Welcome to Six Sigma Black Belt, Course 7, Module 1, SPC foundations. Statistical process control involves the use of statistical tools to help the operator visualize, analyze, and control a process in a consistent manner. It is best to take a proactive stance when deploying SPC. SPC is an involved process that should only be used where it is critical to the aims of the business. Traditionally, SPC has been used to monitor and control an output. In Six Sigma circles, we seek to move control upstream, to focus on the vital axis. If we can control the axis, then the consistency of the output should be maintained. SPC helps us to frame data into understandable patterns. Since it is grounded in statistical principles, it can help us localize sources of special cause variation. The inferences we make about the process can be taken from the samples we collect, and this helps us detect shifts in the performance. SPC allows black belts to measure, monitor, and control processes. The primary feature of SPC comes in control charting. All processes are subject to variation. SPC enables us to monitor a stable process and identify changes due to factors other than random variation. Statistical process control also provides the ability to determine process capability and assess whether the process is operating as expected. These expectations are encapsulated into the average of the quality characteristic, the variability of the quality characteristic, and the consistency of performance. Control chart information can be used to determine the functional range of the process and to compare it with the specified tolerance range. If the functional range is wider, then either the specification range should be expanded or steps taken to reduce the amount of dispersion. Long-term; once we have demonstrated a controlled and capable process, we can look into ways of reducing oversight and inspection costs. Control charts can also be used as a predictive tool to determine when adjustments will be needed. When producing in lots, once an issue has been found, we have no choice but to re-examine or scrap the entire batch lot. Using control charts gives us the additional signals to stop the process at the instant an issue is found and localize our examination to only the parts produced since the last check. This significantly reduces the amount of potential suspect material. An additional benefit of control charts is the ability to monitor continuous improvement efforts. When we make changes, we should always have a way to measure the parameter both before and after the change. Because SPC is proactive in nature, we can lower our manufacturing costs. This also helps us improve stability and set realistic and manageable specifications. This will lower the frequency of inspection and translate into a better relationship with our customer. The oversight that comes with SPC promotes faster problem-solving resolution, decreased cycle time, and improved quality. As beneficial as SPC is, there are some important considerations regarding implementation. We must select the variables or attributes to monitor. Data collection methods and control charts must be set up. Training will be needed. There will also need to be dedicated resources to administrate the control chart process, as well as interpret, investigate, and implement needed corrective actions. Control charts are known as Shewhart charts. The points on the chart are the measured statistic. This could be a mean, range, or proportion. An average of all the data is represented by the solid black line, CL, and passes through the center of the data. Upper control limits, UCL, and lower control limits, LCL, are determined from the variation of the process. These limits help us assess process stability.
