Joglekar Industrial Statistics

Practical Methods and Guidance for Improved Performance
1. Auflage 2010
ISBN: 978-0-470-58412-5
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 288 Seiten, E-Book

HELPS YOU FULLY LEVERAGE STATISTICAL METHODS TO IMPROVEINDUSTRIAL PERFORMANCE
Industrial Statistics guides you through ten practicalstatistical methods that have broad applications in many differentindustries for enhancing research, product design, process design,validation, manufacturing, and continuous improvement. As youprogress through the book, you'll discover some valuable methodsthat are currently underutilized in industry as well as othermethods that are often not used correctly.
With twenty-five years of teaching and consulting experience,author Anand Joglekar has helped a diverse group of companiesreduce costs, accelerate product development, and improveoperations through the effective implementation of statisticalmethods. Based on his experience working with both clients andstudents, Dr. Joglekar focuses on real-world problem-solving. Foreach statistical method, the book:
* Presents the most important underlying concepts clearly andsuccinctly
* Minimizes mathematical details that can be delegated to acomputer
* Illustrates applications with numerous practical examples
* Offers a "Questions to Ask" section at the end of each chapterto assist you with implementation
The last chapter consists of 100 practical questions followed bytheir answers. If you're already familiar with statistical methods,you may want to take the test first to determine which methods tofocus on.
By helping readers fully leverage statistical methods to improveindustrial performance, this book becomes an ideal reference andself-study guide for scientists, engineers, managers and othertechnical professionals across a wide range of industries. Inaddition, its clear explanations and examples make it highly suitedas a textbook for undergraduate and graduate courses instatistics.

Autoren/Hrsg.

Joglekar, Anand M.

Inhaltsverzeichnis

PREFACE.
1. BASIC STATISTICS: HOW TO REDUCE FINANCIAL RISK?
1.1. Capital Market Returns.
1.2. Sample Statistics.
1.3. Population Parameters.
1.4. Confidence Intervals and Sample Sizes.
1.5. Correlation.
1.6. Portfolio Optimization.
1.7. Questions to Ask.
2. WHY NOT TO DO THE USUAL t-TEST AND WHAT TO REPLACE ITWITH?
2.1. What is a t-Test and what is Wrong with It?
2.2. Confidence Interval is Better Than a t-Test.
2.3. How Much Data to Collect?
2.4. Reducing Sample Size.
2.5. Paired Comparison.
2.6. Comparing Two Standard Deviations.
2.7. Recommended Design and Analysis Procedure.
2.8. Questions to Ask.
3. DESIGN OF EXPERIMENTS: IS IT NOT GOING TO COST TOO MUCHAND TAKE TOO LONG?
3.1. Why Design Experiments?
3.2. Factorial Designs.
3.3. Success Factors.
3.4. Fractional Factorial Designs.
3.5. Plackett-Burman Designs.
3.6. Applications.
3.7. Optimization Designs.
3.8. Questions to Ask.
4. WHAT IS THE KEY TO DESIGNING ROBUST PRODUCTS ANDPROCESSES?
4.1. The Key to Robustness.
4.2. Robust Design Method.
4.3. Signal-to-Noise Ratios.
4.4. Achieving Additivity.
4.5. Alternate Analysis Procedure.
4.6. Implications for R&D.
4.7. Questions to Ask.
5. SETTING SPECIFICATIONS: ARBITRARY OR IS THERE A METHOD TOIT?
5.1. Understanding Specifications.
5.2. Empirical Approach.
5.3. Functional Approach.
5.4. Minimum Life Cycle Cost Approach.
5.5. Questions to Ask.
6. HOW TO DESIGN PRACTICAL ACCEPTANCE SAMPLING PLANS ANDPROCESS VALIDATION STUDIES?
6.1. Single-Sample Attribute Plans.
6.2. Selecting AQL and RQL.
6.3. Other Acceptance Sampling Plans.
6.4. Designing Validation Studies.
6.5. Questions to Ask.
7. MANAGING AND IMPROVING PROCESSES: HOW TO USE ANAT-A-GLANCE-DISPLAY?
7.1. Statistical Logic of Control Limits.
7.2. Selecting Subgroup Size.
7.3. Selecting Sampling Interval.
7.4. Out-of-Control Rules.
7.5. Process Capability and Performance Indices.
7.6. At-A-Glance-Display.
7.7. Questions to Ask.
8. HOW TO FIND CAUSES OF VARIATION BY JUST LOOKINGSYSTEMATICALLY?
8.1. Manufacturing Application.
8.2. Variance Components Analysis.
8.3. Planning for Quality Improvement.
8.4. Structured Studies.
8.5. Questions to Ask.
9. IS MY MEASUREMENT SYSTEM ACCEPTABLE AND HOW TO DESIGN,VALIDATE, AND IMPROVE IT?
9.1. Acceptance Criteria.
9.2. Designing Cost-Effective Sampling Schemes.
9.3. Designing a Robust Measurement System.
9.4. Measurement System Validation.
9.5. Repeatability and Reproducibility (R&R) Study.
9.6. Questions to Ask.
10. HOW TO USE THEORY EFFECTIVELY?
10.1. Empirical Models.
10.2. Mechanistic Models.
10.3. Mechanistic Model for Coat Weight CV.
10.4. Questions to Ask.
11. QUESTIONS AND ANSWERS.
11.1. Questions.
11.2. Answers.
APPENDIX: TABLES.
REFERENCES.
INDEX.

Über Autor(innen)

ANAND M. JOGLEKAR, PhD, is a leading statistics educator and consultant. In 1990, Dr. Joglekar founded Joglekar Associates, a firm dedicated to helping industrial organizations reach their goals through the effective implementation of statistical methods. He has taught statistical methods to thousands of industry participants through in-house seminars and seminars sponsored by associations such as the LifeScience Alley®, Institute of Food Technologists, and American Association of Cereal Chemists. Among his many publications, Dr. Joglekar is the author of Statistical Methods for Six Sigma in R&D and Manufacturing (also from Wiley).