Stay in Control! (Statistical Process Control)

Statistical Process Control (SPC) is an industry-standard methodology for measuring and controlling quality during the manufacturing process. The philosophy states that all processes exhibit intrinsic variation.

“Here's the TenStep guest blog post "Stay in Control! (Statistical Process Control)":

Statistical Process Control (SPC) techniques provide a data-based, objective way to determine whether your project is producing products within acceptable levels of quality. If your project is creating a small number of highly-customized deliverables, SPC techniques may not work for you. However, if your project will result in the creation of many similar products, SPC may be a good way for you to determine if your processes are sufficient to produce consistent, quality products.

SPC also helps you determine if your processes are “in control”. That is, you can determine if your processes are adequate to produce products with an acceptable level of quality on an ongoing basis. When the process starts to falter and produce products that do not conform to quality standards, the processes are designated as “out of control”. SPC techniques will tell you as soon as possible when your processes are “out of control”.


On the control chart, the horizontal axis lists the samples or points in time. The vertical axis contains measurements from these samples. The control line (CL) denotes the process target. The upper and lower acceptable control limits are represented by lines Upper Control Limit (UCL) and Lower Control Limit (LCL).


A process in control is one where all measurements over time fall within the upper control limits and the lower control limits.


A process is considered “out of control” when one or more of the following events occur.

  • One or more points are outside of the control limits
  • A run of seven points on one side of the center line (more than what would be considered “random”)
  • An unusual or nonrandom pattern in the data
  • A trend of seven points in a row upward or downward
  • Pattern of over and under CL, but within limits
  • Several points near a control limit (but not outside the limits)

If any of these situations occurs, the project team needs to investigate the cause of the problem and determine the changes required to get the process back “in control”. Simply plotting a control chart cannot improve quality or prevent process problems. The benefits of SPC depend on how the results are interpreted and used.

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