Statistical Process Control - Manufacturing Quality Control Software - Because your profit is on the bottom line...

Statistical Process Control

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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