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Written by Engineers for Engineers, This Book Takes the Mystery Out of Statistical Improvement Tools

A Practical Guide to Statistical Quality Improvement:
Opening Up the Statistical Toolbox


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Why do I need this book?
What are the key features of this book?
Who wrote A Practical Guide to Statistical Quality Improvement?
What does the book cost and how can I order it?

Why do I need this book?

A Practical Guide to Statistical Quality Improvement is the only book of its kind intended for engineering use in both manufacturing and service organizations for the development of a systematic approach to continual improvement.  It contains a compilation of special techniques for Statistical Process Control with step-by-step guidance for applying these tools to process improvement.  You won’t be left trying to figure out complicated formulas.  Specific details are given throughout the book on how to use each of the improvement tools presented. 

Key features include:

  • Unique, comprehensive details on measurement systems
  • Special statistical techniques not in common use in manufacturing
  • Guideline for how to make all of the tools most effective by integrating them into a company-wide continuous improvement effort that includes TQM, Customer-Supplier Relationships, PDCA Cycle
  • Coverage of design of experiments that "walks" the reader through experimental strategy and design

Best of all, there are no hieroglyphics!

The Practical Guide to Statistical Quality Improvement is enhanced with numerous illustrations and an extensive appendix.  This working guide will become a well-used reference for chemical, plastics, mechanical, industrial, and biochemical engineers in manufacturing and by safety engineers and related professionals in industry.

About The Authors

Michael R. Beauregard, PE, Director of Technology at Resource Engineering, has over 20 years of experience in engineering and plant management.  His experience is in the development and application of innovative techniques for improving manufacturing operations.  Mike was a member of the Board of Examiners for the Malcolm Baldrige National Quality Award in 1995, 1996, 1997, 1999, and 2000. 

Raymond J. Mikulak, PE, President of Resource Engineering, has more than 30 years of experience as a general manager.  He has led multi-million dollar manufacturing businesses that serve the automotive and electronic industries.  He specializes in developing and implementing innovative manufacturing strategies to increase productivity and improve quality. 

Barbara A. Olson is the Operations Manager at the Molding Materials Division of Rogers Corporation.  She has over 15 years of experience in applying DOE and other statistical techniques to improve processes in the chemical, plastics, electronics, and automotive industries.

All three authors are ASQ Certified Quality Engineers.

Cost, Ordering, and Other Important Information

Hardcover, 469 pages; 6”x9”.  ISBN 0-442-23439-2

List Price $42.95. 

Order on-line

Order Toll-Free:  800-810-8326 or outside of the US and Canada call 802-496-5888

Order by Fax:  802-496-7724


A Practical Guide to Statistical Quality Improvement:
Opening Up the Statistical Toolbox

Contents

Chapter 1

Fundamental concepts of Total Quality Management

  • TQM-How Does It Work?
  • TQM Leaders

  • The Continuous Improvement Cycle

  • Quality-What Is It Anyway?
  • Quality Drives Productivity

  • From Product Control to Process Control

  • SPC-Why and How
  • Improving the Status Quo with Statistical Process Improvement
  • The Kaizen Mine
  • The Engineer as a Change Agent

Chapter 2

The Basic Tools

  • Understanding Variation
  • Clarity with Flowcharts
  • Sampling
  • Data Collection Formats
  • The Power of Concentration Diagrams
  • Data Grouping: Cause and Effect Diagrams
  • Data Organization

  • Data Analysis-Measuring Variation

Chapter 3

The Measurement System

  • The Measurement System as a Process
  • Units of Measure-Are They Adequate?

  • Components of Measurement Error
  • Level of Measurement Error

  • Measurement Consistency

  • Measurement Bias

  • Measuring Testing Variance

  • GR & R Studies
  • For Nondestructive Tests

  • For Destructive Tests

  • Signal to Noise Ratio

Chapter 4

Statistical Process Control

  • Quality Improvement Cycles
  • Process Stability
  • Control Chart Background

  • In Control Versus In Specification

  • Process Capability
  • Control Charts for Variable Data
  • Control Charts for Attribute Data
  • Special Control Charting Techniques
  • Conformance (or Run) Charts and Precontrol Charts
  • CUSUM Charts
  • Process Targeting

Chapter 5

Using the Tools

  • From SPC to SPI
  • Problem-Solving Techniques

  • Experimenting for Improvement
  • Tests of Significance

  • Randomized Designs

  • Factorial Experiments

  • Fractional Factorial Designs

  • Screening Experiments

  • Mixture Design Techniques

  • Response Surface Analysis

  • EVOP

  • Handling Missing Data
  • Preventive Measures

Chapter 6

Applications

  • Customer Service
  • Materials Control
  • Maintenance
  • Marketing and Sales
  • Human Resources (Personnel)
  • Purchasing
  • Quality Department
  • Safety and Environmental
  • Management

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