Matlab® in Quality Assurance Sciences

by Leonid Burstein

Overview

MATLAB® in Quality Assurance Sciences fills a gap in the highly topical field of quality assurance (QA). It is a compact guide for students, engineers, and scientists in this field. It concentrates on MATLAB® fundamentals with examples of application to a wide range of current problems from general, nano and bio-technology, and statistical control, to medicine and industrial management. Examples cover both the school and advanced level; comprising calculations of total quality management, six sigma, time series, process improvement, metrology, quality control, human factors in quality assurance, measurement and testing techniques, quality project and function management, and customer satisfaction.

This book covers key topics, including: the basics of software with examples; graphics and representations; numerical computation, scripts and functions for QA calculations; ODE and PDEPE solvers applied to QA problems; curve fitting and time series tool interfaces in calculations of quality; and statistics calculations applied to quality testing.

• Includes MATLAB® fundamentals, matrices, arrays, general graphics and specialized plots in quality assurance problems, script files, ordinary and partial differential equations
• Gives calculation of six sigma, total quality management, time series forecasting, reliability, process improvement, metrology, quality control and assurance, measurement and testing techniques
• Provides tools for graphical presentation, basic and special statistics and testing, ordinary and partial differential solvers, and fitting tools

Product Details

ISBN-13:	9780857094889
Publisher:	Elsevier Science
Publication date:	02/12/2015
Sold by:	Barnes & Noble
Format:	eBook
Pages:	264
File size:	13 MB
Note:	This product may take a few minutes to download.

About the Author

Dr Leonid Burstein is a staff member of Kinneret Academic College (Quality Assurance Department), before that he taught at the Technion -IIT, at ORT Braude College, and at several other academic institution in Western and Lower Galilee, in Israel. His scientific work has been reported in more than 50 publications in leading scientific journals. He is author and contributor of published textbooks, monographs, and an Editorial Board member and reviewer for several international scientific journals.

Table of Contents

• Dedication
• List of figures and tables
• Preface
• About the author
• 1: Introduction
  • Abstract
  • MATLAB® and other software
  • The purpose and principal audience for this book
  • About the topics
  • About chapter design and questions for self-checking
  • The MATLAB® versions
  • Order of presentation
• 2: Basics
  • Abstract
  • 2.1 Starting with MATLAB® software
  • 2.2 Vectors, matrices, and arrays
  • 2.3 Flow control
  • 2.4 Questions for self-checking
  • 2.5 Answers to selected questions
• 3: MATLAB® graphics
  • Abstract
  • 3.1 Generation of XY plots
  • 3.2 Generation of XYZ plots
  • 3.3 Specialized two- and three-dimensional plots
  • 3.4 Application examples
  • 3.5 Questions for self-checking
  • 3.6 Answers to selected questions
• 4: Commands for probability distributions, random numbers, and special graphs
  • Abstract
  • 4.1 Density, cumulative, and inverse cumulative functions for probability distributions
  • 4.2 Command for random number generation
  • 4.3 Supplementary commands for random numbers and probability distributions
  • 4.4 Application examples
  • 4.5 Specialized commands for graphical representation
  • 4.6 Application examples
  • 4.7 Questions for self-checking
  • 4.8 Answers to selected questions
• 5: Script, function files, and some useful MATLAB® functions
  • Abstract
  • 5.1 Script file
  • 5.2 Functions and function files
  • 5.3 Some useful MATLAB® functions
  • 5.4 Application examples
  • 5.5 Questions for self-checking
  • 5.6 Answers to selected questions
• 6: Hypothesis tests
  • Abstract
  • 6.1 Hypothesis testing outlines
  • 6.2 The t-test with the ttest command
  • 6.3 Wilcoxon rank sum test
  • 6.4 Sample size and power of test
  • 6.5 Supplementary commands for the hypothesis tests
  • 6.6 Application examples
  • 6.7 Questions for self-checking
  • 6.8 Answers to selected questions
• 7: Ordinary differential equations and tools for their solution
  • Abstract
  • 7.1 The ODE solvers for solving ordinary differential equations
  • 7.2 Numerical methods and the ODE solvers
  • 7.3 The ODE solver command forms and steps for their solution
  • 7.4 Additional forms of the ODE solver commands
  • 7.5 Application examples
  • 7.6 Questions for self-checking
  • 7.7 Answers to selected questions
• Appendix: MATLAB® characters, operators, and commands
• Index

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From the Publisher

Fills a gap in the highly topical field of quality assurance (QA)