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Statistical Process Control

This course is conducted by quality experts and practitioners at Integral Concepts, our training partner. It 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 misapplications in practice. Knowledge of basic algebra is helpful but not required.

To sign up for this course, contact Integral Concepts at (248) 884-2276.

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Seminar Outline

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)


  • Random, Systematic, and Rational Samples
  • Importance of Rational Sampling


  • 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)