Industrial Statistics with Minitab E-Book

Pere Grima Cintas

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 244

Veröffentlichungsjahr: 2012

Beschreibung

Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented.

Industrial Statistics with MINITAB:

• Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.
• Explores statistical techniques and how they can be used effectively with the help of MINITAB 16.
• Contains extensive illustrative examples and case studies throughout and assumes no previous statistical knowledge.
• Emphasises data graphics and visualization, and the most used industrial statistical tools, such as Statistical Process Control and Design of Experiments.
• Is supported by an accompanying website featuring case studies and the corresponding datasets.

Six Sigma Green Belts and Black Belts will find explanations and examples of the most relevant techniques in DMAIC projects. The book can also be used as quick reference enabling the reader to be confident enough to explore other MINITAB capabilities.

Leseprobe

Contents

Cover

Title Page

Copyright

Preface

Part One: Introduction And Graphical Techniques

Chapter 1: A First Look

1.1 Initial Screen

1.2 Entering Data

1.3 Saving Data: Worksheets and Projects

1.4 Data Operations: An Introduction

1.5 Deleting and Inserting Columns and Rows

1.6 First Statistical Analyses

1.7 Getting Help

1.8 Personal Configuration

1.9 Assistant

1.10 Any Difficulties?

Chapter 2: Graphics for Univariate Data

2.1 File ‘PULSE’

2.2 Histograms

2.3 Changing the Appearance of Histograms

2.4 Histograms for Various Data Sets

2.5 Dotplots

2.6 Boxplots

2.7 Bar Diagrams

2.8 Pie Charts

2.9 Updating Graphs Automatically

2.10 Adding Text or Figures to a Graph

Chapter 3: Pareto Charts and Cause–Effect Diagrams

3.1 File ‘DETERGENT’

3.2 Pareto Charts

3.3 Cause-and-Effect Diagrams

Chapter 4: Scatterplots

4.1 File ‘Pulse’

4.2 Stratification

4.3 Identifying Points on a Graph

4.4 Using the ‘Crosshairs’ Option

4.5 Scatterplots with Panels

4.6 Scatterplots with Marginal Graphs

4.7 Creating an Array of Scatterplots

Chapter 5: Three Dimensional Plots

5.1 3D Scatterplots

5.2 3D Surface Plots

5.3 Contour Plots

Chapter 6: Part One: Case Studies

6.1 Cork

6.2 Copper

6.3 Bread

6.4 Humidity

Part Two: Hypothesis Testing. Comparison Of Treatments

Chapter 7: Random Numbers and Numbers Following a Pattern

7.1 Introducing Values Following a Pattern

7.2 Sampling Random Data from a Column

7.3 Random Number Generation

7.4 Example: Solving a Problem Using Random Numbers

Chapter 8: Computing Probabilities

8.1 Probability Distributions

8.2 Option ‘Probability Density’ or ‘Probability’

8.3 Option ‘Cumulative Probability’

8.4 Option ‘Inverse Cumulative Probability’

8.5 Viewing the Shape of the Distributions

8.6 Equivalence between Sigmas of the Process and Defects per Million Parts Using ‘Cumulative Probability’

Chapter 9: Hypothesis Testing for Means and Proportions. Normality Test

9.1 Hypothesis Testing for One Mean

9.2 Hypothesis Testing and Confidence Interval for a Proportion

9.3 Normality Test

Chapter 10: Comparison of Two Means, Two Variances or Two Proportions

10.1 Comparison of Two Means

10.2 Comparison of Two Variances

10.3 Comparison of Two Proportions

Chapter 11: Comparison of More than Two Means: Analysis of Variance

11.1 ANOVA (Analysis of Variance)

11.2 ANOVA with a Single Factor

11.3 ANOVA with Two Factors

11.4 Test for Homogeneity of Variances

Chapter 12: Part Two: Case Studies

12.1 Welding

12.2 Rivets

12.3 Almonds

12.4 Arrow

12.5 U Piece

12.6 Pores

Part Three: Measurement Systems Studies And Capability Studies

Chapter 13: Measurement System Study

13.1 Crossed Designs and Nested Designs

13.2 File ‘RR_CROSSED’

13.3 Graphical Analysis

13.4 R&R Study for the Data in File ‘RR_CROSSED’

13.5 File ‘RR_NESTED’

13.6 Gage R&R Study for the Data in File ‘RR_NESTED’

13.7 File ‘GAGELIN’

13.8 Calibration and Linearity Study of the Measurement System

Chapter 14: Capability Studies

14.1 Capability Analysis: Available Options

14.2 File ‘VITA_C’

14.3 Capability Analysis (Normal Distribution)

14.4 Interpreting the Obtained Information

14.5 Customizing the Study

14.6 ‘Within’ Variability and ‘Overall’ Variability

14.7 Capability Study when the Sample Size Is Equal to One

14.8 A More Detailed Data Analysis (Capability Sixpack)

Chapter 15: Capability Studies for Attributes

15.1 File ‘BANK’

15.2 Capability Study for Variables that Follow a Binomial Distribution

15.3 File ‘OVEN_PAINTED’

15.4 Capability Study for Variables that Follow a Poisson Distribution

Chapter 16: Part Three: Case Studies

16.1 Diameter_measure

16.2 Diameter_capability_1

16.3 Diameter_capability_2

16.4 Web_visits

Part Four: Multi-Vari Charts And Statistical Process Control

Chapter 17: Multi-Vari Charts

17.1 File ‘MUFFIN’

17.2 Multi-Vari Chart with Three Sources of Variation

17.3 Multi-Vari Chart with Four Sources of Variation

Chapter 18: Control Charts I: Individual Observations

18.1 File ‘CHLORINE’

18.2 Graph of Individual Observations

18.3 Customizing the Graph

18.4 I Chart Options

18.5 Graphs of Moving Ranges

18.6 Graph of Individual Observations – Moving Ranges

Chapter 19: Control Charts II: Means and Ranges

19.1 File ‘VITA_C’

19.2 Means Chart

19.3 Graphs of Ranges and Standard Deviations

19.4 Graphs of Means-Ranges

19.5 Some Ideas on How to Use Minitab as a Simulator of Processes for Didactic Reasons

Chapter 20: Control Charts for Attributes

20.1 File ‘MOTORS’

20.2 Plotting the Proportion of Defective Units (P)

20.3 File ‘CATHETER’

20.4 Plotting the Number of Defective Units (NP)

20.5 Plotting the Number of Defects per Constant Unit of Measurement (C)

20.6 File ‘FABRIC’

20.7 Plotting the Number of Defects per Variable Unit of Measurement (U)

Chapter 21: Part Four: Case Studies

21.1 Bottles

21.2 Mattresses (1st Part)

21.3 Mattresses (2nd Part)

21.4 Plastic (1st Part)

21.5 Plastic (2nd Part)

Part Five: Regression And Multivariate Analysis

Chapter 22: Correlation and Simple Regression

22.1 Correlation Coefficient

22.2 Simple Regression

22.3 Simple Regression with ‘Fitted Line Plot’

22.4 Simple Regression with ‘Regression’

Chapter 23: Multiple Regression

23.1 File ‘CARS2’

23.2 Exploratory Analysis

23.3 Multiple Regression

23.4 Option Buttons

23.5 Selection of the Best Equation: Best Subsets

23.6 Selection of the Best Equation: Stepwise

Chapter 24: Multivariate Analysis

24.1 File ‘LATIN_AMERICA’

24.2 Principal Components

24.3 Cluster Analysis for Observations

24.4 Cluster Analysis for Variables

24.5 Discriminant Analysis

Chapter 25: Part Five: Case Studies

25.1 Tree

25.2 Power Plant

25.3 Wear

25.4 TV Failure

Part Six: Experimental Design And Reliability

Chapter 26: Factorial Designs: Creation

26.1 Creation of the Design Matrix

26.2 Design Matrix with Data Already in the Worksheet

Chapter 27: Factorial Designs: Analysis

27.1 Calculating the Effects and Determining the Significant Ones

27.2 Interpretation of Results

27.3 A Recap with a Fractional Factorial Design

Chapter 28: Response Surface Methodology

28.1 Matrix Design Creation and Data Collection

28.2 Analysis of the Results

28.3 Contour Plots and Response Surface Plots

Chapter 29: Reliability

29.1 File

29.2 Nonparametric Analysis

29.3 Identification of the Best Model for the Data

29.4 Parametric Analysis

29.5 General Graphical Display of Reliability Data

Chapter 30: Part Six: Case Studies

30.1 Cardigan

30.2 Steering wheel – 1

30.3 Steering Wheel – 2

30.4 Paper Helicopters

30.5 Microorganisms

30.6 Jam

30.7 Photocopies

Appendices

A1 Appendix 1: Answers to Questions that Arise at the Beginning

1. Why do some columns that should contain data appear to be empty?

2. I cannot make any operation with the data contained in a column. What is happening?

3. I saw some instructions in the menus and now there is no way to find them. What is going on?

4. All menu options are inactive. How can I return to a normal situation?

5. I have a column containing numbers, but it appears with a text format. What should I do?

6. I am creating a graph and it is displayed with options that I have not chosen. Why?

7. I have stored a worksheet but I do not know where it is located. What can I do?

8. Why is the Minitab prompt MTB> not displayed in the session window?

A2 Appendix 2: Managing Data

A2.1 Copy Columns with Restrictions (File: ‘PULSE’)

A2.2 Selection of Data when Plotting a Graph

A2.3 Stacking and Unstacking of Columns (File ‘BREAD’)

A2.4 Coding and Sorting Data

A3 Appendix 3: Customization of Minitab

A3.1 Configuration Options

A3.2 Use of Toolbars

A3.3 Add Elements to an Existing Toolbar

A3.4 Create Custom Toolbars

Index

This edition first published 2012 © 2012 John Wiley & Sons, Ltd

Registered officeJohn Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom

Portions of information contained in this publication/book are printed with permission of Minitab Inc. All such material remains the exclusive property and copyright of Minitab Inc. All rights reserved.

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Library of Congress Cataloging-in-Publication Data

Grima Cintas, Pere. Industrial statistics with Minitab / Pere Grima Cintas, Lluis Marco-Almagro, Xavier Tort-Martorell Llabres. p. cm. Includes index. ISBN: 978-0-470-97275-5 (cloth) 1. Industrial statistics. 2. Industrial management–Statistical methods–Computer programs. 3. Statistics–Computer programs. 4. Minitab. I. Marco-Almagro, Lluis. II. Tort-Martorell Llabres, Xavier. III. Title. HB137.G72 2012 005.5′5–dc23 2012016129

A catalogue record for this book is available from the British Library.

ISBN: 978-0-470-97275-5

Preface

This book is aimed at students and professionals wishing to use Minitab® Statistical Software as a tool for performing statistical analysis. The content is full of examples and applications around quality control and improvement situations, but we believe that it can be equally useful to people working in other areas who need to analyze data, especially in industrial environments.

Let us start by saying that Minitab includes a very good help facility that allows an easy and quick topic location and that they are, almost always, presented in a clear and concrete way and with good examples. Therefore, the aim of the book is different: it is to provide guidance in the use of Minitab for solving statistical problems as well as in solving problems using statistics and Minitab. Our contribution lies in the selection of materials, the structure and order in which they are presented, and a very visual way of presenting them that facilitates understanding the way to do things without reading long paragraphs. In addition the selection of examples and case studies cover a wide range of common industrial situations.

The book is divided into six parts corresponding to six groups of more or less homogeneous topics and three appendices. Each part consists of several chapters explaining how to solve particular situations – how to use a particular statistical technique – using Minitab, and closes with one last chapter dedicated to case studies. We have kept the chapters on how to use Minitab short and specific. Their content is reflected in the chapter titles, and they go straight to the point. All procedures are explained through examples, and a good way to learn is to try to reproduce them. Hints and tips to facilitate tasks or attention calls to avoid errors are highlighted and identified using icons. In the case study chapters the protagonist is the problem they present and Minitab is just the tool that helps to solve them. Naturally, not all options or techniques are discussed, but only those we consider most useful, commonly used or that serve to give an overview of more complex issues. As said before, Minitab has a first-rate help facility incorporated so that readers can explore other options by themselves. Once the reader is familiar with the first chapters, he is ready to explore other technical skills or options of personal interest.

The book is based on a previous Spanish version that has been improved – thanks to the feedback gathered – and adapted to Minitab 16. It is a compilation of our experience of many years’ teaching industrial statistics to undergraduate and graduate engineering and statistics students at Universitat Politècnica de Catalunya-Barcelona Tech; as well as experience gathered by training more that 600 Six Sigma Black Belts from different corporations. Our work as consultants in industrial statistics and quality improvement projects has formed the basis of deciding the content and has provided the basic material for many of the examples and cases presented. The data corresponding to examples and case studies presented are available on the publisher's website www.wiley.com/go/industrial_statistics_with_minitab.

We wish to express our thanks to our fellows at UPC: Josep Ginebra, Jan Graffelman, Alexandre Riba, Lourdes Rodero, Ignasi Solé and Moises Valls, without a doubt our best source of information; to Sandrine Santiago, ex-student and manager of CALETEC consultants, for her brilliant contributions; to our friend Guillermo de León, Professor at Universidad Veracruzana (Mexico), for many useful suggestions that have improved the clarity of many issues and to Lesly Acosta, PhD student and Assistant Professor at UPC, who has done a tremendous job translating from Spanish to English and providing valuable ideas. And finally, a special gratitude to Shubham Dixit from Aptara India for an excellent job correcting the manuscript.

Finally, we would be grateful if you let us know your comments and suggestions.

Pere Grima Cintas, Lluís Marco-Almagroand Xavier Tort-Martorell LlabrésBarcelona