Recent advances in science and technology have made modern computing and engineering systems more powerful and sophisticated than ever. The increasing complexity and scale imply that system reliability problems not only continue to be a challenge but also require more efficient models and solutions. This is the first book systematically covering the state-of-the-art binary decision diagrams and their extended models, which can provide efficient and exact solutions to reliability analysis of large and complex systems. The book provides both basic concepts and detailed algorithms for modelling...

This book explores the domain of reliability engineering in the context of machine tools. Failures of machine tools not only jeopardize users' ability to meet their due date commitments but also lead to poor quality of products, slower production, down time losses etc.

Poor reliability and improper maintenance of a machine tool greatly increases the life cycle cost to the user. Thus, the application area of the present book, i.e. machine tools, will be equally appealing to machine tool designers, production engineers and maintenance managers. The book will serve as a consolidated...

Artificial neural network (ANN) has proven to be a universal approximator for any non-linear continuous function with arbitrary accuracy. This book presents how to apply ANN to measure various software reliability indicators: number of failures in a given time, time between successive failures, fault-prone modules and development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction during testing phase as well as early phases of software development process is presented as well. Applications of artificial neural...