Book description
The first statistics guide focussing on practical application to process control design and maintenance
Statistics for Process Control Engineers is the only guide to statistics written by and for process control professionals. It takes a wholly practical approach to the subject. Statistics are applied throughout the life of a process control scheme – from assessing its economic benefit, designing inferential properties, identifying dynamic models, monitoring performance and diagnosing faults. This book addresses all of these areas and more.
The book begins with an overview of various statistical applications in the field of process control, followed by discussions of data characteristics, probability functions, data presentation, sample size, significance testing and commonly used mathematical functions. It then shows how to select and fit a distribution to data, before moving on to the application of regression analysis and data reconciliation. The book is extensively illustrated throughout with line drawings, tables and equations, and features numerous worked examples. In addition, two appendices include the data used in the examples and an exhaustive catalogue of statistical distributions. The data and a simpletouse software tool are available for download. The reader can thus reproduce all of the examples and then extend the same statistical techniques to real problems.
 Takes a backtobasics approach with a focus on techniques that have immediate, practical, problemsolving applications for practicing engineers, as well as engineering students
 Shows how to avoid the many common errors made by the industry in applying statistics to process control
 Describes not only the wellknown statistical distributions but also demonstrates the advantages of applying the large number that are less wellknown
 Inspires engineers to identify new applications of statistical techniques to the design and support of control schemes
 Provides a deeper understanding of services and products which control engineers are often tasked with assessing
This book is a valuable professional resource for engineers working in the global process industry and engineering companies, as well as students of engineering. It will be of great interest to those in the oil and gas, chemical, pulp and paper, water purification, pharmaceuticals and power generation industries, as well as for design engineers, instrument engineers and process technical support.
Table of contents
 Cover
 Title Page
 Preface
 About the Author
 Supplementary Material

Part 1: The Basics
 1 Introduction
 2 Application to Process Control
 3 Process Examples
 4 Characteristics of Data

5 Probability Density Function
 5.1 Uniform Distribution
 5.2 Triangular Distribution
 5.3 Normal Distribution
 5.4 Bivariate Normal Distribution
 5.5 Central Limit Theorem
 5.6 Generating a Normal Distribution
 5.7 Quantile Function
 5.8 Location and Scale
 5.9 Mixture Distribution
 5.10 Combined Distribution
 5.11 Compound Distribution
 5.12 Generalised Distribution
 5.13 Inverse Distribution
 5.14 Transformed Distribution
 5.15 Truncated Distribution
 5.16 Rectified Distribution
 5.17 Noncentral Distribution
 5.18 Odds
 5.19 Entropy
 6 Presenting the Data
 7 Sample Size
 8 Significance Testing
 9 Fitting a Distribution
 10 Distribution of Dependent Variables
 11 Commonly Used Functions
 12 Selected Distributions
 13 Extreme Value Analysis
 14 Hazard Function
 15 CUSUM
 16 Regression Analysis
 17 Autocorrelation
 18 Data Reconciliation
 19 Fourier Transform

Part 2: Catalogue of Distributions

20 Normal Distribution
 20.1 Skew‐Normal
 20.2 Gibrat
 20.3 Power Lognormal
 20.4 Logit‐Normal
 20.5 Folded Normal
 20.6 Lévy
 20.7 Inverse Gaussian
 20.8 Generalised Inverse Gaussian
 20.9 Normal Inverse Gaussian
 20.10 Reciprocal Inverse Gaussian
 20.11 Q‐Gaussian
 20.12 Generalised Normal
 20.13 Exponentially Modified Gaussian
 20.14 Moyal
 21 Burr Distribution
 22 Logistic Distribution
 Chapter 23: Pareto Distribution
 24 Stoppa Distribution
 25 Beta Distribution
 26 Johnson Distribution
 27 Pearson Distribution
 28 Exponential Distribution
 29 Weibull Distribution
 30 Chi Distribution
 31 Gamma Distribution
 32 Symmetrical Distributions

33 Asymmetrical Distributions
 33.1 Benini
 33.2 Birnbaum–Saunders
 33.3 Bradford
 33.4 Champernowne
 33.5 Davis
 33.6 Fréchet
 33.7 Gompertz
 33.8 Shifted Gompertz
 33.9 Gompertz–Makeham
 33.10 Gamma‐Gompertz
 33.11 Hyperbolic
 33.12 Asymmetric Laplace
 33.13 Log‐Laplace
 33.14 Lindley
 33.15 Lindley‐Geometric
 33.16 Generalised Lindley
 33.17 Mielke
 33.18 Muth
 33.19 Nakagami
 33.20 Power
 33.21 Two‐Sided Power
 33.22 Exponential Power
 33.23 Rician
 33.24 Topp–Leone
 33.25 Generalised Tukey Lambda
 33.26 Wakeby
 34 Amoroso Distribution
 35 Binomial Distribution
 36 Other Discrete Distributions

20 Normal Distribution
 Appendix 1: Data Used in Examples
 Appendix 2: Summary of Distributions
 References
 Index
 End User License Agreement
Product information
 Title: Statistics for Process Control Engineers
 Author(s):
 Release date: October 2017
 Publisher(s): Wiley
 ISBN: 9781119383505
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