Chapter 13 Statistical Applications in Quality and Productivity Management

1. Statistics for Managers Using Microsoft® Excel5th Edition Chapter 13 Statistical Applications in Quality and Productivity Management

2. Chapter Overview

3. Process Variation Total Process Variation Common Cause Variation Special Cause Variation = + • Variation is natural; inherent in the world around us • No two products or service experiences are exactly the same • With a fine enough gauge, all things can be seen to differ

4. Total Process Variation Total Process Variation Common Cause Variation Special Cause Variation = + Variation is often due to differences in: • People • Machines • Materials • Methods • Measurement • Environment

5. Common Cause Variation Total Process Variation Common Cause Variation Special Cause Variation = + Common cause variation • naturally occurring and expected • the result of normal variation in materials, tools, machines, operators, and the environment

6. Special Cause Variation Total Process Variation Common Cause Variation Special Cause Variation = + Special cause variation • abnormal or unexpected variation • has an assignable cause • variation beyond what is considered inherent to the process

7. Control Charts • One “visual” tool used to monitor process, and identify special cause variations as they occur over time is Control Charts Invented by Walter Shewhart in 1920s while working at Bell Labs (see more below) http://en.wikipedia.org/wiki/Control_chart UCL +3σ -3σ LCL

8. Why use control charts? • To identify assignable (special) causes of variation • To reduce defects • To lower costs • To identify opportunities for improvement • To provide an early warning System

9. Control Chart Basics Special Cause Variation: Range of unexpected variability UCL Common Cause Variation: range of expected variability +3σ Process Average -3σ LCL time UCL = Process Average + 3 Standard Deviations LCL = Process Average – 3 Standard Deviations

10. Process Variability Special Cause of Variation: A measurement this far from the process average is very unlikely if only expected variation is present UCL ±3σ → 99.7% of process values should be in this range Process Average LCL time UCL = Process Average + 3 Standard Deviations LCL = Process Average – 3 Standard Deviations

11. In-control Process • A process is said to be in control when the control chart does not indicate any out-of-control condition • Contains only common causes of variation • If the common causes of variation is small, then control chart can be used to monitor the process • If the common causes of variation is too large, you need to alter the process

12. Process In Control • Process in control: points are randomly distributed around the center line and all points are within the control limits UCL Process Average LCL time

13. Process Not in Control Out of control conditions: • One or more points outside control limits • Eight or more points in a row on one side of the center line • Eight or more points movingin the same direction • 14 or more points alternating above and below the center line

14. Process Not in Control • Eight or more points in a row on one side of the center line • One or more points outside control limits UCL UCL Process Average Process Average LCL LCL • Eight or more points moving in the same direction • 14 or more points alternating above and below the center line UCL UCL Process Average Process Average LCL LCL

15. Out-of-control Processes • When the control chart indicates an out-of-control condition (a point outside the control limits or exhibiting trend, for example) • Contains both common causes of variation and assignable causes of variation • The assignable causes of variation must be identified • If detrimental to the quality, assignable causes of variation must be removed • If increases quality, assignable causes must be incorporated into the process design