Halden Zimmermann – DMAIC: Measure Phase continued…
• Determines if the measurement system can adequately discriminate between different parts
• Identifies the source of the variation in measurements (i.e., operators, testing methods)
Control Charting or Statistical Process Control (SPC) Tool
Purpose: The concepts of Statistical Process Control (SPC) were initially developed by Dr. Walter Shewhart of Bell Laboratories in the 1920s and were expanded upon by Dr. W. Edwards Deming, who introduced SPC to Japanese industry after WWII. After early successful adoption by Japanese firms, Statistical Process Control has now been incorporated by organizations around the world as a primary tool to improve product quality by reducing process variation.
Dr. Shewhart identified two sources of process variation. Chance variation is inherent in process and stable over time, and Assignable or Uncontrolled variation is unstable over time. Assignable or Uncontrolled variation is the result of specific events outside the system. Dr. Deming relabeled chance variation as Common Cause variation and assignable variation as Special Cause variation. Based on the laws of statistics and probability, Dr. Shewhart and Dr. Deming devised control charts to plot data over time and identify both Common Cause variation and Special Cause variation.
A Control Chart is a specialized time series plot designed to identify abnormal patterns of variability in a process. The X-bar & R-charts are probably the most commonly used control charts.
Application: Use with time-ordered sample data to identify an important quality characteristic.
Control Charts can help answer questions such as:
• Is my process (machine/operator) stable?
• Is the process average in control?
• Does the process average remain consistent between subgroups?
•What is the variability in the manufacturing process?