Statistical Monitoring of Processes to
Detect Special Causes of Variation
Lecture Outline
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Basics of Statistical Process Control
Control Charts
Control Charts for Attributes
Control Charts for Variables
Control Chart Patterns
SPC with Excel
Process Capability
Statistical QA Approaches
Statistical process control (SPC)
• Monitors production process to prevent poor quality
Acceptance sampling
• Inspects random sample of product to determine if a lot is acceptable
Design of Experiments
Statistical Quality Assurance
Purpose: Assure that processes are performing in an acceptable manner
Methodology: Monitor process output using statistical techniques
If results are acceptable, no further action is required
Unacceptable results call for corrective action
Acceptance Sampling:
Quality assurance that relies primarily on inspection before and after production Statistical Process Control (SPC):
Quality control efforts that occur during production
What is SPC?
A simple, yet powerful, collection of tools for graphically analyzing process data
Has one primary purpose: To tell you when you have a problem
Invented by Walter Shewhart at AT&T to minimize process tampering
Important because unnecessary process changes increase instability and increase the error rate
SPC will identify when a problem (or special cause variation) occurs
Basics of Statistical Process Control
Statistical Process Control (SPC)
- Monitoring production process to detect and prevent poor quality Sample
- Subset of items produced to use for inspection
Control Charts
- Process is within statistical control charts
Production Data always has some
Variability
Chance and Assignable Causes of
Quality Variation
Accuracy and Precision
Normal Distribution – Shaft Diameter
(What is this plot of data telling us?)
Variability
Random
Non-Random
• Common causes
• Inherent in a