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Toward a Diagnostic and Prognostic Method for Knowledge-Driven Decision Making in Smart Manufacturing Technologies
Published
Author(s)
Thomas D. Hedberg Jr., Allison Barnard Feeney, Jaime A. Camelio
Abstract
Making high-quality manufacturing decisions in real-time is difficult. Smart manufacturing requires sufficient knowledge be available to the decision maker to ensure the manufacturing system runs efficiently and effectively. This paper will present a literature review of managing and controlling decision making and technological innovation. We present a process definition for decision making that implements closed-loop diagnostic and prognostic control. Lastly, we discuss a case-study relative to smart manufacturing.
Proceedings Title
15th Annual Conference On Systems Engineering Research (CSER)
Hedberg Jr., T.
, Barnard Feeney, A.
and Camelio, J.
(2017),
Toward a Diagnostic and Prognostic Method for Knowledge-Driven Decision Making in Smart Manufacturing Technologies, 15th Annual Conference On Systems Engineering Research (CSER), Redondo Beach, CA, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=922297
(Accessed October 14, 2025)