Titlebook: Reliability Engineering; Data analytics, mode Stefan Bracke Textbook 2024 Springer-Verlag GmbH Germany, part of Springer Nature 2024 Functi

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Distribution Models and Functions,f a distribution model is given in Sect.?7.1, followed by an explanation of important continuous distribution models (Sect.?7.2) and test distributions (Sect.?7.3).?Subsequently, Sect.?7.4 is focusing to discrete distribution models. Section 7.5 focuses on the saturation function, which can be used

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Distribution Models: Parameter Estimation,e robust and manually simple procedure of regression analysis, which is suitable for many distribution models, is shown in Sect.?8.1. A frequently used iterative procedure is the maximum likelihood estimator (MLE) according to Fisher (1912) shown in Sect.?8.2.?In addition, further estimation methods

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Confidence Intervals,tervals are presented in an introductory chapter (cf. Sect.?9.1). Subsequently, procedures for the determination of confidence intervals of the parameters mean and dispersion in the case of a normally distributed population are presented (Sect.?9.2) as well as the confidence interval for a proportio

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Correlation and Regression, other: correlation analysis and the regression analysis that often goes hand in hand with it can be used to map the relationship between two or more variables. Section?10.1 shows the basics and outlines some fields of application. Subsequently, Sect.?10.2 presents bivariate correlation analysis in

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Analysis of the Failure Behaviour of Components, Assemblies, Systems,ms and can be used in the context of a prototype test (development phase), during the end-of-line test (production) or on the basis of a product fleet in field use. Sect.?12.1 presents the general approach. Sect.?12.2 shows the exemplary application of data analysis on the basis of a given damage da

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Significance Tests,nd explains possible objectives in the context of an application example. The fundamentals of significance testing as well as the associated key indicators and terminology are the focus of Sect.?13.2.?Significance tests for the investigation of an existing series of measurements—the one-sample case—

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Prototype Testing and Accelerated Testing,product at a certain stage of development. The present chapter is first devoted to the fundamentals of accelerated testing (Sect.?14.1). Afterwards, important models are presented which can be used in the planning and analysis of accelerated testing activities, e.g. Arrhenius model, W?hler test, Cof

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Test Process Suitability,t, production and field support. The analysis of measurement and test processes takes place within the framework of test planning. Test planning includes the planning of test procedures, test equipment, test aids, test scope and frequency, test personnel, test time, test location as well as the docu

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Statistical Process Control (SPC),ucts. The term “reliability” refers here?–?in deviation from the definition in Chap.?3?–?to the probability of a defect-free proportion with respect to a monitored product characteristic within a defined time interval of product manufacture. If the monitoring refers to a production process character