The 2006 Asian International Workshop on Advanced Reliability Modeling (AIWARM) is the second symposium in a series of biennial workshops for the dissemination of state-of-art research and the presentation of practice in reliability and maintenance engineering in Asia. It brings together researchers and engineers from not only Asian countries but also all over world to discuss the state of research and practice in dealing with both reliability issues at the system design phase and maintenance issues at the system operation phase. The theme of AIWARM 2006 is “reliability testing and improvement”. The contributions in this volume cover all the main topics in reliability and maintenance engineering, providing an in-depth presentation of theory and practice.

Reliability modeling has been a major concern for engineers and managers engaged in high quality system designs. This book presents the recent advancement in reliability theory and reliability engineering.Starting from maintenance policies, the book introduces reliability analysis to systems using stochastic processes to study their optimization problems. In this book, the authors will illustrate how these techniques of reliability are applied to solve optimization problems in computer, information and network systems.

Innovative tools for reliability analysis and decision making in design, operation and maintenance of engineering systems in today s connected era are critical for safe, reliable and effective operation of these systems The 9th Asia Pacific International Symposium on Advanced Reliability and Maintenance Modelling (APARM 2020) to be held at the Pan Pacific Hotel Vancouver, Canada (August 20 23, 2020) aims to provide a friendly platform for synergistic exchanges of ideas and practices among academics and industry practitioners The conference will cover a broad range of research and application topics relevant to reliability and maintenance

The 2007 winner of the Masing Book Prize sets out important Six Sigma concepts and a selection of up-to-date tools for quality improvement in industry. Six Sigma is a widely used methodology for measuring and improving an organization’s operational performance through a rigorous analysis of its practices and systems. This book presents a series of papers providing a systematic ‘roadmap’ for implementing Six Sigma, following the DMAIC (Define, Measure, Analyse, Improve and Control) phased approach. Motivated by actual problems, the authors offer insightful solutions to some of the most commonly encountered issues in Six Sigma projects, such as validation of normality, experimentation under constraints and statistical control of complex processes. They also include many examples and case studies to help readers learn how to apply the appropriate techniques to real-world problems. Key features: Provides a comprehensive introduction to Six Sigma, with a critical strategic assessment and a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis. Presents some prominent design features of Six Sigma, and a newly proposed roadmap for healthcare delivery. Sets out information on graphical tools, including fishbone diagrams, mind-maps, and reality trees. Gives a thorough treatment of process capability analysis for non-normal data. Discusses advanced tools for Six Sigma, such as statistical process control for autocorrelated data. Consolidating valuable methodologies for process optimization and quality improvement, Six Sigma: Advanced Tools for Black Belts and Master Black Belts is a unique reference for practising engineers in the electronics, defence, communications and energy industries. It is also useful for graduate students taking courses in quality assurance.

This book shares key insights into system performance and management analytics, demonstrating how the field of analytics is currently changing and how it is used to monitor companies’ efforts to drive performance.Managing business performance facilitates the effective accomplishment of strategic and operational goals, and there is a clear and direct correlation between using performance management applications and improved business and organizational results. As such, performance and management analytics can yield a range of direct and indirect benefits, boost operational efficiency and unlock employees’ latent potential, while at the same time aligning services with overarching goals.The book addresses a range of topics, including software reliability assessment, testing, quality management, system-performance management, analysis using soft-computing techniques, and management analytics. It presents a balanced, holistic approach to viewing the world from both a technical and managerial perspective by considering performance and management analytics. Accordingly, it offers a comprehensive guide to one of the most pressing issues in today’s technology-dominated world, namely, that most companies and organizations find themselves awash in a sea of data, but lack the human capital, appropriate tools and knowledge to use it to help them create a competitive edge.

Warranty Data Collection and Analysis deals with warranty data collection and analysis and the problems associated with these activities. The book is a both a research monograph and a handbook for practitioners. As a research monograph, it unifies the literature on warranty data collection and analysis, and presents the important results in an integrated manner. In the process, it highlights topics that require further research. As a handbook, it provides the essential methodology needed by practitioners involved with warranty data collection and analysis, along with extensive references to further results. Models and techniques needed for proper and effective analysis of data are included, together with guidelines for their use in warranty management, product improvement, and new product development. Warranty Data Collection and Analysis will be of interest to researchers (engineers and statisticians) and practitioners (engineers, applied statisticians, and managers) involved with product warranty and reliability. It is also suitable for use as a reference text for graduate-level reliability programs in engineering, applied statistics, operations research, and management.

This book provides a detailed understanding of optimization methods as they are implemented in a variety of manufacturing, fabrication and machining processes. It covers the implementation of statistical methods, multi-criteria decision making methods and evolutionary techniques for single and multi-objective optimization to improve quality, productivity, and sustainability in manufacturing. It reports on the theoretical aspects, special features, recent research and latest development in the field. Optimization of Manufacturing Processes is a valuable source of information for researchers and practitioners, as it fills the gap where no dedicated book is available on intelligent manufacturing/modeling and optimization in manufacturing. Readers will develop an understanding of the implementation of statistical and evolutionary techniques for modeling and optimization in manufacturing.