Meaning
Statistical process control charts track the variation of individual measurements over time to determine if a manufacturing process is stable. Quality engineers plot data on an i-chart when the data cannot be grouped into subgroups, such as with destructive testing or low-volume production. This chart governs the monitoring phase of production, displaying each individual measurement alongside its statistical limits.
It does not measure product specifications, but rather the natural variation of the process itself, allowing operators to detect shifts in the process mean.
Statistical Formula
Control limits on this chart are calculated using the moving range between consecutive data points to estimate process variability. The i-chart utilizes a central line representing the average of all individual measurements, with upper and lower control limits set at three standard deviations. These calculated limits define the boundaries within which the process is expected to operate under normal conditions.
Trend Interpretation
Process variation analysis relies on identifying specific non-random patterns that indicate a process shift or a special cause of variation. On an i-chart, a single point plotting outside the control limits or a run of nine consecutive points on one side of the average line indicates an out-of-control condition. This visual tool allows operators to spot issues before they result in defective parts.
Process Adjustment
Quality protocols require operators to stop the line and investigate the process whenever a control limit is violated. This structured approach prevents unnecessary adjustments that can increase variation, a problem known as over-control. Using the chart ensures that adjustments are made only when a genuine shift in the process is detected.