Gregory Levitin – författare

Offers timely and comprehensive coverage of dynamic system reliability theoryThis book focuses on hot issues of dynamic system reliability, systematically introducing the reliability modeling and analysis methods for systems with imperfect fault coverage, systems with function dependence, systems subject to deterministic or probabilistic common-cause failures, systems subject to deterministic or probabilistic competing failures, and dynamic standby sparing systems. It presents recent developments of such extensions involving reliability modelling theory, reliability evaluation methods, and features numerous case studies based on real-world examples. The presented dynamic reliability theory can enable a more accurate representation of actual complex system behavior, thus more effectively guiding the reliable design of real-world critical systems.Dynamic System Reliability: Modelling and Analysis of Dynamic and Dependent Behaviors begins by describing the evolution from the traditional static reliability theory to the dynamic system reliability theory, and provides a detailed investigation of dynamic and dependent behaviors in subsequent chapters. Although written for those with a background in basic probability theory and stochastic processes, the book includes a chapter reviewing the fundamentals that readers need to know in order to understand contents of other chapters which cover advanced topics in reliability theory and case studies.  The first book systematically focusing on dynamic system reliability modelling and analysis theoryProvides a comprehensive treatment on imperfect fault coverage (single-level/multi-level or modular), function dependence, common cause failures (deterministic and probabilistic), competing failures (deterministic and probabilistic), and dynamic standby sparingIncludes abundant illustrative examples and case studies based on real-world systemsCovers recent advances in combinatorial models and algorithms for dynamic system reliability analysisOffers a rich set of references, providing helpful resources for readers to pursue further research and study of the topicsDynamic System Reliability: Modelling and Analysis of Dynamic and Dependent Behaviors is an excellent book for undergraduate and graduate students, and engineers and researchers in reliability and related disciplines.

Many real systems are composed of multi-state components with different performance levels and several failure modes. These affect the whole system's performance. Most books on reliability theory cover binary models that allow a system only to function perfectly or fail completely. "The Universal Generating Function in Reliability Analysis and Optimization" is the first book that gives a comprehensive description of the universal generating function technique and its applications in binary and multi-state system reliability analysis. Features:- an introduction to basic tools of multi-state system reliability and optimization;- applications of the universal generating function in widely used multi-state systems;- examples of the adaptation of the universal generating function to different systems in mechanical, industrial and software engineering. This monograph will be of value to anyone interested in system reliability, performance analysis and optimization in industrial, electrical and nuclear engineering.

Many real systems are composed of multi-state components with different performance levels and several failure modes. These affect the whole system's performance.Most books on reliability theory cover binary models that allow a system only to function perfectly or fail completely.The Universal Generating Function in Reliability Analysis and Optimization is the first book that gives a comprehensive description of the universal generating function technique and its applications in binary and multi-state system reliability analysis.Features:-an introduction to basic tools of multi-state system reliability and optimization;-applications of the universal generating function in widely used multi-state systems;-examples of the adaptation of the universal generating function to different systems in mechanical, industrial and software engineering.This monograph will be of value to anyone interested in system reliability, performance analysis and optimization in industrial, electrical and nuclear engineering.

This two-volume book covers the recent applications of computational intel- gence techniques in reliability engineering. Research in the area of computational intelligence is growing rapidly due to the many successful applications of these new techniques in very diverse problems. “Computational Intelligence” covers many fields such as neural networks, fuzzy logic, evolutionary computing, and their hybrids and derivatives. Many industries have benefited from adopting this technology. The increased number of patents and diverse range of products dev- oped using computational intelligence methods is evidence of this fact. These techniques have attracted increasing attention in recent years for solving many complex problems. They are inspired by nature, biology, statistical te- niques, physics and neuroscience. They have been successfully applied in solving many complex problems where traditional problem-solving methods have failed. The book aims to be a repository for the current and cutting-edge applications of computational intelligent techniques in reliability analysis and optimization.

This two volume book covers the recent applications of computational intelli gence techniques in reliability engineering. Research in the area of computational intelligence is growing rapidly due to the many successful applications of these new techniques in very diverse problems. “Computational Intelligence” covers many fields such as neural networks, fu zzy logic, evolutionary computing, and their hybrids and derivatives. Many indus tries have benefited from adopting this technology. The increased number of patents and diverse range of products devel oped using computational intelligence methods is evidence of this fact. These techniques have attracted increasing attention in recent years for solving many complex problems. They are inspired by nature, biology, statistical tech niques, physics and neuroscience. They have been successfully applied in solving many complex problems where traditional problem solving methods have failed. The book aims to be a repository for the current and cutting edge applications of computational intelligent techniques in reliability analysis and optimization.

This two-volume book covers the recent applications of computational intel- gence techniques in reliability engineering. Research in the area of computational intelligence is growing rapidly due to the many successful applications of these new techniques in very diverse problems. “Computational Intelligence” covers many fields such as neural networks, fuzzy logic, evolutionary computing, and their hybrids and derivatives. Many industries have benefited from adopting this technology. The increased number of patents and diverse range of products dev- oped using computational intelligence methods is evidence of this fact. These techniques have attracted increasing attention in recent years for solving many complex problems. They are inspired by nature, biology, statistical te- niques, physics and neuroscience. They have been successfully applied in solving many complex problems where traditional problem-solving methods have failed. The book aims to be a repository for the current and cutting-edge applications of computational intelligent techniques in reliability analysis and optimization.

This two volume book covers the recent applications of computational intelli gence techniques in reliability engineering. Research in the area of computational intelligence is growing rapidly due to the many successful applications of these new techniques in very diverse problems. “Computational Intelligence” covers many fields such as neural networks, fu zzy logic, evolutionary computing, and their hybrids and derivatives. Many indus tries have benefited from adopting this technology. The increased number of patents and diverse range of products devel oped using computational intelligence methods is evidence of this fact. These techniques have attracted increasing attention in recent years for solving many complex problems. They are inspired by nature, biology, statistical tech niques, physics and neuroscience. They have been successfully applied in solving many complex problems where traditional problem solving methods have failed. The book aims to be a repository for the current and cutting edge applications of computational intelligent techniques in reliability analysis and optimization.