IEEE Std 1332-2012 (Revision of IEEE Std 1332-1998)
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Release : 2012
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Author : Dev G. Raheja
Publisher : John Wiley & Sons
Page : 261 pages
File Size : 33,20 MB
Release : 2012-07-20
Category : Technology & Engineering
ISBN : 1118310039
A unique, design-based approach to reliability engineering Design for Reliability provides engineers and managers with a range of tools and techniques for incorporating reliability into the design process for complex systems. It clearly explains how to design for zero failure of critical system functions, leading to enormous savings in product life-cycle costs and a dramatic improvement in the ability to compete in global markets. Readers will find a wealth of design practices not covered in typical engineering books, allowing them to think outside the box when developing reliability requirements. They will learn to address high failure rates associated with systems that are not properly designed for reliability, avoiding expensive and time-consuming engineering changes, such as excessive testing, repairs, maintenance, inspection, and logistics. Special features of this book include: A unified approach that integrates ideas from computer science and reliability engineering Techniques applicable to reliability as well as safety, maintainability, system integration, and logistic engineering Chapters on design for extreme environments, developing reliable software, design for trustworthiness, and HALT influence on design Design for Reliability is a must-have guide for engineers and managers in R&D, product development, reliability engineering, product safety, and quality assurance, as well as anyone who needs to deliver high product performance at a lower cost while minimizing system failure.
Author : Sabina Jeschke
Publisher : Springer
Page : 714 pages
File Size : 13,62 MB
Release : 2016-10-12
Category : Technology & Engineering
ISBN : 3319425595
This book develops the core system science needed to enable the development of a complex industrial internet of things/manufacturing cyber-physical systems (IIoT/M-CPS). Gathering contributions from leading experts in the field with years of experience in advancing manufacturing, it fosters a research community committed to advancing research and education in IIoT/M-CPS and to translating applicable science and technology into engineering practice. Presenting the current state of IIoT and the concept of cybermanufacturing, this book is at the nexus of research advances from the engineering and computer and information science domains. Readers will acquire the core system science needed to transform to cybermanufacturing that spans the full spectrum from ideation to physical realization.
Author : Aurélien Muise
Publisher : Springer Nature
Page : 139 pages
File Size : 11,70 MB
Release : 2022-05-31
Category : Computers
ISBN : 303101572X
Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learning literature that covers algorithms, theory and applications for both numerical and structured data. We first introduce relevant definitions and classic metric functions, as well as examples of their use in machine learning and data mining. We then review a wide range of metric learning algorithms, starting with the simple setting of linear distance and similarity learning. We show how one may scale-up these methods to very large amounts of training data. To go beyond the linear case, we discuss methods that learn nonlinear metrics or multiple linear metrics throughout the feature space, and review methods for more complex settings such as multi-task and semi-supervised learning. Although most of the existing work has focused on numerical data, we cover the literature on metric learning for structured data like strings, trees, graphs and time series. In the more technical part of the book, we present some recent statistical frameworks for analyzing the generalization performance in metric learning and derive results for some of the algorithms presented earlier. Finally, we illustrate the relevance of metric learning in real-world problems through a series of successful applications to computer vision, bioinformatics and information retrieval. Table of Contents: Introduction / Metrics / Properties of Metric Learning Algorithms / Linear Metric Learning / Nonlinear and Local Metric Learning / Metric Learning for Special Settings / Metric Learning for Structured Data / Generalization Guarantees for Metric Learning / Applications / Conclusion / Bibliography / Authors' Biographies
Author : Shimon Y. Nof
Publisher : Springer Nature
Page : 1533 pages
File Size : 33,45 MB
Release : 2023-06-16
Category : Technology & Engineering
ISBN : 3030967298
This handbook incorporates new developments in automation. It also presents a widespread and well-structured conglomeration of new emerging application areas, such as medical systems and health, transportation, security and maintenance, service, construction and retail as well as production or logistics. The handbook is not only an ideal resource for automation experts but also for people new to this expanding field.