SUMMARY

With the recent development of artificial intelligence and autonomous techniques, how human should work with automation agents to achieve human goals with high performance has been a research question studied in multiple disciplines, and the focus is usually on the interaction between the two. Such collaboration can be a series of complex operations like manufacturing and autonomous driving, or a series of decision-making process like design and supply chain planning. This dissertation will study how collaborative intelligence can be achieved to enable human-automation symbiosis from system design and operations perspectives. Compared to conventional automation systems where human and automation agents work separately, the human-automation team will be modeled by introducing human factors in this symbiosis system. Therefore, this study can be decomposed into several research questions. Firstly, system design for human-automation symbiosis will be proposed, indicating components, mechanisms, and the structure. Then the function and role of automation agents for human are discussed, including different applications of automation techniques in real-world activities. With the understanding of automation agents, how collaborative intelligence can be modeled through team cognition and behavior theory is studied. From the operations perspective, implementation of human-automation mutual adaptation will be studied. The task allocation problem will then be modeled and solved. Finally, a case study of a manufacturing assembly line will be presented for validation.

Online Teams meeting:
https://teams.microsoft.com/l/meetup-join/19%3ameeting_MGU5MGE2YjAtN2U5ZC00YjI4LWIyZTMtMTk1Yzk4MmFkOWI4%40thread.v2/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%22b4a87408-067e-45a1-8cc8-967b876e9d54%22%7d