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Statistical Process Control (SPC) is a scientific, data-driven methodology for quality analysis and improvement. In manufacturing, SPC is an industry-standard methodology for measuring and controlling quality during the manufacturing process.
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Dr. Walter A. Shewhart (1891–1967), a specialist in the use of statistical methods, was responsible for the application of statistical methods to process control. Up until Shewhart, quality control methods were focused on inspecting finished goods and sorting out the nonconforming product. As an alternative to inspection, Shewhart introduced the concept of continuous inspection during production and plotting the results on a time-ordered graph that we now know as a control chart.
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By using statistical process control, manufacturers can move from a detection approach to a prevention approach, reducing or eliminating the need to rely on sorting or inspection. SPC can increase productivity, reduce waste, and reduce the risk of shipping nonconforming products.
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Control charts are used to determine whether a process is stable or unstable. However, using statistical process control just to “put out fires”—finding an out-of-control point on a control chart and then determining and removing the assignable cause—is not the same as creating continuous improvement. SPC can be fully realized only when you use it to improve processes and reduce variation.
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Control limits are calculated from the process itself. Because control limits show how the process is performing, they are also referred to as the “voice of the process.” Control limits show how the process is expected to perform; they show the variation within the system or the range of the product that the process creates.
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Specification limits are boundaries set by a customer, engineering, or management to designate where the product must perform. Specification limits are also referred to as the “voice of the customer” because they represent the results that the customer requires. If a product is out of specification, it is nonconforming and unacceptable to the customer.
All control charts have three common elements:
There are four foundational guidelines to Shewhart statistical process control charts.
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Control charts are used to determine whether a process is stable or unstable. There are many types of control charts that can be used to fit the nature of different types of data streams and sampling methods.
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Capability is calculated from existing data but can be used as a prediction of future performance. However, the capability results must come from an in-control process if the results are to be used to predict the process’s behavior in the future. The most commonly used measures of capability are Cp, Cpk, Pp, and Ppk.
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Statistical process control can help manufacturers achieve continuous process improvement—when it is implemented properly. Watch out for obstacles that can sideline your SPC efforts.
LEARN MORE: OVERCOMING OBSTACLES TO EFFECTIVE SPC