Hoang Pham

Integrating development processes, policies, and reliability predictions from the beginning of the product development lifecycle to ensure high levels of product performance and safety, this book helps companies overcome the challenges posed by increasingly complex systems in today’s competitive marketplace. Examining both research on and practical aspects of product quality and reliability management with an emphasis on applications, the book features contributions written by active researchers and/or experienced practitioners in the field, so as to effectively bridge the gap between theory and practice and address new research challenges in reliability and quality management in practice. Postgraduates, researchers and practitioners in the areas of reliability engineering and management, amongst others, will find the book to offer a state-of-the-art survey of quality and reliability management and practices.

Quality and Reliability Management and Its Applications

This book discusses practical applications of reliability and statistical methods and techniques in various disciplines, using machine learning, artificial intelligence, optimization, and other computation methods. Bringing together research from international experts, each chapter aims to cover both methods and practical aspects on reliability or statistical computations with emphasis on applications. 5G and IoT are set to generate an estimated 1 billion terabytes of data by 2025 and companies continue to search for new techniques and tools that can help them practice data collection effectively in promoting their business. This book explores the era of big data through reliability and statistical computing, showcasing how almost all applications in our daily life have experienced a dramatic shift in the past two decades to a truly global industry. Including numerous illustrations and worked examples, the book is of interest to researchers, practicing engineers, and postgraduate students in the fields of reliability engineering, statistical computing, and machine learning.

Applications in Reliability and Statistical Computing

An effective reliability programme is an essential component of every product's design, testing and efficient production. From the failure analysis of a microelectronic device to software fault tolerance and from the accelerated life testing of mechanical components to hardware verification, a common underlying philosophy of reliability applies. Defining both fundamental and applied work across the entire systems reliability arena, this state-of-the-art reference presents methodologies for quality, maintainability and dependability. Featuring: Contributions from 60 leading reliability experts in academia and industry giving comprehensive and authoritative coverage. A distinguished international Editorial Board ensuring clarity and precision throughout. Extensive references to the theoretical foundations, recent research and future directions described in each chapter. Comprehensive subject index providing maximum utility to the reader. Applications and examples across all branches of engineering including IT, power, automotive and aerospace sectors. The handbook's cross-disciplinary scope will ensure that it serves as an indispensable tool for researchers in industrial, electrical, electronics, computer, civil, mechanical and systems engineering. It will also aid professional engineers to find creative reliability solutions and management to evaluate systems reliability and to improve processes. For student research projects it will be the ideal starting point whether addressing basic questions in communications and electronics or learning advanced applications in micro-electro-mechanical systems (MEMS), manufacturing and high-assurance engineering systems.

Handbook of Reliability Engineering

Computer software reliability has never been so important. Computers are used in areas as diverse as air traffic control, nuclear reactors, real-time military, industrial process control, security system control, biometric scan-systems, automotive, mechanical and safety control, and hospital patient monitoring systems. Many of these applications require critical functionality as software applications increase in size and complexity. This book is an introduction to software reliability engineering and a survey of the state-of-the-art techniques, methodologies and tools used to assess the reliability of software and combined software-hardware systems. Current research results are reported and future directions are signposted. This text will interest: graduate students as a course textbook introducing reliability engineering software; reliability engineers as a broad, up-to-date survey of the field; and researchers and lecturers in universities and research institutions as a one-volume reference.

System Software Reliability

P.K. Kapur

A. Gupta

P.C. Jha

Software Reliability Assessment with OR Applications is a comprehensive guide to software reliability measurement, prediction, and control. It provides a thorough understanding of the field and gives solutions to the decision-making problems that concern software developers, engineers, practitioners, scientists, and researchers. Using operations research techniques, readers will learn how to solve problems under constraints such as cost, budget and schedules to achieve the highest possible quality level. Software Reliability Assessment with OR Applications is a comprehensive text on software engineering and applied statistics, state-of-the art software reliability modeling, techniques and methods for reliability assessment, and related optimization problems. It addresses various topics, including: unification methodologies in software reliability assessment; application of neural networks to software reliability assessment; software reliability growth modeling using stochastic differential equations; software release time and resource allocation problems; and optimum component selection and reliability analysis for fault tolerant systems. Software Reliability Assessment with OR Applications is designed to cater to the needs of software engineering practitioners, developers, security or risk managers, and statisticians. It can also be used as a textbook for advanced undergraduate or postgraduate courses in software reliability, industrial engineering, and operations research and management.

Software Reliability Assessment with OR Applications

Vijay Kumar

This book provides engineers and researchers knowledge to help them in system reliability analysis using machine learning, artificial intelligence, big data, genetic algorithm, information theory, multi-criteria decision making, and other techniques. It will also be useful to students learning reliability engineering. The book brings readers up to date with how system reliability relates to the latest techniques of AI, big data, genetic algorithm, information theory, and multi-criteria decision making and points toward future developments in the subject.

Predictive Analytics in System Reliability

Alberto Regattieri

Riccardo Manzini

Emilio Ferrari

New, global and extended markets are forcing companies to process and manage increasingly differentiated products with shorter life cycles, low volumes and reduced customer delivery times. In today’s global marketplace production systems need to be able to deliver products on time, maintain market credibility and introduce new products and services faster than competitors. As a result, a new production paradigm of a production system has been developed and a supporting management decision-making approach simultaneously incorporating design, management, and control of the production system is necessary so that this challenge can be effectively and efficiency met. "Maintenance Engineering and its Applications in Production Systems" meets this need by introducing an original and integrated idea of maintenance: maintenance for productivity. The volume starts with the introduction and discussion of a new conceptual framework based on productivity, quality, and safety supported by maintenance. Subsequent chapters illustrate the most relevant models and methods to plan, organise, implement and control the whole maintenance process (reliability evaluation models and prediction, maintenance strategies and policies, spare parts management, computer maintenance management software – CMMS, and total productive maintenance – TPM, etc.). Several examples of problems supported by solutions, and real applications to help and test the reader’s comprehension are included. "Maintenance Engineering and its Applications in Production Systems" will certainly be valuable to engineering students, doctoral and post-doctoral students and also to maintenance practitioners, as well as managers of industrial and service companies.

Maintenance for Industrial Systems

Ngoc Thanh Nguyen

Bogdan Trawiński

Tzung-Pei Hong

Duong Hung Hoang

The two-volume set LNAI 10751 and 10752 constitutes the refereed proceedings of the 10th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2018, held in Dong Hoi City, Vietnam, in March 2018. The total of 133 full papers accepted for publication in these proceedings was carefully reviewed and selected from 423 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Machine Learning and Data Mining; Decision Support and Control Systems; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Multiple Model Approach to Machine Learning; Sensor Networks and Internet of Things; Intelligent Information Systems; Data Structures Modeling for Knowledge Representation; Modeling, Storing, and Querying of Graph Data; Data Science and Computational Intelligence; Design Thinking Based R&D, Development Technique, and Project Based Learning; Intelligent and Contextual Systems; Intelligent Systems and Algorithms in Information Sciences; Intelligent Applications of Internet of Thing and Data Analysis Technologies; Intelligent Systems and Methods in Biomedicine; Intelligent Biomarkers of Neurodegenerative Processes in Brain; Analysis of Image, Video and Motion Data in Life Sciences; Computational Imaging and Vision; Computer Vision and Robotics; Intelligent Computer Vision Systems and Applications; Intelligent Systems for Optimization of Logistics and Industrial Applications.

10th Asian Conference, ACIIDS 2018, Dong Hoi City, Vietnam, March 19-21, 2018, Proceedings, Part I

Intelligent Information and Database Systems

In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.

Hoang Pham

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