What is SPC - Statistical Process Control?
History of Statistical Process Control (SPC)
SPC was developed at Bell Laboratories in the early 1920s by Walter A. Shewhart. In 1924 he introduced the control chart tool and coined the concept of a state of statistical control. He eventually published a book titled “Statistical Method from the Viewpoint of Quality Control” (1939). The SPC methodology gained wide usage during World War II by the military in the munitions and weapons facilities. The demand for product forced them to look for a better and more efficient way to monitor quality without compromising safety. In the 1970’s, the Japanese manufacturing companies adopted SPC to improve their product quality. Today, SPC is a widely used quality methodology throughout many industries.
What is Statistical Process Control (SPC)
Statistical process control (SPC) is a method of quality control which employs statistical methods to monitor and detect sources of variations. This helps to ensure that the process operates efficiently, producing more specification-conforming products with less waste (rework or scrap). SPC can be applied to any process where the "conforming product" (product meeting specifications) output can be measured.
The application of SPC involves three main phases of activity:
- Understanding the process and the specification limits using design of experiments.
- Monitoring the ongoing process, assisted by control charts, to detect significant changes of mean or variation.
- Continuous Improvement to identify and eliminate assignable (special) sources of variation using tools like ANOVA, 80/20 Pareto analysis & Failure mode analysis
Why should you implement Statistical Process Control (SPC)
An advantage of SPC over other methods of quality control, such as "inspection" (pass/fail) is that it emphasizes early detection and prevention of problems, rather than the correction of problems after they have occurred. In addition to reducing waste, SPC directly impacts manufacturing productivity and capacity as it leads to a reduction in the time required to produce the product and makes it less likely that the finished product will need to be reworked or scrapped.
Here are some key benefits to develop a compelling Return on Investment (ROI) for implementing SPC:
Learn More about Statistical Process Control (SPC)
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Abeer has over a decade of experience in semiconductor processing and advanced manufacturing. He is co-inventor on U.S. patents in the field of semiconductor manufacturing and has extensive experience implementing advanced manufacturing systems for high volume and complexity products. Prior to his role at Sentient, Abeer has worked as an equipment technician, process engineer, advanced process control systems engineer, and manufacturing systems architect. He has a degree in Microelectronic Engineering.