TY - GEN
T1 - A REAL-TIME ARTIFICIAL INTELLIGENCE PROCESS MANAGER FOR ENGINEERING DESIGN
AU - Gyory, Joshua T.
AU - Soria Zurita, Nicolás F.
AU - Martin, Jay
AU - Balon, Corey
AU - McComb, Christopher
AU - Kotovsky, Kenneth
AU - Cagan, Jonathan
N1 - Publisher Copyright:
Copyright © 2022 by ASME and The United States Government.
PY - 2022
Y1 - 2022
N2 - Managing the design process of teams has been shown to considerably improve problem-solving behaviors and resulting final outcomes. Automating this activity presents significant opportunities in delivering interventions that dynamically adapt to the state of a team to reap the most impact. In this work, an Artificial Intelligence (AI) agent is created to manage the design process of engineering teams in real time, tracking features of teams’actions and communications during a complex design and path-planning task with multidisciplinary team members. Teams are also placed under the guidance of human process managers for comparison. Regarding outcomes, teams perform equally as well under both types of management, with trends towards even superior performance from the AI-managed teams. The managers’ intervention strategies and team perceptions of those strategies are also explored, illuminating some intriguing similarities. Both the AI and human process managers focus largely on communication-based interventions, though differences start to emerge in the distribution of interventions across team roles. Furthermore, team members perceive the interventions from the both the AI and human manager as equally relevant and helpful and believe the AI agent to be just as sensitive to the needs of the team. Thus, the overall results show that the AI manager agent introduced in this work matches the capabilities of humans, showing potential in automating the management of a complex design process.
AB - Managing the design process of teams has been shown to considerably improve problem-solving behaviors and resulting final outcomes. Automating this activity presents significant opportunities in delivering interventions that dynamically adapt to the state of a team to reap the most impact. In this work, an Artificial Intelligence (AI) agent is created to manage the design process of engineering teams in real time, tracking features of teams’actions and communications during a complex design and path-planning task with multidisciplinary team members. Teams are also placed under the guidance of human process managers for comparison. Regarding outcomes, teams perform equally as well under both types of management, with trends towards even superior performance from the AI-managed teams. The managers’ intervention strategies and team perceptions of those strategies are also explored, illuminating some intriguing similarities. Both the AI and human process managers focus largely on communication-based interventions, though differences start to emerge in the distribution of interventions across team roles. Furthermore, team members perceive the interventions from the both the AI and human manager as equally relevant and helpful and believe the AI agent to be just as sensitive to the needs of the team. Thus, the overall results show that the AI manager agent introduced in this work matches the capabilities of humans, showing potential in automating the management of a complex design process.
UR - http://www.scopus.com/inward/record.url?scp=85142540875&partnerID=8YFLogxK
U2 - 10.1115/DETC2022-88609
DO - 10.1115/DETC2022-88609
M3 - Contribución a la conferencia
AN - SCOPUS:85142540875
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 48th Design Automation Conference (DAC)
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2022
Y2 - 14 August 2022 through 17 August 2022
ER -