Abstract

AbstractThis chapter describes the various approaches to analyse, quantify and evaluate uncertainty along the phases of the product life cycle. It is based on the previous chapters that introduce a consistent classification of uncertainty and a holistic approach to master the uncertainty of technical systems in mechanical engineering. Here, the following topics are presented: the identification of uncertainty by modelling technical processes, the detection and handling of data-induced conflicts, the analysis, quantification and evaluation of model uncertainty as well as the representation and visualisation of uncertainty. The different approaches are discussed and demonstrated on exemplary technical systems.

Highlights

  • This chapter describes the various approaches to analyse, quantify and evaluate uncertainty along the phases of the product life cycle

  • The observations described in this contribution show that if aleatoric data uncertainty occurs, high active damping results in less scatter at angular frequencies beyond the isolation point compared to the passive approach, see [128]

  • The scatter of the amplitude attenuation beyond the angular isolation frequency is smaller with the active approach

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Summary

Introduction

This chapter describes the various approaches to analyse, quantify and evaluate uncertainty along the phases of the product life cycle It is based on the previous chapters that introduce a consistent classification of uncertainty and a holistic approach to master the uncertainty of technical systems in mechanical engineering. This chapter deals with the analysis, quantification and evaluation of data and model uncertainty in mechanical engineering as an essential first step to master uncertainty. This will be extended and completed by the methods and technologies to. We provide both a mathematical and an engineering perspective to the analysis, quantification and evaluation of data and model uncertainty

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