• Part One: Context is the Beginning of Improvement

Chapter Two Visualize Your Process

2.1 Brainstorming
2.2 Flowcharts
2.3 Constructing Flowcharts
2.4 Deployment Flowcharts
2.5 PERT Diagrams
2.5 Do People Really Do This Stuff?
2.6 Processes and Systems
2.7 Cause-and-Effect Diagrams

Chapter Three Visualize Your Data

3.1 Running Records
3.2 Bar Charts
3.3 Pareto Charts
3.4 Histograms and Stem-and-Leaf Plots
3.5 Summary of Bar Charts and Running Records
3.6 Pie Charts

Chapter Four Graphical Purgatory

4.1 Computer-Generated Bar Charts
4.2 Computer-Generated Running Records
4.3 Stacked Bars and Linear Pie Charts
4.4 Radar Plots
4.5 Improving the Two Best Computer Graphs of Table 4.1
4.6 Summary

Chapter Five Some Arithmetic

5.1 Measures of Location
5.2 Measures of Dispersion
5.3 Ratios, Percentages, and Proportions
5.4 How Many Digits Do You Need?
5.5 Comparing Apples and Orange

Chapter Six Visualize Your Process Behavior

6.1 Two Types of Variation
6.2 Two Types of Action
6.3 The Basic Process Behavior Chart: the XmR Chart
6.4 An XmR Chart for Accounts Receivable
6.5 What Do Predictable Processes Look Like?
6.6 Strong Signals and Weaker Signals
6.7 Why Johnnie Can't Breathe
6.8 Plans, Goals, Targets, and Process Behavior Charts
6.9 Exercises

Chapter Seven Using XmR Charts Effectively

7.1 Comparing Groups Using Process Behavior Charts
7.2 The "Has a Change Occurred?" Chart
7.3 Why Susie Can Breathe
7.4 What Kind of Data Belongs on an XmR Chart
7.5 Another Way to Compute Limits for the XmR Chart
7.6 Charting Profits and Losses
7.7 How Do You Use These Charts for Continual Improvement?
7.8 Exercises

Chapter Eight What Makes the XmR Chart Work?

8.1 The Logic Behind Process Behavior Charts
8.3 Why Three-Sigma Limits?
8.2 Where Does the Value of 2.66 Come From?
8.4 But How Can We Get Good Limits From Bad Data?
8.5 So Which Way Should You Compute Limits?
8.6 Chunky Data
8.7 Exercises

Chapter Nine Avoiding Man-Made Chaos

9.1 Creating Man-Made Chaos
9.2 Description Is Not Analysis
9.3 Charts for Each Region
9.4 So What If We Combined All Six Regions?
9.5 Avoiding Man-Made Chaos
9.6 Exercises

Chapter Ten Charts for Count Data

10.1 Counts and Measurements
10.2 Areas of Opportunity
10.3 Collecting Good Count Data
10.4 Charts for Counts
10.5 Charts for Rates Based on Counts
10.6 Some Cautions About Ratios Involving Counts
10.7 Summary
10.8 Exercises

Chapter Eleven Traditional Charts for Count Data

11.1 Charts for Binomial Counts: the up-Chart
11.2 Charts for Binomial Proportions: thep-Chart
11.3 Charts for Poisson Counts: the c-Chart
11.4 Charts for Poisson Rates: then-Chart
11.5 So How Should You Chart Count Data?
11.6 XmR Charts for Chunky Ratios
11.7 Process Behavior Charts for Rare Events
11.8 Summary

Chapter Twelve Average and Range Charts

12.1 Shewhart's Average and Range Charts
12.2 What Average Charts Do Best
12.3 When Does It Make Sense to Use Subgroups?
12.4 Daily Department Store Sales
12.5 Regional Sales by Quarter
12.6 More on Peak Flow Rates
12.7 Administrative Average and Range Charts
12.8 Exercises

Chapter Thirteen Seasonal Data

13.1 Moving Averages
13.2 Year-to-Date Plots
13.3 The Problem of Seasonal Effects
13.4 Deseasonalized Values
13.5 Finding Seasonal Factors
13.6 Not All Data Show Strong Seasonality
13.7 The Appliance Store Data
13.8 The Claims Per Day Data
13.9 Working with Seasonal Data
13.10 Exercises

Chapter Fourteen Collecting Good Data

14.1 What Are You Trying to Do?
14.2 Operational Definitions
14.3 Counts and Categories
14.4 The Problems of Aggregation
14.5 Ratios of Aggregated Measures

Chapter Fifteen The Learning Way

15.1 Mail Order Improvement
15.2 Plan, Do, Study, Act
15.3 "Let's Reduce Losses on Beer and Sake Sales"
15.4 What Should You Do Now?

 

SPS Press, Inc. 1998г