Understanding Statistical Process Control (SPC) and Top Applications

 


What is Statistical Process Control?

SPC is typically defined as a method of using statistical analysis to control and measure quality, thereby improving the manufacturing process. Manufacturers collect quality real-time data in the form of process or product measurements taken from different instrumentation and machines. The collected data is then used to monitor, evaluate, and control the manufacturing process.

By gathering this information and displaying it on graphs and charts, manufacturers can see if their processes are functioning at their highest potential. SPC highlights the areas that need improvement, enabling companies to eliminate waste, delays, and the likelihood of producing defective products.

The History of SPC

It may surprise you to know that statistical process control has been around for almost a century. In 1924, Doctor William Shewart of Bell Laboratories researched methods of improving manufacturing quality and lowering costs, which laid the groundwork for SPC. He created the control chart to determine whether a process was in or out of control. He published a book, “Statistical Method from the Viewpoint of Quality Control,” in 1939.

The US military relied heavily on SPC during the Second World War, to oversee product quality in weapons and munitions without sacrificing safety. Unfortunately, SPC fell out of practice when the war ended.

After the war, Dr. W. Edwards Deming refined and updated Shewart’s work and brought it to Japan, where Japanese businesses enthusiastically embraced the ideas. SPC helped Japan recover its manufacturing capability and even exceed it, giving the Japanese a world-wide reputation for industrial excellence.

Finally, in the 1970s, the United States, feeling the pressure of the competition stemming from Japan’s high-quality manufactured goods, began to adopt SPC. Today, statistical process control can be found all over the world.


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