Power of Statistical Thinking, The: Improving Industrial Processes

Process Definition. Statistical Techniques for Process Study. Managing Processes Within an Organizational Context. The Impact of Variation on Achieving Process Objectives. The Scientific Method and Process Management.

Use of Flowcharts for Describing Process Operations. Planning for Data Collection. Pareto Diagrams. Cause and Effect Diagrams. Introduction to the Concept of Statistical Control Charts. Summary.

Description of Attributes Data Requiring the Use of p or np Charts. Construction of p Charts. The Concept of Statistical Control. Construction of np Charts. Construction of p Charts When n Varies. Collection of Attributes Data to Support Process Study: A Case Study. Supporting Ideas for the Effective Use of p and np Charts. Practice Problems. Application Problem.

Description of Attributes Data Requiring the Use of c or u Charts. Construction of c Charts. Construction of u Charts. Using c and u Charts in Ongoing Process Improvement Work: A Case Study. Supporting Ideas for the Effective Use of c and u Charts. Summary. Practice Problems. Application Problem.

Description of Types of Variation in Process Data. Identifying Variation and Knowing Its Sources. Charts for Variables Data and Process Analysis. Summaries of Process Behavior. Examples of the Process Use of Range and X-bar Charts. Supporting Principles for the Effective Use of R and X-bar Charts (or s and X-bar Charts). Practice Problems. Application Problem.

Sampling, Subgrouping, and Elements of Purpose. Chart Characteristics Direct Sampling and Subgroup Formation. Three Sampling and Subgrouping Plans in a Dimensional Study. Subgrouping Plans for Processes with Possible Fixed Differences. Subgrouping Plans for Studying Coils, Webs, or Rolls. Principles for Rational Subgrouping. An Application of the Principles of Rational Subgrouping. Summary. Application Problems.

Process Data with Logical Subgroups of Size One. Evaluating Process Behavior with Moving Range and Individuals Charts. A Discussion of Issues Associated with the Use of MR and X Charts. Application of MR and X Charts in Process Study. Ideas for the Effective Use of MR and X Charts. Summary. Practice Problems. Application Problem.

Understanding the Components Contributing to Total Variation. Study of the Components of Variation in a Batch Process. Example of a Multiple-level Subgrouping Plan and Analysis. Study of Fixed Effects in a Hierarchical Model. Practice Problems. Application Problem.

Characterizing a Measurement Process. Evaluation of a Measurement Process: Reporting on Total Laboratory Variation. The Effect of Measurement Variation on Process Study. Comparison of Measurement Processes. Gauge R and R Studies. Recommendations for Ensuring Good Measurements. Application Problems.

Definition of Designed Experiments. Elements of Designed Experiments. Basic Mechanics of Designed Experiments. Additional Experimental Strategies. Summary and Design References. Practice Problems.

The Normal Probability Model. The Binomial Probability Model: A Theoretical Basis for p and np Charts. The Poisson Probability Model: A Theoretical Basis for c Charts.

Seven Successive Points in or Beyond Zone C on Same Side of Centerline (or the Rule of Seven). Test for Length of Longest Run. Test for Too Few Runs. Two Out of Three Successive Points in Zone A or Beyond. Four Out of Five Successive Points in Zone B or Beyond. Fifteen or More Consecutive Points in Zone C on Either Side of Centerline. Eight Consecutive Points Beyond Zone C on Either Side of Centerline.

Table D.1 Standard Normal Distribution. Table D.2 Factors for Use with X-bar and Range Charts. Table D.3 Factors for Use with X-bar and s Charts. Table D.4 Denominator Degrees of Freedom F(alpha) for alpha = .05. Table D.5 Denominator Degrees of Freedom F(alpha) for alpha = .01.