Expected between/within (B/W) performance for Between/Within Capability Analysis

Find definitions and interpretation guidance for every expected between/within performance measure that is provided with the between/within capability analysis.

PPM < LSL for Expected Between/Within Performance

PPM < LSL for expected between/within performance is the expected number of parts per million that have measurements that are less than the lower specification limit (LSL). Expected between/within performance values are calculated using the between/within standard deviation. PPM < LSL for expected within performance is 1,000,000 times the probability that the measurement of a randomly selected part from the between/within subgroup process distribution is less than LSL.

The probability that a randomly selected part is less than LSL is shown by the shaded region under the between/within normal curve.

Interpretation

Use PPM < LSL for expected between/within performance to estimate the number of nonconforming items, represented in parts per million, that you can expect to be below the lower specification limit based on the variation between/within the subgroups. Between/within performance values indicate the performance that could be achieved if additional sources of systemic process variation, besides the variation between and within subgroups, could be eliminated.

Lower values of PPM < LSL indicate greater process capability, relative to the lower specification limit. Ideally, few or no parts have measurements that are less than the lower specification limit.

PPM > USL for Expected Between/Within Performance

PPM > USL for expected between/within performance is the expected number of parts per million that have measurements that are greater than the upper specification limit (USL). Expected between/within performance values are calculated using the between/within standard deviation. PPM > USL for expected within performance is 1,000,000 times the probability that the measurement of a randomly selected part from the between/within subgroup process distribution is greater than USL.

The probability that a randomly selected part is greater than USL is shown by the shaded region under the between/within normal curve.

Interpretation

Use PPM > USL for expected between/within performance to estimate the number of nonconforming items, represented in parts per million, that you can expect to be above the upper specification limit based on the variation between/within the subgroups. Between/within performance values indicate the performance that could be achieved if additional sources of systemic process variation, besides the variation between and within subgroups, could be eliminated.

Lower values of PPM > USL indicate greater process capability, relative to the upper specification limit. Ideally, few or no parts have measurements that are greater than the upper specification limit.

PPM Total for Expected Between/Within Performance

PPM Total for expected between/within performance is the expected number of parts per million that have measurements that are outside the specification limits. Expected between/within performance values are calculated using the between/within standard deviation. PPM Total for expected between/within performance is 1,000,000 times the probability that the measurement of a randomly selected part from the within-subgroup process distribution is outside the specification limits.

The probability that a randomly selected part is outside the specification limits is shown by the shaded regions under the between/within normal curve.

Interpretation

Use PPM Total for expected between/within performance to estimate the number of nonconforming items, represented in parts per million, that you can expect to be outside the specification limits based on the variation between/within the subgroups. Between/within performance values indicate the performance that could be achieved if additional sources of systemic process variation, besides the variation between and within subgroups, could be eliminated.

Lower values of PPM Total indicate greater process capability. Ideally, few or no parts have measurements that are outside the specification limits.

You can also use PPM to estimate the percentage of conforming and nonconforming parts in your process.
PPM % Nonconforming Parts % Conforming
66807 6.807% 93.193%
6210 0.621% 99.379%
233 0.0233% 99.9767%
3.4 0.00034% 99.99966%

% < LSL for Expected Between/Within Performance

% < LSL for expected between/within performance is the expected percentage of parts that have measurements that are less than the lower specification limit (LSL). Expected between/within performance values are calculated using the between/within standard deviation. % < LSL for expected within performance is the probability that the measurement of a randomly selected part from the between/within subgroup process distribution is less than LSL.

The probability that a randomly selected part is less than LSL is shown by the shaded region under the between/within normal curve.

Interpretation

Use % < LSL for expected between/within performance to estimate the percentage of nonconforming items that you can expect to be below the lower specification limit based on the variation between/within the subgroups. Between/within performance values indicate the performance that could be achieved if additional sources of systemic process variation, besides the variation between and within subgroups, could be eliminated.

Lower values of % < LSL indicate greater process capability, relative to the lower specification limit. Ideally, few or no parts have measurements that are less than the lower specification limit.

% > USL for Expected Between/Within Performance

% > USL for expected between/within performance is the expected percentage of parts that have measurements that are greater than the upper specification limit (USL). Expected between/within performance values are calculated using the between/within standard deviation. % > USL for expected within performance is the probability that the measurement of a randomly selected part from the between/within subgroup process distribution is greater than USL

The probability that a randomly selected part is greater than USL is shown by the shaded region under the between/within normal curve.

Interpretation

Use % > USL for expected between/within performance to estimate the percentage of nonconforming items that you can expect to be above the upper specification limit based on the variation between/within the subgroups. Between/within performance values indicate the performance that could be achieved if additional sources of systemic process variation, besides the variation between and within subgroups, could be eliminated.

Lower values of % > USL indicate greater process capability, relative to the upper specification limit. Ideally, few or no parts have measurements that are greater the upper specification limit.

% Total for Expected Between/Within Performance

% Total for expected between/within performance is the expected percentage of parts that have measurements that are outside the specification limits. Expected between/within performance values are calculated using the between/within standard deviation. % Total for expected between/within performance is the probability that the measurement of a randomly selected part from the between/within process distribution is outside the specification limits.

The probability that a randomly selected part is outside the specification limit is shown by the shaded regions under the between/within normal curve.

Interpretation

Use % Total for expected between/within performance to estimate the percentage of nonconforming items, that you can expect to be outside the specification limits based on the variation between/within the subgroups. Between/within performance values indicate the performance that could be achieved if additional sources of systemic process variation, besides the variation between and within subgroups, could be eliminated.

Lower values of % Total indicate greater process capability. Ideally, few or no parts have measurements that are outside the specification limits.

Z.LSL for Between/Within Capability

Z.LSL (between/within) is the number of standard deviations between the process mean and the lower specification limit (LSL). It is calculated based on the between/within process performance, using the between/within subgroup standard deviation.

Note

To display Z.bench measures, you must click Options and change the default output from capability statistics to benchmark Z's when you perform the capability analysis.

Interpretation

Use Z.LSL (between/within) to evaluate the between/within sigma capability of your process relative to the lower specification limit.

Generally, higher Z.LSL values indicate that the process is capable at the lower tail of the distribution. Lower values indicate that your process may need improvement. When possible, compare Z.LSL (between/within) with a benchmark value based on process knowledge or industry standards. If Z.LSL is less than your benchmark, consider ways to improve your process.

Z.USL for Between/Within Capability

Z.USL (between/within) is the number of standard deviations between the process mean and the upper specification limit (USL). It is calculated based on the between/within process performance, using the between/within subgroup standard deviation.

Note

To display Z.bench measures, you must click Options and change the default output from capability statistics to benchmark Z's when you perform the capability analysis.

Interpretation

Use Z.USL (between/within) to evaluate the between/within sigma capability of your process relative to the upper specification limit.

Generally, higher Z.USL values indicate that the process is capable at the upper tail of the distribution. Lower values indicate that your process may need improvement. When possible, compare Z.USL (between/within) with a benchmark value based on process knowledge or industry standards. If Z.USL is less than your benchmark, consider ways to improve your process.

Z.Bench for Between/Within Capability

Z.bench (between/within) is the percentile on a standard normal distribution that translates the estimated probability of defects in the process to an upper tail probability. It is calculated based on the between/within process performance, using the between/within standard deviation.

The defects for the process fall on either side of the specification limits. The between/within subgroup standard deviations are shown by the tick marks.

If you put all the defects on the right tail of the distribution, and then measure the number of between/within- subgroup standard deviations from the center (red line) to the point that defines the total defects, you obtain the Z-bench (between/within) value.

Note

To display Z.bench, you must click Options and change the default output from capability statistics to benchmark Z's when you perform the capability analysis.

Interpretation

Use Z.Bench (between/within) to evaluate the between/within sigma capability of your process.

Generally, higher Z.bench (between/within) values indicate that the process is more capable. Lower values indicate that your process may need improvement. When possible, compare Z.bench (between/within) with a benchmark value based on process knowledge or industry standards. If Z.bench (between/within) is less than your benchmark, consider ways to improve your process.

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