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Cognitive Work in Future Manufacturing Systems: Human-centered AI for Joint Work with Models

Published

Author(s)

Peter O. Denno

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? In answering this question, this paper adapts Klein's flexecution for use in manufacturing. Theory-based 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. The article illustrates these ideas with an example of formulating models for production scheduling.
Citation
Journal of Integrated Design and Process Science
Issue
28

Keywords

manufacturing framework, process improvement, human-centered AI, problem formulation

Citation

Denno, P. (2024), Cognitive Work in Future Manufacturing Systems: Human-centered AI for Joint Work with Models, Journal of Integrated Design and Process Science, [online], https://doi.org/10.3233/JID-230035, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933309 (Accessed April 15, 2024)
Created February 23, 2024, Updated March 18, 2024