What does a control chart track, and which type of process variation does it help identify?

What does a control chart track, and which type of process variation does it help identify?

• A. A control chart tracks a process metric over time to detect assignable (special) versus common cause variation.
• B. It forecasts demand for products using time series data only.
• C. It measures only average process output without variation.
• D. It identifies optimal process settings to eliminate all variation.

Answer: (A)

Control charts monitor a process metric over time and help you tell whether the variation you see is the normal, built-in kind or due to a specific, identifiable cause. The chart shows data points in time order, with a center line (the usual or target value) and control limits. When most points stay within limits and look random, the variation is likely common cause—just the everyday noise of the process. If a point lands outside the limits or patterns appear—such as a run of points trending up, a sudden shift, or a repeating cycle—that signals assignable (special) variation, meaning something in the process has changed and should be investigated. This tool is not about forecasting demand, nor about eliminating all variation or focusing only on the average. It’s about distinguishing normal variation from actionable, identifiable problems so you can keep the process in control or take corrective actions when needed.

Control charts monitor a process metric over time and help you tell whether the variation you see is the normal, built-in kind or due to a specific, identifiable cause. The chart shows data points in time order, with a center line (the usual or target value) and control limits. When most points stay within limits and look random, the variation is likely common cause—just the everyday noise of the process. If a point lands outside the limits or patterns appear—such as a run of points trending up, a sudden shift, or a repeating cycle—that signals assignable (special) variation, meaning something in the process has changed and should be investigated.

This tool is not about forecasting demand, nor about eliminating all variation or focusing only on the average. It’s about distinguishing normal variation from actionable, identifiable problems so you can keep the process in control or take corrective actions when needed.