Basic Concepts of Statistical Process Control (SPC)

Basic Concepts of Statistical Process Control (SPC)

 

Basic Concepts of Statistical Process Control (SPC)- Dr. Walter Shewhart identified two sources of process variation:

  • Chance variation that is inherent in process, and stable over time, and
  • Assignable, or Uncontrolled variation, which is unstable over time – the result of specific events outside the system.

Dr. Deming relabelled chance variation as Common Cause variation and assignable variation as Special Cause variation.

Statistical Process Control (SPC) is a statistical method to measure, monitor, and control a process. In other words, SPC is a method of quality control that employs statistical methods to measure, monitor, and control a process. It is a scientific visual method to monitor, control, and improve the process by eliminating special cause variation in a process. SPC focuses on optimizing continuous improvement by using statistical tools to analyze data, make inferences about process behavior, and then make appropriate decisions. The basic assumption of SPC is that all processes are subject to variation.

SPC helps companies to move towards prevention-based quality control instead of detection based quality controls. By monitoring SPC graphs, organizations can easily predict the behavior of the process.

After the experience with many types of process data, and supported by the laws of statistics and probability, control charts are used to plot data over time and identify both Common Cause Variation and Special Cause variation.

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