Risk based uncertainty quantification to improve robustness of manufacturing operations

Robustness-based portfolio optimization under epistemic uncertainty

In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...

Robustness to strategic uncertainty

In games with continuum strategy sets, we model a player’s uncertainty about another player’s strategy, as an atomless probability distribution over the other player’s strategy set. We call a strategy profile (strictly) robust to strategic uncertainty if it is the limit, as uncertainty vanishes, of some sequence (all sequences) of strategy profiles in which every player’s strategy is optimal un...

Introduction to Uncertainty Quantification

“It worked for manufacturing...!” Operations strategy in project-based operations

This paper describes the application of an Operations Strategy (OS) approach to project-based operations (PBOs), defined as low to medium volume and medium to high variety operations. The OS approach has been extensively and beneficially used in high and medium volume operations. By examining the development of OS from its genesis in manufacturing operations, we identify four aspects of the OS ...

Robustness-based Design Optimization under Data Uncertainty

This paper proposes formulations and algorithms for design optimization under both aleatory (i.e., natural or physical variability) and epistemic uncertainty (i.e., imprecise probabilistic information), from the perspective of system robustness. The proposed formulations deal with epistemic uncertainty arising from both sparse and interval data without any assumption about the probability distr...