Statistical process control (SPC) is a method of quality control that monitors processes by identifying correctable variations from the target mean. SPC was pioneered by Dr. Walter Shewhart and involves setting upper and lower control limits based on the target mean and standard deviation to determine when a process is out of statistical control. SPC uses variable and attribute control charts to monitor processes over time and identify abnormal variations that require investigation and correction.

1. STATISTICAL PROCESS CONTROL Presented by: Alisha Payton

2. What is SPC? Method of achieving quality control Monitors processes by identifying correctable variations Pioneered by Dr. Walter Shewhart STATISTICAL PROCESS CONTROL

3. STATISTICAL PROCESS CONTROL

4. What is the concept? Observes variations in processes 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 UCL LCL Sample number Mean Out of control Normal variation due to chance Abnormal variation due to assignable sources Abnormal variation due to assignable sources STATISTICAL PROCESS CONTROL

5. Example Run Chart STATISTICAL PROCESS CONTROL

6. How is it done? Set “out of control” process limits Determine process target (mean) Compute Upper Control Limits 3 σ above the mean Compute Lower Control Limits 3 σ below the mean Chart the limits on the process run charts Monitor process for “out of control” points Normal variation due to chance UCL LCL STATISTICAL PROCESS CONTROL

7. Types of Charts Variable (measurable variations) Examples: X-bar, Range chart STATISTICAL PROCESS CONTROL

8. Types of Charts Attributes (countable variations) Examples: p-chart, c-chart STATISTICAL PROCESS CONTROL

9. Normal Behavior Possible problem, investigate Possible problem, investigate UCL LCL Samples over time 1 2 3 4 5 6 UCL LCL Samples over time 1 2 3 4 5 6 UCL LCL Samples over time 1 2 3 4 5 6 STATISTICAL PROCESS CONTROL

10. How to use SPC software STATISTICAL PROCESS CONTROL