Statistical Process Control

What is SPC?

SPC, or Statistical process control is a method used to distinguish between variation and trends that are "random" and "expected" within the uncertainty bounds of a process, and the variation and trends that are non-random, and therefore must have been caused by some "assignable" cause or influence.

History of SPC:

In early 1920s, Walter A. Shewhart pioneered the concept of a state of statistical control at Bell Laboratories. The SPC charts as we know it today were developed by Shewhart in 1924.

How Statistical Process Control helps?

Statistical Process Control bring in the power of advanced data analysis, but simplifies it in to 8 simple rules that with some training even shop floor operators and supervisors too can use to identify causes of sporadic issues, and help fix them forever.  Typical benefits seen by organizations that have implement SPC in true sense:

  1. Reduce time to identify causes of sporadic issues by 1/10th of time that would take otherwise.
  2. Reduce scrap, rework and downgrade to 1/3rd to almost kill and eradicate defect generation.
  3. Ensure an improvement action somewhere doesn't degrade performance elsewhere
  4. Trends to identify shifts in performance and scientifically establish benefit of improvement actions.
  5. Finally, payback atleast 10 times the cost of implementation and running SPC - to the companies' bottom-line.