Uncertainty Quantification in Digital Twin Simulations

Bahar Biller (), Canan Gunes Corlu () and Stephan R. Biller ()
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Bahar Biller: SAS Institute
Canan Gunes Corlu: Boston University, Metropolitan College
Stephan R. Biller: Purdue University

Chapter Chapter 10 in Optimizing Supply Chains Through Digital Twins, 2025, pp 163-194 from Springer

Abstract: Abstract One of the challenges of developing digital twin simulations stems from lacking full information about business process flows and characterizations of their input distributions. This chapter describes how this challenge arises in different phases of digital twin development. We present practitioners an overview of solutions to use for correctly quantifying the overall uncertainty in digital twin simulation development. We accompany the presentation with a supply chain use case.

Keywords: Data-driven simulation; Digital twin; Factory twin; Input uncertainty; Risk management; Supply chain twin; Uncertainty quantification (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-032-08147-6_10

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DOI: 10.1007/978-3-032-08147-6_10

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