Statistical Process Control …SPCWhat is Statistical Process Control? How to implement SPC? What are the widely applied statistical methods? Statistical measurement and analysis explained. How to interpret process control charts. What is Pre-Control? When to use “c” versus “p” charts…etc..etc..
Statistical Process Control (SPC) focuses on the measurement and analysis of process performance, with a view to creating an accurate and useful measure of the current situation, identifying sources of variation impacting on the process output (i.e. the product or service being produced) and eliminating that variation with a view to consistently and repeatedly producing the desired output.
SPC converts process performance into a relatively simple visual control graph. The visual nature of SPC is one of its key strengths. However, the requirement to collect data on a routine basis, plus some of the mathematical requirements can deter people from considering the use of SPC in process improvement. However, a good understanding of even the basics of SPC, can allow very good process capability analysis and the implementation of very effective process controls.
You need to understand the differences between common and special causes of variation, you will need to be able to perform some relatively simple mathematical calculations and to create control charts. As part of the set-up process, you may want to perform some capability studies. The statistics behind Cp, Cpk, Pp and Ppk are broadly similar to those behind the x-bar and range charts.
Once you have set-up and are implementing SPC measures, you will want to start to interrogate the results you are seeing. You will need to be aware of how to identify trends, also to know if and when the control limits are appropriate. An understanding of the benefits and drawbacks of SPC will be useful, to ensure you optimize the benefits, while avoiding some of the risks associated with the application of SPC as part of process control and optimization.
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