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Statistics for process control engineers: a practical approach/ Myke king

By: Material type: TextTextPublication details: New Jersey: John Wiley & Sons, 2017Description: xvii, 600 pages: charts, diagrams, tables; 25 cmISBN:
  • 9781119383505
Subject(s): DDC classification:
  • 23rd SB:620.00920115 K52
Contents:
The basics -- Application to process control -- Process examples -- Characteristics of data -- Probability density function -- Presenting the data -- Sample size -- Significance testing -- Fitting a distribution -- Distribution of dependent variables -- Commonly used functions -- Selected distributions -- Extreme vaiue analysis -- Hazard function -- CUSUM -- Regression analysis -- Autocorrelation -- Data reconciliation -- Fourier transform -- Catalogue of distributions -- Normal distribution -- Burr distribution -- Logistic distribution -- Pareto distribution -- Stoppa distribution -- Johnson distribution -- Pearson distribution -- Exponential distribution -- Weibull distribution -- Chi distribution -- Gamma distribution -- Symmetrical distributions -- Asymmetrical distribitions -- Amoroso -- Binomial distribution -- Binomial distribution -- Other discrete distributions
Summary: 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 simple-to-use 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. 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.
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Includes bibliography and index

The basics -- Application to process control -- Process examples -- Characteristics of data -- Probability density function -- Presenting the data -- Sample size -- Significance testing -- Fitting a distribution -- Distribution of dependent variables -- Commonly used functions -- Selected distributions -- Extreme vaiue analysis -- Hazard function -- CUSUM -- Regression analysis -- Autocorrelation -- Data reconciliation -- Fourier transform -- Catalogue of distributions -- Normal distribution -- Burr distribution -- Logistic distribution -- Pareto distribution -- Stoppa distribution -- Johnson distribution -- Pearson distribution -- Exponential distribution -- Weibull distribution -- Chi distribution -- Gamma distribution -- Symmetrical distributions -- Asymmetrical distribitions -- Amoroso -- Binomial distribution -- Binomial distribution -- Other discrete distributions

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 simple-to-use 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. 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.

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