Discrete stochastic models and applications for reliability engineering and statistical quality control, Ranjan, Prashant (uni Of Engg And Mgmt, Jaipur) Rao, Ram Shringar (ambedkar Ins. Of Advanced Comm. Tech. And Research, Indraprastha Uni, India) Kumar,
Описание: This book provides real-life examples and illustrations of models in reliability engineering and statistical quality control and establishes a connection between the theoretical framework and their engineering applications.
Автор: Ranjan, Prashant (uni Of Engg And Mgmt, Jaipur) Rao, Ram Shringar (ambedkar Ins. Of Advanced Comm. Tech. And Research, Indraprastha Uni, India) Kumar, Название: Discrete stochastic models and applications for reliability engineering and statistical quality control ISBN: 0520389999 ISBN-13(EAN): 9780520389991 Издательство: Wiley Рейтинг: Цена: 3802.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Aubrey Clayton traces the history of the flaw that underlies modern statistics, beginning with the seventeenth-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Ranging across math, philosophy, and culture, Bernoulli`s Fallacy explains why something has gone wrong with how we use data-and how to fix it.
Описание: The authors offer a handbook for exploration, embodiment and art making: part account of a pilgrimage they walked; part invitation to walk and sensitise ourselves to the world around us in a wholly new way; part political/philosophical/ecological reflection; part compendium of games, pastimes, tactics and new rituals; part invitation to create art.
Описание: This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering.
Описание: Spiritual teachings and guided practices, with audio links, about how to turn off our busy minds anywhere, anytime, and drop down into our hearts, where we find direction and deeper connection with others-from top online spiritual teacher Sarah Blondin, whose meditations have been accessed nearly 10 million times by hundreds or thousands of users.
Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis and related fields.
Specific topics covered include:
* non-parametric estimation of lifetimes of subjects exposed to radiation
* statistical analysis of simultaneous degradation-mortality data with covariates of the aged
* estimation of maintenance efficiency in semiparametric imperfect repair models
* cancer prognosis using survival forests
* short-term health problems related to air pollution: analysis using semiparametric generalized additive models
* parametric models in accelerated life testing and fuzzy data
* semiparametric models in the studies of aging and longevity
This book will be of use as a reference text for general statisticians, theoreticians, graduate students, reliability engineers, health researchers, and biostatisticians working in applied probability and statistics.
Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.
This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing.
The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems.
Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.
Описание: 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.
Описание: Our original objective in writing this book was to demonstrate how the concept of the equation of motion of a Brownian particle — the Langevin equation or Newtonian-like evolution equation of the random phase space variables describing the motion — first formulated by Langevin in 1908 — so making him inter alia the founder of the subject of stochastic differential equations, may be extended to solve the nonlinear problems arising from the Brownian motion in a potential. Such problems appear under various guises in many diverse applications in physics, chemistry, biology, electrical engineering, etc. However, they have been invariably treated (following the original approach of Einstein and Smoluchowski) via the Fokker-Planck equation for the evolution of the probability density function in phase space. Thus the more simple direct dynamical approach of Langevin which we use and extend here, has been virtually ignored as far as the Brownian motion in a potential is concerned. In addition two other considerations have driven us to write this new edition of The Langevin Equation. First, more than five years have elapsed since the publication of the third edition and following many suggestions and comments of our colleagues and other interested readers, it became increasingly evident to us that the book should be revised in order to give a better presentation of the contents. In particular, several chapters appearing in the third edition have been rewritten so as to provide a more direct appeal to the particular community involved and at the same time to emphasize via a synergetic approach how seemingly unrelated physical problems all involving random noise may be described using virtually identical mathematical methods. Secondly, in that period many new and exciting developments have occurred in the application of the Langevin equation to Brownian motion. Consequently, in order to accommodate all these, a very large amount of new material has been added so as to present a comprehensive overview of the subject.
Описание: An examination of system reliability theory, this title features in-depth discussion of dependability management and reliability centered systems as well as functional safety issues-matters critical to the IEC standards.
Автор: Meeker William Q. Название: Statistical Methods for Reliability Data ISBN: 1118115457 ISBN-13(EAN): 9781118115459 Издательство: Wiley Рейтинг: Цена: 18208.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An authoritative guide to the most recent advances in statistical methods for quantifying reliability
Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book's website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook.
The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data.
SMRD2 features:
Contains a wealth of information on modern methods and techniques for reliability data analysis
Offers discussions on the practical problem-solving power of various Bayesian inference methods
Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website
Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter
Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts
Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.
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