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The interest in defining and implementing Digital Twins (DT) is at the forefront of today’s product organizations. The evolution of increasingly complex systems requires that their information be organized and managed via digital twins.  In addition, the development of Artificial Intelligence (AI) will result in an increasing degree of system complexity. These complex systems will exhibit true emergent behavior as AIs modify system aspects as the result of goal seeking and learning. DTs will need to increase in capability, becoming intelligent in their approach. This article presents a discussion on how these Intelligent Digital Twins (IDTs) will evolve and assist in developing and managing complex systems.

Abstract. This paper proposes that Systems Engineering and Product Lifecycle Management are closely related. In fact, the contention is that one of the threads that has led to the formation of Product Lifecycle Management is Systems Engineering. Product Lifecycle Management extends Systems Engineering and uses many of its methodologies and processes. However, this connection between these two areas has not gotten the proper attention from either industry or academia. Cross-pollinating Product Lifecycle Management and Systems Engineering would benefit both disciplines.. The paper is based on the author's observation and work at large organizations with significant Systems Engineering disciplines, such as NASA, the United States' Department of Defense, Boeing Corporation, Lockheed Martin, and others. The discrepancy between Systems Engineering claims of being involved in the entire product lifecycle versus the reality of Systems Engineering ending its involvement with the product at requirement verification informs the perspective of this paper.