Structural and System Reliability (1版)
類似書籍推薦給您
立即查看
DESIGN OF EXPERIMENTS FOR RELIABILITY ACHIEVEMENT
類似書籍推薦給您
DESCRIPTION
ENABLES READERS TO UNDERSTAND THE METHODS OF EXPERIMENTAL DESIGN TO SUCCESSFULLY CONDUCT LIFE TESTING TO IMPROVE PRODUCT RELIABILITY
This book illustrates how experimental design and life testing can be used to understand product reliability in order to enable reliability improvements. The book is divided into four sections. The first section focuses on statistical distributions and methods for modeling reliability data. The second section provides an overview of design of experiments including response surface methodology and optimal designs. The third section describes regression models for reliability analysis focused on lifetime data. This section provides the methods for how data collected in a designed experiment can be properly analyzed. The final section of the book pulls together all of the prior sections with customized experiments that are uniquely suited for reliability testing. Throughout the text, there is a focus on reliability applications and methods. It addresses both optimal and robust design with censored data.
To aid in reader comprehension, examples and case studies are included throughout the text to illustrate the key factors in designing experiments and emphasize how experiments involving life testing are inherently different. The book provides numerous state-of-the-art exercises and solutions to help readers better understand the real-world applications of experimental design and reliability. The authors utilize R and JMP® software throughout as appropriate, and a supplemental website contains the related data sets.
Written by internationally known experts in the fields of experimental design methodology and reliability data analysis, sample topics covered in the book include:
An introduction to reliability, lifetime distributions, censoring, and inference for parameter of lifetime distributions
Design of experiments, optimal design, and robust design
Lifetime regression, parametric regression models, and the Cox Proportional Hazard Model
Design strategies for reliability achievement
Accelerated testing, models for acceleration, and design of experiments for accelerated testing
The text features an accessible approach to reliability for readers with various levels of technical expertise. This book is a key reference for statistical researchers, reliability engineers, quality engineers, and professionals in applied statistics and engineering. It is a comprehensive textbook for upper-undergraduate and graduate-level courses in statistics and engineering.
立即查看
RELIABILITY ANALYSIS USING MINITAB AND PYTHON 2022 <John Wiley>
類似書籍推薦給您
【簡介】
Description
Reliability Analysis Using Minitab and Python expertly applies Minitab and Python programs to the field of reliability engineering, presenting basic concepts and explaining step-by-step how to implement statistical distributions and reliability analysis methods using the two programming languages. The textbook enables readers to effectively use software to efficiently process massive amounts of data while also reducing human error.
Examples and case studies as well as exercises and questions are included throughout to enable a smooth learning experience. Excel files containing the sample data and Minitab and Python example files are also provided.
Students who have basic knowledge of probability and statistics will find this textbook highly approachable. Nonetheless, it also covers material on basic statistics at the beginning, so students who are not familiar with statistics can follow the material as well.
Written by a highly qualified author in the field, sample topics covered in Reliability Analysis Using Minitab and Python include:
Establishing a basic statistical background, with a focus on probability, joint probability, union probability, conditional probability, mutually exclusive events, and bayes’ rule
Statistical distributions, with a focus on discrete cases, continuous cases, exponential distribution, Weibull distribution, normal distribution, and lognormal distribution
Reliability data plotting, with a focus on straight line properties, least squares fit, linear rectification, exact failure times, and readout failure data
Accelerated life testing, with a focus on accelerated testing theory, exponential distribution acceleration, and Weibull distribution acceleration
System failure modeling, with a focus on reliability block diagram, series system model, parallel system model, k-out-of-n system model, and minimal paths and minimal cuts.
Repairable systems, with a focus on corrective and preventive maintenances, availability, maintainability, and preventive maintenance scheduling
Reliability Analysis Using Minitab and Python serves as an excellent introductory level textbook on the topic for both undergraduate and graduate students. It presents information clearly and concisely and includes many helpful additional learning resources to aid in understanding of concepts, information retention, and practical application.
【目錄】
Table of Contents
1 Introduction
2 Basic Concepts of Probability
3 Lifetime Distributions
4 Reliability Data Plotting
5 Accelerated Life Testing
6 System Failure Modeling
7 Repairable Systems
8 Case Studiesa
原價:
1700
售價:
1598
現省:
102元
立即查看
Statistical Methods for Reliability Data (2版)
類似書籍推薦給您
商品描述
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. This text 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.
This Second Edition:
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 includes access to a companion website with 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 data sets used in the book's examples and exercises.
商品描述(中文翻譯)
《統計方法應用於可靠性數據的權威指南》
《統計方法應用於可靠性數據,第二版》(SMRD2)是一本關於可靠性數據分析和可靠性測試計劃的最廣泛使用和最新發展的統計方法的必備指南。由三位領域專家撰寫,SMRD2更新並擴展了長期以來的統計技術,並展示了如何應用強大的圖形、數值和基於模擬的方法於可靠性的各種應用中。SMRD2是一個全面的資源,描述了最大概似和貝葉斯方法來解決產品可靠性和相似應用領域中出現的實際問題。本書通過眾多應用案例來說明方法,並且所有數據集都可以在書籍的網站上找到。此外,SMRD2還包含了大量的練習題,以增強其作為課程教材的使用價值。
本書第二版的特點如下:
- 包含了大量關於現代可靠性數據分析方法和技術的信息
- 討論了各種貝葉斯推斷方法在實際問題解決中的實用性
- 提供了使用R接口到Stan系統進行的貝葉斯數據分析示例,這些Stan模型可以在書籍的網站上找到
- 每章末尾提供了有用的技術問題和數據分析練習題
- 提供了以數據、分析結果和技術概念為重點的示意圖
《統計方法應用於可靠性數據,第二版》針對工業界和學術界的工程師和統計學家撰寫,並提供了一個附帶網站,其中包含有價值的資源,包括R套件、Stan模型代碼、演示幻燈片、技術筆記、關於商業軟體的可靠性數據分析信息,以及用於書中示例和練習的csv數據集。
作者簡介
William Q. Meeker, PhD, is Professor of Statistics and Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He is a Fellow of the American Association for the Advancement of Science, the American Statistical Association, and the American Society for Quality.
Luis A. Escobar, PhD, is a Professor in the Department of Experimental Statistics at Louisiana State University. He is a Fellow of the American Statistical Association, an elected member of the International Statistics Institute, and an elected Member of the Colombian Academy of Sciences.
Francis G. Pascual, PhD, is an Associate Professor in the Department of Mathematics and Statistics at Washington State University.
作者簡介(中文翻譯)
William Q. Meeker, PhD 是愛荷華州立大學統計學教授和自由藝術與科學卓越教授。他是美國科學促進協會、美國統計學會和美國品質學會的會士。
Luis A. Escobar, PhD 是路易斯安那州立大學實驗統計學系教授。他是美國統計學會的會士,國際統計學會的選舉會員,以及哥倫比亞科學院的選舉會員。
Francis G. Pascual, PhD 是華盛頓州立大學數學與統計學系副教授。
原價:
1820
售價:
1693
現省:
127元
立即查看
Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives
類似書籍推薦給您
Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives
An insightful treatment of present and emerging technologies in fault diagnosis and failure prognosis
In Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives, a team of distinguished researchers delivers a comprehensive exploration of current and emerging approaches to fault diagnosis and failure prognosis of electrical machines and drives. The authors begin with foundational background, describing the physics of failure, the motor and drive designs and components that affect failure and signals, signal processing, and analysis.
The book then moves on to describe the features of these signals and the methods commonly used to extract these features to diagnose the health of a motor or drive, as well as the methods used to identify the state of health and differentiate between possible faults or their severity.
Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives discusses the tools used to recognize trends towards failure and the estimation of remaining useful life. It addresses the relationships between fault diagnosis, failure prognosis, and fault mitigation.
The book also provides:
A thorough introduction to the modes of failure, how early failure precursors manifest themselves in signals, and how features extracted from these signals are processed
A comprehensive exploration of the fault diagnosis, the results of characterization, and how they used to predict the time of failure and the confidence interval associated with it
A focus on medium-sized drives, including induction, permanent magnet AC, reluctance, and new machine and drive types
Perfect for researchers and students who wish to study or practice in the rea of electrical machines and drives, Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives is also an indispensable resource for researchers with a background in signal processing or statistics.
立即查看