Decision-Making Under Uncertainty for a Digital Thread-Enabled Design Process
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 24, 2021
- Source ID
- 10.1115/1.4050108
Entities
People
- Karen Willcox
- Victor Singh
Organizations
- Air Force Office of Scientific Research
- Massachusetts Institute of Technology
- Office of Advanced Scientific Computing Research
- University of Texas at Austin