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nonconforming units are manufactured The control chart is an online process-monitoring technique widely used for this purpose Recall the following from 1 Figure 1-10 illustrates that adjustments to common causes of variation increase the variation of a process whereas Fig 1-11 illustrates that actions should be taken in response to assignable causes of variation Control charts may also be used to estimate the parameters of a production process and, through this information, to determine the capability of a process to meet speci cations The control chart can also provide information that is useful in improving the process Finally, remember that the eventual goal of statistical process control is the elimination of variability in the process Although it may not be possible to eliminate variability completely, the control chart helps reduce it as much as possible A typical control chart is shown in Fig.

<languageVersion : 1.0;> kernel FillColor < namespace : "com.actionscriptbible"; vendor : "ActionScript 3.0 Bible"; version : 1; description : "Fills image with a single color"; > { output pixel4 result; void evaluatePixel() { result = pixel4(1.0, 0.0, 0.0, 1.0); } }

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16-1, which is a graphical display of a quality characteristic that has been measured or computed from a sample versus the sample number or time Often, the samples are selected at periodic intervals such as every hour The chart contains a center line (CL) that represents the average value of the quality characteristic corresponding to the in-control state (That is, only chance causes are present) Two other horizontal lines, called the upper control limit (UCL) and the lower control limit (LCL), are also shown on the chart These control limits are chosen so that if the process is in control, nearly all of the sample points will fall between them In general, as long as the points plot within the control limits, the process is assumed to be in control, and no action is necessary.

Code inside angle brackets <> is metadata. Although this is necessary for Pixel Bender, I ll exclude it in examples in this section to focus on the implementation. I ll bring it back when I get into language details.

However, a point that plots outside of the control limits is interpreted as evidence that the process is out of control, and investigation and corrective action are required to nd and eliminate the assignable cause or causes responsible for this behavior The sample points on the control chart are usually connected with straight-line segments so that it is easier to visualize how the sequence of points has evolved over time Even if all the points plot inside the control limits, if they behave in a systematic or nonrandom manner, this is an indication that the process is out of control For example, if 18 of the last 20 points plotted above the center line but below the upper control limit and only two of these points plotted below the center line but above the lower control limit, we would be very suspicious that something was wrong.

You can see that the kernel looks like a class. Rather than return a value, you mark that the variable result will hold the output value with the output keyword and assign it a value, in this case the color red. Each time this is run, it returns the red color, so it turns each pixel red. This simple kernel has no inputs. You can have multiple inputs for a kernel, a single input, or even no inputs. Perhaps the most common application of a shader is to determine the appearance of a single image (or polygon). This kind of shader might have a single input image. Now, even though the kernel is executed for a single pixel, the input isn t limited to a single pixel of the image. The kernel has access to the full image so that it can, for example, ip an image across the diagonal:

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