Course Overview
This course is a great place to learn about what really drives product quality and how to monitor processes to pro-actively drive quality improvement. Participants gain the fundamental knowledge necessary to implement Statistical Process Control and learn to avoid the common mis-applications in practice. Knowledge of basic algebra is helpful but not required.
Seminar Content
SPC Fundamentals
- Concept of Variation
- The Normal Distribution
- Control Limits vs. Specification Limits
- Definition of Control/Stability
- Definition of Quality
- Quality Control vs. Process Control
A Central Limit Theorem
- Introduction to Non-Normal Data
- The Central Limit Theorem
Conceptual Implementation of SPC
- Measurement Systems Issues
- Monitoring Process Behavior
- Xbar and R Chart Concepts
Sources of Variation
- Common and Special Cause Sources
- Detecting Special Cause Sources
Xbar and R Charts
- Differences Between Measurements and Averages
- Computing Control Limits and Charting
Chart Interpretation
- Type I and Type II Errors
- Guidelines for Analysis of Charts
- Out of Control Signals
Basic Statistics
- Population versus Sample
- Notation
- Measures of Central Tendency (Mean, Mean)
- Measures of Variation (Range, Standard Deviation, Variance)
Sampling
- Random, Systematic, and Rational Samples
- Importance of Rational Sampling
Sensitivity
- Impact of Sample Size on Chart Sensitivity
- Determining Sample Size
Process Capability
- Stability vs. Capability
- The Standard Normal
- Z Values
- Computing Proportion Defective
- Capability Indices: Cp, Cpk, Pp, Ppk
Other Charts
- Individuals & Moving Ranges
- Xbar and S Charts
- Attribute Charts (p, np, c, u)
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