Statistical Process Control (SPC)

This is a seminar on the practical application of control charts to improve quality and reduce costs, emphasizing the continuous improvement of processes in both the manufacturing and administrative areas.

Statistical process control is a fundamental building block in TQM. This seminar is more practical and interesting for participants by drawing on their actual workplace examples and data.

In addition to learning basic calculation skills, participants learn about the power and limitations SPC.  They learn how to apply SPC to a process and successfully implement it as part of a company's total quality efforts.

Who should attend this seminar?

Manufacturing Engineers, Quality Engineers, and other production persons will find it very useful as well. Managers of these functions will benefit greatly. Persons from service or administrative functions will receive exercises and applications tailored to their needs. 

This is a 16 hour course with a maximum class size of 24.

On completion of this seminar you will be able to:

  • Analyze variation for informed decisions using histograms.
  • Construct the two most commonly used control charts for variables and attributes type data.
  • Calculate control limits for continuous improvement.

      You will understand:
  • The nature of variation, how it is controlled and why it is important to control.
  • The conceptual difference between old and new quality control methods.
  • Process control vs. simply meeting requirements.
  • What average and range is, not just how it is calculated, and why it enables SPC to work so effectively.
  • The mechanics of creating control charts.
  • The difference between assignable cause and random cause and how this can convert art to science.

      Topics covered:
  • Prevention vs. inspection
  • Nature of variation
  • Histograms
  • Average, range, median and standard deviation
  • Variables control charting
  • Attributes control charting
  • Control chart examples and applications
  • Short run SPC
  • Narrow limit gauging
  • Process capability analysis (Cpk)