence and in Themselves on AI-Assisted Decision-Making in Design

Leah Chong, Ayush Raina, Kosa Goucher-Lambert, Kenneth Kotovsky, Jonathan Cagan

J. Mech. Des. March 2023, 145(3): 031401.

Paper No: MD-22-1057

DOI: https://doi.org/10.1115/1.4055123

Published Online: October 31, 2022

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Topics: Artificial intelligence, Decision making, Design, Feedback, Trusses (Building)

Journal Articles

Comparing the Impacts on Team Behaviors Between Artificial Intelligence and Human Process Management in Interdisciplinary Design Teams

Joshua T. Gyory, Kenneth Kotovsky, Christopher McComb, Jonathan Cagan

J. Mech. Des. October 2022, 144(10): 104501.

Paper No: MD-21-1606

DOI: https://doi.org/10.1115/1.4054723

Published Online: June 30, 2022

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Topics: Design, Teams, Artificial intelligence, Process management (Business automation)

Journal Articles

Human Versus Artificial Intelligence: A Data-Driven Approach to Real-Time Process Management During Complex Engineering Design

Joshua T. Gyory, Nicolás F. Soria Zurita, Jay Martin, Corey Balon, Christopher McComb, Kenneth Kotovsky, Jonathan Cagan

J. Mech. Des. February 2022, 144(2): 021405.

Paper No: MD-21-1267

DOI: https://doi.org/10.1115/1.4052488

Published Online: October 14, 2021

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Topics: Design, Teams, Artificial intelligence

Journal Articles

The Influence of Process Management: Uncovering the Impact of Real-Time Managerial Interventions via a Topic Modeling Approach

Joshua T. Gyory, Kenneth Kotovsky, Jonathan Cagan

J. Mech. Des. November 2021, 143(11): 111401.

Paper No: MD-20-1764

DOI: https://doi.org/10.1115/1.4050748

Published Online: May 21, 2021

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Topics: Design, Modeling, Process management (Business automation), Teams

Proceedings Papers

Agent-Based Synthesis of Electro-Mechanical Design Configurations

Matthew Campbell, Jonathan Cagan, Kenneth Kotovsky

Proc. ASME. DETC98, Volume 3: 10th International Conference on Design Theory and Methodology, V003T03A003, September 13–16, 1998

Paper No: DETC98/DTM-5673

DOI: https://doi.org/10.1115/DETC98/DTM-5673

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Topics: Design, Algorithms, Computer software, Engineering design

Journal Articles

Only as Strong as the Strongest Link: The Relative Contribution of Individual Team Member Proficiency in Configuration Design

Ethan Brownell, Jonathan Cagan, Kenneth Kotovsky

J. Mech. Des. August 2021, 143(8): 081402.

Paper No: MD-20-1706

DOI: https://doi.org/10.1115/1.4049338

Published Online: February 11, 2021

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Topics: Design, Teams, Topology

Proceedings Papers

Only As Strong As the Strongest Link: The Impact of Individual Team Member Proficiency in Configuration Design

Ethan Brownell, Jonathan Cagan, Kenneth Kotovsky

Proc. ASME. IDETC-CIE2020, Volume 8: 32nd International Conference on Design Theory and Methodology (DTM), V008T08A022, August 17–19, 2020

Paper No: DETC2020-22152

DOI: https://doi.org/10.1115/DETC2020-22152

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Topics: Design, Teams, Engineering design, Modeling

Proceedings Papers

A Topic Modeling Approach to Study the Impact of Manager Interventions on Design Team Cognition

Joshua T. Gyory, Kenneth Kotovsky, Jonathan Cagan

Proc. ASME. IDETC-CIE2020, Volume 8: 32nd International Conference on Design Theory and Methodology (DTM), V008T08A023, August 17–19, 2020

Paper No: DETC2020-22186

DOI: https://doi.org/10.1115/DETC2020-22186

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Topics: Design, Modeling, Teams, Experimental design, Process management (Business automation)

Journal Articles

Adaptive Inspirational Design Stimuli: Using Design Output to Computationally Search for Stimuli That Impact Concept Generation

Kosa Goucher-Lambert, Joshua T. Gyory, Kenneth Kotovsky, Jonathan Cagan

J. Mech. Des. September 2020, 142(9): 091401.

Paper No: MD-19-1478

DOI: https://doi.org/10.1115/1.4046077

Published Online: March 9, 2020

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Topics: Design, Innovation

Proceedings Papers

A Differential Game Approach to Dynamic Competitive Decisions Toward Human-Computer Collaboration

Alparslan Emrah Bayrak, Christopher McComb, Jonathan Cagan, Kenneth Kotovsky

Proc. ASME. IDETC-CIE2019, Volume 7: 31st International Conference on Design Theory and Methodology, V007T06A017, August 18–21, 2019

Paper No: DETC2019-97619

DOI: https://doi.org/10.1115/DETC2019-97619

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Topics: Collaboration, Computers

Proceedings Papers

Computationally Derived Adaptive Inspirational Stimuli for Real-Time Design Support During Concept Generation

Kosa Goucher-Lambert, Joshua T. Gyory, Kenneth Kotovsky, Jonathan Cagan

Proc. ASME. IDETC-CIE2019, Volume 7: 31st International Conference on Design Theory and Methodology, V007T06A009, August 18–21, 2019

Paper No: DETC2019-98188

DOI: https://doi.org/10.1115/DETC2019-98188

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Topics: Design, Databases, Performance, Dimensions, Patents

Proceedings Papers

Should Teams Collaborate During Conceptual Engineering Design? An Experimental Study

Joshua T. Gyory, Jonathan Cagan, Kenneth Kotovsky

Proc. ASME. IDETC-CIE2018, Volume 7: 30th International Conference on Design Theory and Methodology, V007T06A026, August 26–29, 2018

Paper No: DETC2018-85602

DOI: https://doi.org/10.1115/DETC2018-85602

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Topics: Engineering design, Teams, Conceptual design, Design, Engineering students, Performance, Undergraduate students

Proceedings Papers

Validating a Tool for Predicting Problem-Specific Optimized Team Characteristics

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky

Proc. ASME. IDETC-CIE2017, Volume 7: 29th International Conference on Design Theory and Methodology, V007T06A020, August 6–9, 2017

Paper No: DETC2017-67430

DOI: https://doi.org/10.1115/DETC2017-67430

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Topics: Teams, Design, Internet, Response surface methodology, Temperature

Journal Articles

Mining Process Heuristics From Designer Action Data via Hidden Markov Models

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky

J. Mech. Des. November 2017, 139(11): 111412.

Paper No: MD-17-1161

DOI: https://doi.org/10.1115/1.4037308

Published Online: October 2, 2017

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Topics: Cooling systems, Design, Topology, Trusses (Building), Emissions, Mining

Journal Articles

Capturing Human Sequence-Learning Abilities in Configuration Design Tasks Through Markov Chains

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky

J. Mech. Des. September 2017, 139(9): 091101.

Paper No: MD-16-1761

DOI: https://doi.org/10.1115/1.4037185

Published Online: July 12, 2017

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Topics: Design, Chain, Trusses (Building)

Journal Articles

Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky

J. Mech. Des. April 2017, 139(4): 041101.

Paper No: MD-16-1497

DOI: https://doi.org/10.1115/1.4035793

Published Online: February 6, 2017

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Topics: Design, Teams

Proceedings Papers

Linking Properties of Design Problems to Optimal Team Characteristics

Christopher McComb, Jonathan Cagan, Kenneth Kotovsky

Proc. ASME. IDETC-CIE2016, Volume 7: 28th International Conference on Design Theory and Methodology, V007T06A021, August 21–24, 2016

Paper No: DETC2016-59333

DOI: https://doi.org/10.1115/DETC2016-59333

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Topics: Design, Teams, Fluids, Regression analysis, Structural design

Journal citation

NARROW

Does Design Proficiency Matter in Engineering Design Teams? A Computational Model and Experiments

A Real-Time Artificial Intelligence Process Manager for Engineering Design

Collaborative Design Decision-Making With Artificial Intelligence: Exploring the Evolution and Impact of Human Confidence in AI and in Themselves

The Evolution and Impact of Human Confidence in Artificial Intelligence and in Themselves on AI-Assisted Decision-Making in Design

Comparing the Impacts on Team Behaviors Between Artificial Intelligence and Human Process Management in Interdisciplinary Design Teams

Human Versus Artificial Intelligence: A Data-Driven Approach to Real-Time Process Management During Complex Engineering Design

The Influence of Process Management: Uncovering the Impact of Real-Time Managerial Interventions via a Topic Modeling Approach

Agent-Based Synthesis of Electro-Mechanical Design Configurations

Only as Strong as the Strongest Link: The Relative Contribution of Individual Team Member Proficiency in Configuration Design

Only As Strong As the Strongest Link: The Impact of Individual Team Member Proficiency in Configuration Design

A Topic Modeling Approach to Study the Impact of Manager Interventions on Design Team Cognition

Adaptive Inspirational Design Stimuli: Using Design Output to Computationally Search for Stimuli That Impact Concept Generation

A Differential Game Approach to Dynamic Competitive Decisions Toward Human-Computer Collaboration

Computationally Derived Adaptive Inspirational Stimuli for Real-Time Design Support During Concept Generation

Should Teams Collaborate During Conceptual Engineering Design? An Experimental Study

Validating a Tool for Predicting Problem-Specific Optimized Team Characteristics

Mining Process Heuristics From Designer Action Data via Hidden Markov Models

Capturing Human Sequence-Learning Abilities in Configuration Design Tasks Through Markov Chains

Optimizing Design Teams Based on Problem Properties: Computational Team Simulations and an Applied Empirical Test

Linking Properties of Design Problems to Optimal Team Characteristics

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