SPC - Statistical Process Control

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Statistical Process Control (SPC) (Page 3 of 5)

In relation to the preceding discussions, this is equivalent to achieving data distributions that are centered between the specified limits, and as narrow as possible. Good centering between limits and negligible variation translates to parameters that are always within specifications, which is the true essence of process control.

Control Charting

It is often said that you can not control something that you do not measure. Thus, every engineer setting up a new process must have a clear idea of how the performance of this new process is to be measured. Since every process needs to satisfy customer requirements, process output parameters for measurement and monitoring are generally based on customer specifications. Industry-accepted specifications are also followed in selecting process parameters for monitoring.

Control charting is a widely-used tool for process monitoring in the semiconductor industry. It employs control charts (see Fig. 3), which are simply plots of the process output data over time. Before a control chart may be used, the process engineer must first ensure that the process to be monitored is normal and stable.

A process may have several control charts - one for each of its major output parameters. A new control chart must have at least the following: the properly labeled x- and y-axes, lines showing the lower and upper specification limits for the parameter being monitored, and a line showing the center or target of these specifications. Once a control chart has been set up, the operator must diligently plot the output data at predefined intervals.

After 30 data points have been collected on the chart (may be less if measurement intervals are long), the upper and lower control limits of the process may already be computed. Control limits define the boundaries of the normal behavior of the process. Their values depend only on the output data generated by the process in the immediate past. Control limits are therefore independent of specification limits. However, both sets of limits are used in the practice of SPC, although in different ways.

The lower control limit LCL and the upper control limit UCL of a process may be calculated from the mean and standard deviation (or sigma) of the plotted data as follows:

LCL = Mean - (3 x Sigma);

UCL = Mean + (3 x Sigma).

Thus, the span from the LCL of a process to its UCL is 6 sigma. The probability of getting points outside this +/- 3 sigma range is already very low (see Table 1). Getting a measurement outside this range should therefore warn an engineer that something abnormal is happening, i.e., the process may be going out of control. This is the reason why these boundaries are known as 'control limits.'

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