Robust Design and Uncertainty Quantification for Managing Risks in Engineering

Ron Bates ()
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Ron Bates: Rolls-Royce plc., Design Sciences, Engineering Capability

Chapter 42 in Handbook of Uncertainty Quantification, 2017, pp 1421-1436 from Springer

Abstract: Abstract Methods for uncertainty quantification lie at the heart of the robust design process. Good robust design practice seeks to understand how a product or ;process behaves under uncertain conditions to design out unwanted effects such as inconsistent or below-par performance or reduced life (and hence increased service or total life cycle costs). Understanding these effects can be very costly, requiring a deep understanding of the system(s) under investigation and of the uncertainties to be guarded against. This chapter explores applications of UQ methods in an engineering design environment, including discussions on risk and decision, systems engineering, and validation and verification. The need for a well-aligned hierarchy of high-quality models is also discussed. These topics are brought together in an Uncertainty Management Framework to provide an overall context for embedding UQ methods in the engineering design process. Lastly, some significant challenges to the approach are highlighted.

Keywords: Systems Engineering; Verification & Validation; Risk; Decision Making; Simulation; Uncertainty Propagation; Robust optimization (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-12385-1_45

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DOI: 10.1007/978-3-319-12385-1_45

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