Analytics Modeling In Reliability And Machine Learning And Its Applications
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Analytics Modeling in Reliability and Machine Learning and Its Applications
This book presents novel research and application chapters on topics in reliability, statistics, and machine learning. It has an emphasis on analytical models and techniques and practical applications in reliability engineering, data science, manufacturing, health care, and industry using machine learning, AI, optimization, and other computational methods. Today, billions of people are connected to each other through their mobile devices. Data is being collected and analysed more than ever before. The era of big data through machine learning algorithms, statistical inference, and reliability computing in almost all applications has resulted in a dramatic shift in the past two decades. Data analytics in business, finance, and industry is vital. It helps organizations and business to achieve better results and fact-based decision-making in all aspects of life. The book offers a broad picture of current research on the analytics modeling and techniques and its applications in industry. Topics include: l Reliability modeling and methods. l Software reliability engineering. l Maintenance modeling and policies. l Statistical feature selection. l Big data modeling. l Machine learning: models and algorithms. l Data-driven models and decision-making methods. l Applications and case studies in business, health care, and industrial systems. Postgraduates, researchers, professors, scientists, engineers, and practitioners in reliability engineering and management, machine learning engineering, data science, operations research, industrial and systems engineering, statistics, computer science and engineering, mechanical engineering, and business analytics will find in this book state-of-the-art analytics, modeling and methods in reliability and machine learning.
Reliability Engineering
Author: Massimo Lazzaroni
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-08-31
This book gives a practical guide for designers and users in Information and Communication Technology context. In particular, in the first Section, the definition of the fundamental terms according to the international standards are given. Then, some theoretical concepts and reliability models are presented in Chapters 2 and 3: the aim is to evaluate performance for components and systems and reliability growth. Chapter 4, by introducing the laboratory tests, puts in evidence the reliability concept from the experimental point of view. In ICT context, the failure rate for a given system can be evaluate by means of specific reliability prediction handbooks; this aspect is considered in Chapter 5, with practical applications. In Chapters 6, 7 and 8, the more complex aspects regarding both the Maintainability, Availability and Dependability are taken into account; in particular, some fundamental techniques such as FMECA (Failure Mode, Effects, and Criticality Analysis) and FTA (Fault Tree Analysis) are presented with examples for reparable systems.
Quantile-Based Reliability Analysis
Author: N. Unnikrishnan Nair
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-08-24
This book provides a fresh approach to reliability theory, an area that has gained increasing relevance in fields from statistics and engineering to demography and insurance. Its innovative use of quantile functions gives an analysis of lifetime data that is generally simpler, more robust, and more accurate than the traditional methods, and opens the door for further research in a wide variety of fields involving statistical analysis. In addition, the book can be used to good effect in the classroom as a text for advanced undergraduate and graduate courses in Reliability and Statistics.