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Decision-Making Under Uncertainty for a Digital Thread-Enabled Design Process

Journal Article · · Journal of Mechanical Design
DOI:https://doi.org/10.1115/1.4050108· OSTI ID:1851173
 [1];  [2]
  1. Massachusetts Institute of Technology, 77 Massachusetts Avenue 37-312, Cambridge, MA 02138; OSTI
  2. Professor of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, 201 E 24th Street, POB 4.102, Austin, TX 78712
Abstract

Digital thread is a data-driven architecture that links together information from all stages of the product lifecycle. Despite increasing application in manufacturing, maintenance/operations, and design related tasks, a principled formulation of analyzing the decision-making problem under uncertainty for the digital thread remains absent. The contribution of this article is to present a formulation using Bayesian statistics and decision theory. First, we address how uncertainty propagates in the product lifecycle and how the digital thread evolves based on the decisions we make and the data we collect. By using these mechanics, we explore designing over multiple product generations or iterations and provide an algorithm to solve the underlying multistage decision problem. We illustrate our method on an example structural design problem where our method can quantify and optimize different types and sequences of decisions, ranging from experimentation, manufacturing, and sensor placement/selection, to minimize total accrued costs.

Research Organization:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
SC0009297
OSTI ID:
1851173
Journal Information:
Journal of Mechanical Design, Journal Name: Journal of Mechanical Design Journal Issue: 9 Vol. 143; ISSN 1050-0472
Publisher:
ASME
Country of Publication:
United States
Language:
English

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