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This textbook teaches methods of data analytics for technical reliability analyses and risk prognosis on the basis of probabilistics, statistics and modelling. The methods of Reliability Engineering are applied in the elementary phases of the product emergence process (concept and series development, production) as well as during the field use of technical products. This book contains a detailed outline of the basics of statistics, graphical visualisation and calculation methods. Numerous case studies are discussed, representing typical tasks of the engineer in reliability analysis during development/production as well as during the assessment of field damages. The target groups are thus both engineering students and practitioning engineers who deal with technical reliability in the context of the development and manufacturing of complex technical products as well as field data analyses. The presentation of the methods and procedures of Reliability Engineering follows the guideline "theory-guided - practice-oriented", so that this book can be used both as a reference work and as a textbook. About the author Univ.-Prof. Dr.-Ing. Stefan Bracke studied mechanical engineering at the University of Bochum and received his doctorate in the field of quality assurance within product recycling. After working at Porsche AG and the Technical University of Cologne, he has been Professor of Reliability Engineering and Risk Analytics at the University of Wuppertal since 2010. Furthermore, he accepted a guest professorship at Meiji University in Tokyo, Japan, in 2016. The focus of his research and teaching is on reliability and risk analytics in the development, manufacture and field use of technical products. This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

Industrial engineering. --- Production engineering. --- Operations research. --- Statistics. --- Engineering mathematics. --- Engineering --- Industrial and Production Engineering. --- Operations Research and Decision Theory. --- Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. --- Mathematical and Computational Engineering Applications. --- Data processing.

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