Each programme built will have SPC analysis on variable and attribute tests. Just select the programme from the Plan tab in the monitoring module and you will see the SPC analysis for that programme.

Note: The analysis will only appear after enough data has been completed (For variable test SPC analysis to appear you need to complete 25 instances of the test e.g. the test is completed 25 times in one record or once in 25 records, and this can all take place in one day or over a number of days. For attribute tests, SPC analysis appears when the test has been completed at least once over 25 days).

Monitoring programs are built up from Tests. Tests include Variable tests, Attribute tests & Open Data tests. 

SPC will show analysis for attribute tests and variable tests as these types of tests have specifications.

When a variable test is set up as a single data point you will see the SPC analysis with a Control Chart Individual. When a variable test is set up as multiple selection with a sample size of <10 (but more than 2), you will see SPC analysis with the X-Bar Chart and R-Chart. When a variable test is set up as multiple selection with a sample size of >10 you will see SPC analysis with the X-bar Chart and S-Chart.

The X-bar and R-chart are quality control charts used to monitor the mean and variation of a process based on samples taken in a given time.  X-bar charts are used to monitor the mean of a process based on samples taken from the process at given times. R-chart indicates how the range of the subgroup's changes over time. The range of a sample is simply the difference between the largest and smallest observation. The S-chart is a type of control chart used to monitor the process variability (as the standard deviation) when measuring subgroups at regular intervals from a process.

When SPC analysis is enabled for an attribute test a p control chart is used. A p-chart (sometimes called a p-control chart) is used in statistical quality control to graph the proportions of defective items.

1. Data Type: States the nature of the tests data i.e Variable.
2. Status: Indicates whether the test is statistically in or out of control. Out of control processes are highlighted in Red. In control processes are highlighted in Green.
3. Upper Spec Limit: The upper specification limit as defined in the Test in Master Data.
4. Target Spec: The specification target as defined in the Test in Master Data.
5. Lower Spec Limit: The lower specification limit as defined in the Test in Master Data.
6. Total Sample Size: The total sample size is shown here (This is the previous 25 results for the test plotted on the chart).
7. Process Mean: The average of the last 25 test results (Calculation: sum of all tests results/sample size).
8. Standard Deviation: Measure to quantify the amount of variation within a set of data values.
9. Upper Control Limit: The highest level of quality acceptable for a test (Calculation: Process mean + 3 x moving range of the last 10 results / 1.128). Plotted as the upper orange dotted line on the chart.
10. Lower Control Limit: The lowest level of quality acceptable for a test (Calculation: Process mean - 3 x moving range of the last 10 results / 1.128). Plotted as the lower orange dotted line on the chart.
11. Cp Index: The Cp index is calculated using specification limits and the standard deviation only. This index indicates, in general, whether the process is capable of producing products to specifications. Cp value >1 (Quite capable), Cp value =1 (Just capable), Cp value <1 (Incapable).
12. Cpk: Cpk index is calculated using specification limits, the standard deviation, and the mean. The index indicates whether the process is capable of producing within specification and is also an indicator of the ability of the process to adhere to the target specification. Cpk <1.00 (Poor, incapable), 1.00< Cpk <1.67 (Fair), Cpk >1.67 (Excellent, Capable), Cpk = 2 for a 6δ process (i.e. a 6 sigma process).
13. Distribution Chart: Summarises values & their frequency. Displays a sample size of up to 100 tests.
14. Control Chart - Individual: Test data plotted over time indicating control limits (Shows last 25 results).

1. Data Type: States the nature of the tests data i.e. Variable.
2. Status: Indicates whether the test is statistically in or out of control. Out of control processes are highlighted in Red. In control processes are highlighted in Green.
3. Cp Index: The Cp index is calculated using specification limits and the standard deviation only. This index indicates, in general, whether the process is capable of producing products to specifications. Cp value >1 (Quite capable), Cp value =1 (Just capable), Cp value <1 (Incapable).
4. Cpk: Cpk index is calculated using specification limits, the standard deviation, and the mean. The index indicates whether the process is capable of producing within specification and is also an indicator of the ability of the process to adhere to the target specification. Cpk <1.00 (Poor, incapable), 1.00< Cpk <1.67 (Fair), Cpk >1.67 (Excellent, Capable), Cpk = 2 for a 6δ process (i.e. a 6 sigma process).
5. Total Sample Size: The total sample size is shown here (This is the number of previous results for the test plotted on the chart).
6. Upper Spec Limit: The upper specification limit as defined in the Test in Master Data.
7. Target Spec: The specification target as defined in the Test in Master Data.
8. Lower Spec Limit: The lower specification limit as defined in the Test in Master Data.
9. The Standard Deviation: Is a measure of the amount of variation or dispersion of a set of values.
10. Distribution Chart: Summarises values & their frequency. Displays a sample size of up to 100 tests.
11. The Process Mean: The process mean is the average of the observed values.
12. X Upper Control Limit: Control limits are calculated from your data for the X-bar chart. The upper control limit is based on the random variation in the process and help indicate when your process is out of control. They are drawn typically at 3 standard deviations from the center line. (Do not confuse control limits with specification limits. Control limits are based on process variation. Specification limits are based on customer requirements.  A process can be in control and yet not be capable of meeting specifications.) The X upper control limit is marked on the X-bar chart with an orange dotted line.
13. X Center Line: The center line for the X-Bar chart represents the average of the plotted points and is donated as a blue dotted line on the chart.
14. X Lower Control Limit: Control limits are calculated from your data for the X-bar chart. The lower control limit is based on the random variation in the process and help indicate when your process is out of control. They are drawn typically at 3 standard deviations from the center line. (Do not confuse control limits with specification limits. Control limits are based on process variation. Specification limits are based on customer requirements.  A process can be in control and yet not be capable of meeting specifications.) The X lower control limit is marked on the X-Bar chart with a orange dotted line.
15. X-Bar Chart: The chart plots the X upper and X lower control limits in orange and the X center line in blue. If a result is plotted above or below the upper/lower control limits the test is out of control.
16. Process Range: This is the range for the current test (range is the highest value minus the lowest value).
17. R Upper Control Limit: Control limits are calculated from your data for the R-bar chart. The R upper control limit is based on the random variation in the process and help indicate when your process is out of control.  The R upper control limit is marked on the R-Bar chart with an orange dotted line.
18. R Center Line: The center line for the R-bar chart represents the average of the plotted points and is donated as a blue dotted line on the chart.
19. R Lower Control Limit: Control limits are calculated from your data for the R-bar chart. The lower control limit is based on the random variation in the process and help indicate when your process is out of control. They are drawn typically at 3 standard deviations from the center line. (Do not confuse control limits with specification limits. Control limits are based on process variation. Specification limits are based on customer requirements.  A process can be in control and yet not be capable of meeting specifications.) The R lower control limit is marked on the R-bar chart with a orange dotted line
20. R-Chart: The chart plots the R upper and R lower control limits and the R center line in orange and the R center line in blue. If a result is plotted above or below the upper/lower control limits the test is out of control.

1. Range: When a variable test is set up as multiple selection with a sample size of >10 you will see SPC analysis with a X-bar Chart and S-Chart, the range value will be displayed here instead of a chart.

2. Process Deviation: This displays the mean standard deviation value.

3. S Upper Control Limit: The upper control limit is based on the random variation in the process and help indicate when your process is out of control. They are drawn typically at 3 standard deviations from the center line. (Do not confuse control limits with specification limits. Control limits are based on process variation. Specification limits are based on customer requirements.  A process can be in control and yet not be capable of meeting specifications.) The X upper control limit is marked on the X-bar chart with an orange dotted line.

4. S Center Line: The center line for the S-bar chart represents the average of the plotted points and is donated as a blue dotted line on the chart.

5. S Lower Control Limit: The lower control limit is based on the random variation in the process and help indicate when your process is out of control. They are drawn typically at 3 standard deviations from the center line. (Do not confuse control limits with specification limits. Control limits are based on process variation. Specification limits are based on customer requirements.  A process can be in control and yet not be capable of meeting specifications.) The S lower control limit is marked on the S-bar chart with an orange dotted line.

6. S-Bar Chart: The chart plots the S upper and S lower control limits in orange and the X center line in blue. If a result is plotted above or below the upper/lower control limits the test is out of control.

A P control chart is used to look at variation in yes/no type attributes data. There are only two possible outcomes: either the item is defective or it is not defective. The P control chart is used to determine if the fraction of defective items in a group of items is consistent over time.

1. Data Type: States the nature of the tests data i.e. Attribute
2. Status: Indicates whether the test is statistically in or out of control. Out of control processes are highlighted in Amber. In control processes are highlighted in Green.
3. Upper Control Limit: The highest level of quality acceptable for a test (Calculation: Process mean + 3x the Standard Deviation).
4. Lower Control Limit: The lowest level of quality acceptable for a test (Calculation: Process mean - 3x the Standard Deviation).
5. Avg. Sample Size: The average number of tests conducted in the last 10 days where tests occurred.
6. Avg. # nonconforming: The average number of tests conducted in the last 10 days were tests failed.
7. Total Sample Size: The total number of tests conducted in the last 10 days where tests occurred.
8. Total # Non-conforming: The average number of tests conducted in the last 10 days which failed.
9. Process Mean: The total number of tests failed/by the total number of tests conducted.
10. Standard Deviation: Measure to quantify the amount of variation within a set of data values.
11. Control Chart - P Chart: Plots the percentage non-conforming over time.