A Real-Time Artificial Intelligence Process Manager for Engineering Design

J. Gyory, Nicolas F. Soria Zurita, Jay Martin, Corey Balon, Christopher McComb, K. Kotovsky, J. Cagan
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Abstract

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.
面向工程设计的实时人工智能过程管理器
管理团队的设计过程已被证明可以显著改善解决问题的行为和最终结果。自动化此活动为交付动态适应团队状态的干预提供了重要的机会,以获得最大的影响。在这项工作中,创建了一个人工智能(AI)代理来实时管理工程团队的设计过程,跟踪团队在与多学科团队成员进行复杂设计和路径规划任务期间的行动和通信特征。团队也被置于人工流程经理的指导下进行比较。就结果而言,团队在两种类型的管理下表现一样好,而且人工智能管理的团队甚至有更出色的表现。本文还探讨了管理者的干预策略和团队对这些策略的看法,揭示了一些有趣的相似之处。人工智能和人类流程管理人员都主要关注基于通信的干预,尽管在跨团队角色的干预分配中开始出现差异。此外,团队成员认为人工智能和人类经理的干预同样相关和有帮助,并相信人工智能代理对团队的需求同样敏感。因此,总体结果表明,在这项工作中引入的人工智能管理代理与人类的能力相匹配,显示出自动化管理复杂设计过程的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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