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Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements

by: Harry, Mikel J.; Mann, Prem S.; De Hodgins, Ofelia C.; Hulbert, Richard L.; Lacke, Christopher J.

Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements

by: Harry, Mikel J.; Mann, Prem S.; De Hodgins, Ofelia C.; Hulbert, Richard L.; Lacke, Christopher J.

ISBN 13:
9780470114940
ISBN 10:
0470114940
Edition: 1st
Format: Hardcover
Copyright: 01/19/2010
Publisher: Wiley

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Summary

The only textbook of its kind, this authoritative account provides a balanced approach to quantitative and qualitative statistics using the Six Sigma and Lean Sigma methodologies. The emphasis is on applications and the implementation of data analyses as they relate to Six Sigma. The primary purpose of the book is to serve as a reference guide and textbook for both experienced practitioners and new students of Six Sigma. The book includes plentiful examples, exercises, and case studies based on real data and real-life analytical and business problems. It is written by a broad spectrum of academic and industry professionals.

Principles of Six Sigma
Overview
Six Sigma Essentials
Quality Definition
Value Creation
Business, Operations, Process and Individual BOPI Goals
Underpinning Economics
Performance Metrics
Process
Design Complexity
Nature and Purpose of Six Sigma
Needs That Underlie Six Sigma
Why Focusing on The Customer is Essential To Six Sigma
Success Factors
Software applications
References
Glossary
Six Sigma Installation
Overview
Six Sigma Leadership - The Fuel of Six Sigma
Deployment Planning
Applications Projects
Deployment Timeline
Design for Six Sigma [DFSS] Principles
Processing for Six Sigma [PFSS] Principles
Managing for Six Sigma [MPSS] Principles
Project Review
Summary
References
Glossary
Lean Six Sigma Projects
Overview
Introduction
Project Description
Project Guidelines (General)
Project Selection
Project Scope
Project Leadership
Project Teams
Project Financials
Project Management
Project Payback
Project Milestones
Project Roadmap
Project Charters (General)
Six Sigma Projects
Project Summary
References
Glossary
Lean Practices
Overview
Introduction
The Idea of Lean Thinking
Theory of Constraints [TOC]
Lean Concept
Definition of Value Added Activities and Non Value Added Activities
Why Companies Think Lean
Visual Controls - Visual Factory
The Idea of Pull - Kanban
5S - 6S System
The Idea of Perfection - Kaizen
Replicate - Translate
PokaYoke System - Mistake Proofing
SMED System
7W + 1 Approach - Seven + one Deadly Waste(s)
6M Approach
Summary
References
Glossary
Value Stream Mapping
Overview
Introduction
Value Stream Mapping
Focused Brainstorming
Graphical representation of a Process in a Value Stream Map
Effective Working Time
Customer Demand
Takt Time
Pitch Time
Queuing Time
Cycle Time
Total Cycle Time
Calculation of Total Lead Time(s)
Value Added Percentage and Six Sigma Level
Drawing the Current Value Stream Map
Drawing the Value Stream Map?
What Makes a Value Stream Lean?
The Future Value Stream Map
Summary
References
Glossary
Introductory Statistics and Data
Overview
Introduction
Genetic Code of Statistics
Population and Samples
The Idea of Data
Nature of Data
Data Collection
The Importance of Data Collection
Sampling in Six sigma
Sources of Data
Database
Chapter Summary
References
Glossary
Quality Tools
Overview
Introduction
Nature of Six Sigma Variables
Quality Function Deployment (QFD)
Scales of Measurement
Diagnostic Tools
Analytical Methods
Graphical Tools
Graphical Representation of a Process
SIPOC Diagram
IPO Diagram - General Model of a Process System
Force Field Analysis
Matrix Analysis - The Importance of Statistical Thinking
Check Sheets
Score Cards
Affinity Diagram
Concept Integration
Reference
Glossary
Making Sense of Data in Six Sigma and Lean
Overview
Summarizing Quantitative Data: Graphical Methods
Summarizing Quantitative Data: Numerical Methods
Organizing and Graphing Qualitative Data
Summarizing Bivariate Data
Glossary
Fundamentals of Capability and Rolled Throughput Yield
Overview
Introduction
Why Capability
Six Sigma Capability Metric
Discrete Capability
Continuous Capability - Example
Fundamentals of Capability
Short versus Long Term Capability
Capability and Performance
Indices of Capability
Shift - Calibrating the Shift
Applying the 1.5Concept
Yield
Hidden Factory
Glossary
References
Probability
Overview
Experiments, Outcomes, and Sample Space
Calculating Probability
Combinatorial Probability
Marginal and Conditional Probabilities
Union of Events
Intersection of Events
Glossary
Discrete Random Variables and Their Probability Distributions
Overview
Six Sigma Performance Variables
Six Sigma Leverage Variables
Random Variable
Probability Distributions of a Discrete Random Variable
Mean of a Random Variable
Standard Deviation of a Discrete Random Variable
The Binomial Distribution
The Poisson Probability Distribution
The Geometrical Distribution
The Hypergeometric Probability Distribution
Glossary
Continuous Random Variables and Their Distributions
Overview
Continuous Probability Distributions
The Normal Distribution
The Exponential Distribution
Glossary
Sampling Distributions
Overview
Sampling Distribution of a Sample Mean
Sampling Distribution of a Sample Proportion
The Central Limit Theorem
Glossary
Single Population Estimation
Overview
What Does a Confidence Interval Mean?
Estimating a Population Mean
Estimating a Population Proportion
Estimating a Population Variance
Glossary
Control Methods
Overview
Introduction
Control Logic
Statistical Control Systems
Statistical Control
Prevention VS Detection
What is a Process Control System?
Variation
Process Out-of-Control
Fundamentals of Process Control
Continuous Statistical Process Control (SPC) Tools
Interpreting Process Control
Statistical Process Control and Statistical Process Monitoring
The Foundation of Statistical Process Control (SPC)
Tools for Process Controls - Control Charts
Control Limits
Process Out-of-Control
Western Electric Rules
Why Control Charts and How are These Used
Pre-Control Method
Control Charts for Variables
Control Chart for Attributes
Glossary
References
Single Population Hypothesis Tests
Overview
Introduction to Hypothesis Testing
Testing a Claim About a Population Mean
Hypothesis Test About a Population Proportion
Glossary
Estimation and Hypothesis Tests: Two Populations
Overview
Inferences About the Differences Between Two Population Means for Independent Samples
Inferences About the Differences Between Two Population Means for Paired Samples
Inferences About the Differences Between Two Population Proportions
Glossary
Chi-Square Tests
Overview
A Goodness-of-Fit Test
Contingency Tables
Tests of Independence and Homogeneity
Glossary
Analysis of Variance
Overview
The F- Distribution
One-Way Analysis of Variance
One-Way Analysis of Variance
Pairwise Comparisons
Multi-Factor Analysis of Variance
What Do We Do When the Assumptions Are Unreasonable?
Glossary
Linear and Multiple Regression
Overview
Simple Regression Model
Linear Regression
Coefficient of Determination and Correlation
Multiple Regression
Regression Analysis
Using the Regression Model
Residual Analysis
Cautions in Using Regression
Glossary
Measurement Analysis
Overview
Introduction
Measurement
Measurement Error
Accuracy and Precision
Measurement System as a Process
Categories of Measurement Error Which Affect the Location
Categories of Measurement Which Affect the Spread
Gage-Accuracy and Precision
Exploring Linearity Error
Gage R & R [Repeatability & Reproducibility]
Gage R&R - Variable
Gage R&R - Crossed
Attribute Gage R & R Study
ANOVA Method versus R Method
ANOVA/Variance Component Analysis
Rules of Thumb
Acceptability Criteria
Chapter Review
References
Glossary
Fundamentals of Design of Experiments
Overview
Introduction
What is Design of Experiments (DOE)?
Role of Experimental Design in Process Improvement
Experiment Design Tools
Principles of an Experimental Design
Different Types of Experiments
Introduction to Factorial Designs
Features of Factorial Designs - Orthogonality
Full Factorial Designs
Residual Analysis 22
Modeling 22
Multi-Factor Experiment
Fractional Factorial Designs
The ANOVA Table
Normal Probability Plot of the Effects
Main Effects Plot
Blocking Variable
Statistically Significant
Practically Significant
Fundamentals of Residual Analysis
Center Points
Noise Factors
Strategy of Good Experimentation
Selecting the Variable Levels
Selecting the Experimental Design
Replication
Analyzing the data [ANOVA]
Recommendations
Achieving the Objective
Chapter Summary
Chapter Example
References
Glossary
Design for Six Sigma [DFSS], Simulation, and Optimization
Overview
Introduction
Six Sigma as Stretch Target
Producibility
Statistical Tolerances
Design Application
Design Margin
Design Qualification
Design for Six Sigma (DFSS) Principles
Decision Power
Experimentation
Experiment Design
Response Surface Designs
Factorial Producibility
Toolbox Overview
Monte Carlo Simulations
Design for Six Sigma Project Selection Example
Defining Simulation Inputs
Defining Outputs and Running a Simulation
Stochastic Optimization: Discovering the Best Portfolio with the Least Risk
Conclusions
References
Glossary
Survey Methods and Sampling Techniques
Overview
The Sample Survey
The Survey System
Clear Goals
Target Population and Sample Size
Interviewing Method
Response Rate, Respondents and Non-respondents
Survey Methods
Sources of Information and Data
The Order of the Questions
Pilot Test the Questionnaire
Biased Sample or Response Error
Sampling - Random and Non-Random Sample
Population Distribution
Sampling Distribution
Sampling and Non-sampling Errors
References
Glossary
Statistical Tables
Table of Binomial Probabilities
Standard Normal Distribution Table
The t Distribution Table
Chi-Square Distribution Table
The F Distribution Table
Critical Values for the Mann-Whitney Test
Critical Values for the Wilcoxon Signed-Rank Test
Sigma Conversion Table
Answers to Selected Odd-Numbered Exercises
Index
Table of Contents provided by Publisher. All Rights Reserved.

Amazon no longer offers textbook rentals. We do!

Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements

Practitioner's Guide to Statistics and Lean Six Sigma for Process Improvements

9780470114940

0470114940

Summary

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Table of Contents

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