Every operation has an output in mind—either a good or a service. Additionally, procedures produce a large amount of data. Statistical Process Control, sometimes known as SPC, is a statistical technique for using the data produced by a process to continuously control and improve it.

The conventional definition of SPC is a technique for applying statistical analysis to monitor and control quality while enhancing the manufacturing process. Manufacturers get high-quality real-time data in the form of measurements of their processes or goods obtained from various tools and equipment. The manufacturing process is then monitored, assessed, and controlled using the data that have been obtained.

Manufacturers can determine whether their processes are operating to their fullest potential by gathering this data and visualising it on graphs and charts. SPC identifies opportunities for development, allowing businesses to reduce waste, delays, and the likelihood of manufacturing subpar goods.

How Do SPC Charts Work?
To track changes in the process over time, an SPC chart is employed. The process’s output data are all plotted in chronological order. A central line (CL) for the average, a lower control line (LCL) for the lower control unit, and an upper control line (UCL) for the upper control unit make up an SPC chart’s three primary parts.

Dr. Walter A. Shewhart of Bell Laboratories created SPC charts for the first time in the 1920s. They are also known as Shewhart charts because of this. But after World War II, when Dr. W. Edwards Deming introduced the idea to the Japanese industry, they became well-known. SPC charts are now used by businesses all over the world as one of the main tools to monitor and enhance process control.

What Are Limits of Control?
The standard deviations above and below the centre line of an SPC chart are known as the control limits. The process is under control if the data points fall inside the control limits (common cause variation). A process is out of control if there are data points outside of these control units (special cause variation).
When creating an SPC chart, it is better to manually plot the data points at first. You can utilise statistical software to update them after the formulas and their significance are known. A variety of tests are employed to find a “out of control” variation. Nelson tests and Western Electric tests are a couple of the most well-liked ones.

SPC Chart Uses
SPC charts are used for continuous improvement of a process utilising a number of strategies. Business analysts can benefit from SPC charts in a variety of ways, but the following are the most crucial ones:

• Recognize and address issues as soon as they arise.
• predict what results a method will produce
• Analyze a process to see if it is stable.
• Give guidance on what to focus on in order to improve the process.

What You Should Do Is This One of the places to start with every Lean Six Sigma project is next SPC charts. As a result, it’s critical to comprehend these statistical control charts in order to maintain process control.