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    Process Improvement Using Six Sigma: A DMAIC Guide
    Process Improvement Using Six Sigma: A DMAIC Guide
    Process Improvement Using Six Sigma: A DMAIC Guide
    Ebook142 pages1 hour

    Process Improvement Using Six Sigma: A DMAIC Guide

    By Rama Shankar

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    About this ebook

    In order to stay competitive, organizations need to continuously improve their processes. The purpose of this book is to provide the practitioner with the necessary tools and techniques with which to implement a systematic approach to process improvement initiatives using the Six Sigma methodology.

    While there are many self-help books out there, here the topics are discussed in a way so as to remove the fear out of Six Sigma and statistics. This guide takes readers through the five phases of the Six Sigma methodology, Define-Measure-Analyze-Improve-Control (DMAIC), in five clearly written and easy-to-understand sections. You learn each phase’s purpose and what activities to perform in each. Numerous examples are included throughout and all statistics are described to the exact level of understanding necessary. Each of the five sections then concludes with a checklist to ensure that all of the phase’s activities have been completed.

    Following the systematic approach outlined in this book will ensure that customer needs and functional area needs are understood and met; knowledge of subject matter experts (SMEs) and team members to improve the process is leveraged; team consensus is reached on the root cause(s) for problems; and risk is managed by addressing all compliance issues.

    Author Webinar Series:
    "https://asq.webex.com/asq/lsr.php?RCID=57f5326bc0d05d791507f1b6ad92f99d" as the author provides a thorough introduction to this book and its key deliverables.
    LanguageEnglish
    PublisherASQ Quality Press
    Release dateNov 10, 2008
    ISBN9780873891332
    Process Improvement Using Six Sigma: A DMAIC Guide
    Author

    Rama Shankar

    Rama Shankar is an adjunct professor at the Illinois Institute of Technology, Daley College Chicago, and Great Lakes Institute of Management, India.

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      Book preview

      Process Improvement Using Six Sigma - Rama Shankar

      Process Improvement Using Six Sigma

      A DMAIC Guide

      Rama Shankar

      ASQ Quality Press

      Milwaukee, Wisconsin

      American Society for Quality, Quality Press, Milwaukee 53203

      © 2009 by ASQ

      All rights reserved. Published 2009

      Library of Congress Cataloging-in-Publication Data

      Shankar, Rama, 1956– 

      Process improvement using Six Sigma : a DMAIC guide / Rama Shankar.

      p. cm.

      Includes index.

      ISBN 978-0-87389-752-5 (soft cover : alk. paper)

      1. Six sigma (Quality control standard) 2. Total quality management. 3. Process control. 4. Reengineering (Management) I. Title.

      HD62.15.S477 2009

      658.4'013—dc22 2008052670

      ISBN: 978-0-87389-752-5

      No part of this book may be reproduced in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher.

      Publisher: William A. Tony

      Acquisitions Editor: Matt T. Meinholz

      Project Editor: Paul O’Mara

      Production Administrator: Randall Benson

      ASQ Mission: The American Society for Quality advances individual, organizational, and community excellence worldwide through learning, quality improvement, and knowledge exchange.

      Attention Bookstores, Wholesalers, Schools, and Corporations: ASQ Quality Press books, videotapes, audiotapes, and software are available at quantity discounts with bulk purchases for business, educational, or instructional use. For information, please contact ASQ Quality Press at 800-248-1946, or write to ASQ Quality Press, P.O. Box 3005, Milwaukee, WI 53201-3005.

      To place orders or to request a free copy of the ASQ Quality Press Publications Catalog, including ASQ membership information, call 800-248-1946. Visit our Web site at www.asq.org or http://www.asq.org/quality-press.

      Quality Press

      Call toll free 800-248-1946

      Fax 414-272-1734

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      E-mail: [email protected]

      600 N. Plankinton Avenue

      Milwaukee, Wisconsin 53203

      Om

      to

      My guru

      My mother

      My family

      Table of Contents

      List of Figures and Tables

      Read Me First

      Acronym List

      Introduction

      I. Define

      Purpose of Define Phase

      How Do You Identify Projects for Improvement?

      How Do You Pick a Project?

      How Do You Scope Your Project? The SIPOC Diagram

      Assemble the Process Improvement Team

      Create a Project Authorization/Charter Document

      End of Define Phase

      II. Measure

      Purpose of Measure Phase

      Develop an Understanding of Your Process—Creating Process Maps

      Risk Management Plan FMEA

      Calculating Process Sigma for Your Process—Process Capability

      Calculating Process Sigma (Z) or Process Capability (Cp and Cpk) for Variable Data

      Conducting Gage R&R Studies—Variable Data and Attribute Data

      End of Measure Phase

      III. Analyze

      Purpose of Analyze Phase

      Are Things Improving? Running a Hypothesis Test

      Can You Uncover Any Relationships? Correlation and Regression

      ANOVA (Analysis of Variance)

      End of Analyze Phase

      IV. Improve

      Purpose of Improve Phase

      Investigating Relationships between Input and Output—Running Design of Experiments (DOE)

      End of Improve Phase

      V. Control

      Purpose of Control Phase

      Monitor the Stability of the Process—Statistical Process Control

      Mistake-Proofing/Poka-Yoke

      Technology Transfer—The Control Plan

      Wrap-Up—Updating Essential Documents

      Calculating Project Savings

      Final Report

      End of Control Phase

      List of Figures and Tables

      Figure 1. The process model.

      Figure 2. The DMAIC process.

      Figure 3. Example of multiple levels of Pareto charts.

      Figure 4. SIPOC diagram template.

      Figure 5. SIPOC diagram for going to work in the morning.

      Figure 6. Example of a meeting minutes template.

      Figure 7. Example of a communication plan template.

      Figure 8. Example of a simple charter document template.

      Figure 9. Example of a process map for a stamping process.

      Figure 10. Example of an FMEA.

      Figure 11. Summarizing raw data.

      Figure 12. Histogram for cycle time.

      Table 1. Calculating process sigma—variable data.

      Figure 13. Process capability for terminal length showing percentage overall performance.

      Figure 14. Process capability for terminal length showing PPM overall performance.

      Table 2. Calculating process sigma—attribute and count data.

      Figure 15. Gage R&R graph for inventory retains.

      Figure 16. Minitab output for deflection measurement of electronic parts.

      Figure 17. Results of deflection measurement of electronic parts.

      Figure 18. Appraiser results for bank loan pass/fail study.

      Figure 19. Attribute agreement analysis of bank loan gage R&R study.

      Table 3. Common alpha risk values.

      Figure 20. Results of t-test of tooling cavity dimensions.

      Figure 21. Output of t-test for pharmacy layout.

      Figure 22. Results of t-test for pharmacy layout.

      Figure 23. Output of t-test for document approval process.

      Figure 24. Results of t-test for document approval process.

      Figure 25. Output of correlation/regression test for plastic density versus strength.

      Table 4. Cheat sheets for ANOVA assumptions.

      Figure 26. Main effects plot for ambulance response time.

      Figure 27. Results of ANOVA assumptions test for factors.

      Figure 28. Anderson-Darling normality test for hospital 1.

      Figure 29. Anderson-Darling normality test for hospital 2.

      Figure 30. Anderson-Darling normality test for hospital 3.

      Figure 31. Bartlett’s test for ambulance response times.

      Figure 32. Results of statistical analysis of ambulance response times.

      Figure 33. Output of residual plots for ambulance response times.

      Figure 34. Tukey test results for ambulance response times.

      Figure 35. Main effects plot for two-way ANOVA of ambulance response times.

      Figure 36. Interactions plot for two-way ANOVA of ambulance response times.

      Figure 37. ANOVA table for ambulance response times.

      Table 5. Experimental worksheet and results—gluten dissolution experiment.

      Figure 38. Main effects plot for gluten dissolution experiment.

      Figure 39. Interactions plot for gluten dissolution experiment.

      Figure 40. Cube plot for gluten dissolution experiment.

      Figure 41. Normal probability plot for gluten dissolution experiment at alpha = .10.

      Figure 42. Pareto chart for gluten dissolution experiment at alpha = .10.

      Figure 43. Four-in-one residuals graph for gluten dissolution experiment.

      Table 6. Calculated P value for dissolution time.

      Figure 44. Normal probability plot for gluten dissolution experiment at alpha = .05 with factors A, B, AC, C, and AB.

      Figure 45. Pareto chart for gluten dissolution experiment rerun at alpha = .05 with factors C, A, AC, B, and AB.

      Table 7. Calculated P value for dissolution time at alpha = 0.05.

      Figure 46. Normal probability plot for gluten dissolution experiment at alpha = .05 without interaction term AB.

      Figure 47. Pareto chart for gluten dissolution experiment at alpha = .05 without interaction term AB.

      Table 8. Calculated P value for dissolution time at alpha = 0.05 without interaction term AB.

      Figure 48. Analysis of variance for dissolution time.

      Table 9. Estimated coefficients for dissolution time using data in uncoded units (data for prediction equation from software).

      Figure 49. Response optimizer graph for gluten dissolution experiment.

      Table 10. Experimental worksheet and results—pellet hardness.

      Figure 50. Main effects plot for pellet hardness experiment.

      Figure 51. Interactions plot for pellet hardness experiment.

      Figure 52. Cube plot for pellet hardness experiment.

      Figure 53. Normal probability plot for pellet hardness experiment—alpha = .10.

      Figure 54. Pareto chart for pellet hardness experiment—alpha = .10.

      Figure 55. Four-in-one residuals graph for pellet hardness experiment.

      Table 11. Calculated P value for pellet hardness at alpha = 0.10. .

      Figure 56. Normal probability plot for pellet hardness experiment with alpha = 0.05.

      Figure 57. Pareto chart of effects for pellet hardness experiment with alpha = 0.05.

      Table 12. Calculated P value for pellet hardness at alpha = 0.05 without interaction term ABC and BC.

      Figure 58. Analysis of variance for

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