Edición de la obra Introduction to Fuzzy Reliability
| Autor | Kai-Yuan Cai |
|---|---|
| Editorial | Springer US |
| Fecha de publicación | 1996 |
| Lugar | Boston, MA |
| Idioma | inglés |
| Páginas | 336 |
| Formato | [electronic resource] / |
| ISBN-13 | 9781461286080, 9781461314035 |
| ISBN-10 | 1461286085, 1461314038 |
| OCLC | 852788893 |
| Serie | The Kluwer International Series in Engineering and Computer Science -- 363 · Kluwer international series in engineering and computer science -- 363. |
| Número de Cutter | C133i |
|---|
Introduction to Fuzzy Reliability treats fuzzy methodology in hardware reliability and software reliability in a relatively systematic manner. The contents of this book are organized as follows. Chapter 1 places reliability engineering in the scope of a broader area, i.e. system failure engineering. Readers will find that although this book is confined to hardware and software reliability, it may be useful for other aspects of system failure engineering, like maintenance and quality control. Chapter 2 contains the elementary knowledge of fuzzy sets and possibility spaces which are required reading for the rest of this book. This chapter is included for the overall completeness of the book, but a few points (e.g. definition of conditional possibility and existence theorem of possibility space) may be new. Chapter 3 discusses how to calculate probist system reliability when the component reliabilities are represented by fuzzy numbers, and how to analyze fault trees when probabilities of basic events are fuzzy. Chapter 4 presents the basic theory of profust reliability, whereas Chapter 5 analyzes the profust reliability behavior of a number of engineering systems. Chapters 6 and 7 are devoted to probist reliability theory from two different perspectives. Chapter 8 discusses how to model software reliability behavior by using fuzzy methodology. Chapter 9 includes a number of mathematical problems which are raised by applications of fuzzy methodology in hardware and software reliability, but may be important for fuzzy set and possibility theories.