Concept of statistical process control

The underlying concept of Statistical Process Control (SPC) is based on a comparison of what is happening today with what happened previously. We take a snapshot of how the process typically performs or build a model of how we think the process will perform and calculate control limits for the expected measurements of the output of the process.

Thereafter we collect data from the process and compare the data to the control limits. The majority of measurements should fall within the control limits. Measurements that fall outside the control limits are examined to see if they belong to the same population as our initial snapshot or model.

Stated differently, we use historical data to compute the initial control limits. Then the data are compared against these initial limits. Points that fall outside of the limits are investigated and, perhaps, some will later be discarded. If so, the limits would be recomputed and the process repeated. This is referred to as Phase I. Real-time process monitoring, using the limits from the end of Phase I, is called Phase II.

Key monitoring and investigating tools

There are many ways to implement process control. Key monitoring and investigating tools include:

  • Histograms
  • Check Sheets
  • Pareto Charts
  • Cause and Effect Diagrams
  • Defect Concentration Diagrams
  • Scatter Diagrams
  • Control Charts

Statistical quality control (SQC)

Several techniques can be used to investigate the product for defects or defective pieces once processing is complete.

Typical tools of SQC are:

  • Lot Acceptance Sampling Plans
  • Skip Lot Sampling Plans
  • Military (MIL) Standard Sampling Plans



Contact information
Mr Coos Bosma
Statistical Consultant and Analyst
Tel: 27 41 504 9902