
Figure 1: PRE
PRE-Control is a simple visual control--one that makes the status of an activity obvious--for real time management of production processes. It is especially useful for processes for which no history is available with which to construct a traditional statistical process control (SPC) chart, and it does not rely on any assumptions about the process' probability density function. PRE-Control also works on processes with one-sided specifications whose underlying distributions are often non-normal, i.e. not shaped like a bell curve.
Traditional PRE-Control uses a simple chart with green, yellow and red measurement zones. When it is convenient for the operator or inspector to use a spreadsheet, PRE-Control is easily adaptable to Microsoft Excel or a similar program like Corel Quattro Pro. This article will describe a version that provides immediate visual feedback on each measurement, and it will begin with a basic overview of PRE
PRE-Control Procedure
Unlike the Shewhart control chart, PRE
Figure 2. PRE-Control Switching Rules
To qualify a new production run, the operator must produce five consecutive pieces whose measurements are all in the Green zone. The operator then takes periodic samples of two pieces, and assesses the results as follows:
If both measurements are in the Green zone, or one is Green and one is Yellow, the sample passes and operation continues.
If both measurements are in the Yellow zone in the same direction (high or low), or either is in the Red zone, the operator is to assume that the process has gone out of adjustment, and is not centered on the nominal. The process must then be adjusted to bring it back onto nominal.
After the adjustment is complete, the process must be re-qualified as if it were a new production run.[1] This rule is similar to the switching rules for many acceptance sampling plans, where a failed sample results in tightened sampling.
If the measurements are in the Yellow zone in opposite directions--one high and one low--excessive variation may be responsible.
[1] This is not mentioned explicitly in the reference, but it is reasonable to assume that the operator must confirm the effectiveness of an adjustment by re-qualifying the process.
The reference notes that a disadvantage of PRE

Table 1. Calculation of PRE-Control Zones
Deployment of PRE-Control to a Spreadsheet
The first step is to compute the boundaries of the Green, Yellow and Red zones, as shown in Table 1. Suppose the specification or tolerance limits are [90,110] mils, millimeters, or whatever, and also that the measurements will never be outside the range [80,120]. The latter provision allows error-proofing against misplaced decimal points and similar data entry errors.
Table 2. PRE-Control Spreadsheet Cells

Figure 3. Conditional Formatting of Data Entry Cells
The visual control is provided by the conditional formatting of columns C through G as shown in Figure 3, with cell C27 as an example. To access this, select the cell, FORMAT on the menu bar, and "Conditional Formatting." The format may then be copied into all other cells in columns C through G (below row 26 in Table 2).
Condition 1 states that, if the measurement is between the boundaries of the Green zone, the cell background should be green.
Condition 2 states that, if the measurement is outside the Green zone but within the Yellow zone, the cell background should be yellow.
Condition 3 states that, if the measurement is outside the Yellow zone but inside the data limits, the cell background should be red. The test for "inside the data limits" is apparently required to prevent the spreadsheet from interpreting a blank as a zero. An alternative test for a measurement below the LTL might be (C26<=$B$15)*COUNT(C26), since COUNT(C26) will be zero for an empty cell. The test for an entry above the upper data limit may be omitted, in which case a data entry error also will turn the cell red, but the column for "Data Entry" will indicate the reason.
As the operator or inspector enters measurements, the spreadsheet counts them in real time. Examples are for Row 27. The braces "{" and "}" show these to be array summations. To turn a formula into an array summation, press Control-Shift-Enter instead of just Enter.
Green: {=SUM(($C27:$G27>=B$14)*($C27:$G27<=B$13))}
Yellow: {=SUM(($C27:$G27>=B$15)*($C27:$G27
+SUM(($C27:$G27>B$13)*($C27:$G27<=B$12))}
Red: {=SUM(($C27:$G27
+SUM(($C27:$G27>B$12)*ISNUMBER($C27:$G27))}
In the latter case, the ISNUMBER function makes sure a blank will not be treated as a zero. This algorithm will also result in a "FAIL" result if the measurement is outside the data limits, but the error proofing column will indicate the reason. If zero is a valid measurement in the other zones, as it might be if the LTL is negative and the UTL is positive, a similar check for the presence of a number as opposed to a blank will be needed for the green and yellow zones.
The Result column determines whether the sample passes or fails. It begins with the following calculation (with K27 as an example), and returns +1 for a passing result and

Figure 4. Handling of Data Entry Error
Examples of Use
Figure 4 shows the start of a setup or qualification sample of five pieces. The first two measurements are in the Green zone, but the inspector enters 10 instead of 100 for the third. Note that, at this point, the spreadsheet has counted two Green zone entries for the first row.
Figure 5. Successful Qualification or Setup

Figure 6. Periodic PRE-Control Sampling

Figure 7. Unsuccessful and Successful Readjustments and Re-Qualifications
It is possible to develop a chart with Green, Yellow, and Red zones upon which the measurements can be plotted, but there is no need to have a chart when the data table itself provides immediate visual feedback on the status of each measurement.

Table 3. PRE-Control Zones, Zero is Best
Procedure when Zero is Best
For a one-sided specification in which zero is the best possible measurement, the setup is simpler. The Green zone is half the distance from zero to the tolerance limit, the Yellow zone is the remaining distance, and out of tolerance is Red. Table 3 shows an example in which the upper tolerance limit is 100, and the highest conceivable measurement is 140.
Table 4. PRE-Control Calculations, Zero is Best

Figure 8. Conditional Cell Background Formatting, Zero is Best

Figure 9. PRE-Control Examples, Zero is Best
Condition 2: If the measurement is less than or equal to the Yellow zone limit, and greater than the Green limit, turn the background yellow.
Condition 3: If the measurement is less than or equal to the data limit, and greater than the Yellow zone limit, turn the background red.
Figure 9 shows examples of how the PRE-Control spreadsheet works for the zero is best case.

Table 5. PRE-Control Zones, Minimum is Best
Procedure for One-Sided Tolerance, Minimum or Maximum is Best
For a one-sided specification in which minimum or maximum is best, the Green zone is three quarters of the distance from the best possible measurement to the tolerance limit, the Yellow zone is the remaining distance, and out of tolerance is Red. Table 5 shows an example in which the upper tolerance limit is 100, and the best possible measurement is 40.
Table 6. PRE-Control Calculations, Minimum is Best

Figure 8. Conditional Cell Background Formatting, Zero is Best

Figure 10. Conditional Cell Background Formatting, Minimum is Best
Condition 2: If the measurement is less than or equal to the Yellow zone limit, and greater than the Green zone limit, turn the cell background yellow.
Condition 3: If the measurement is less than or equal to the upper data limit, and greater than the Yellow zone limit, turn the cell background red.

Figure 11. PRE-Control Examples, Minimum is Best
The procedure for "maximum is best" is similar, and Table 7 shows the zone calculations.

Table 7. PRE-Control Zones, Maximum is Best

Table 8. PRE-Control Calculations, Maximum is Best

Figure 12: Conditional Cell Format, Maximum is Best
Summary
PRE-Control has always been a visual control that requires almost no interpretation by its user. The computer spreadsheet makes it possible to interpret measurements as soon as the user enters them, and to provide immediate feedback on the status of the measurements and the sample. It adds the capacity for real-time detection of data entry errors and, in the case of minimum is best or maximum is best, identification of new best measurements.References [1] Juran and Gryna, Quality Control Handbook, 4th ed., 24.33 to 24.34
Report Abusive Comment