Cognitive work in future manufacturing systems: Human-centered AI for joint work with models

Article type: Research Article

Authors: Denno, Peter^{; *}

Affiliations: National Institute of Standards and Technology, Gaithersburg, MD, USA

Correspondence: [*] Corresponding author: Peter Denno, National Institute of Standards and Technology, Gaithersburg, MD, USA. E-mail: [email protected].

Abstract:  Manufacturers perpetually adapt their systems to meet unforeseen events, new objectives, competition, and improved understanding of processes. In that human-directed work, models mediate an enduring relationship between production resources and engineers. Accommodating new understanding in the models controlling production can lead to more effective manufacturing. That work has previously been the province of quality programs such as Six Sigma, but is now fertile ground to study human-computer interaction about that enduring relationship mediated by models. Can AI augment human capability in the arcane work of formulating and refining models? This question is relevant to complex system engineering generally, not just manufacturing. In answering this question, this paper adapts Klein’s flexecution for use in adaptable manufacturing systems. Theory flexecution, the methodical refinement of models, points to human-computer interactions that emphasize the roles of models, explanation, and machine agents that recognize the engineer’s goals. This perspective article illustrates these ideas with an example of formulating models for production scheduling.

Keywords: Human/AI teaming, joint cognitive work, domain-specific languages, manufacturing, AI copilot

DOI: 10.3233/JID-230035

Journal: Journal of Integrated Design and Process Science, vol. 27, no. 2, pp. 71-82, 2024