Statistical Process Control (SPC) Dashlets
Statistical Process Control (SPC) is a method of Quality Control that employs statistical methods to monitor and control a process. This helps to ensure that the process operates efficiently, producing more specification-conforming products with less waste, rework, or scrap.
SPC Analysis must be enabled within the Attribute or Variable Test, it is not automatically enabled when an Attribute or Variable Test is created. When creating your Variable and Attribute Tests, ensure to tick the 'Enable SPC Analysis' option if you wish to use the SPC Analysis.
Note: Open Data Tests are not included in SPC Analysis as they do not have Specifications.
Where to Enable SPC Analysis:
Image: Enabling SPC Analysis in an Attribute Test
Image: Enabling SPC Analysis in a Variable Single Selection Single Data Point Test
Image: Enabling SPC Analysis in a Variable Multiple Selection Test
Note: Click here to access the article on creating Tests for use in Monitoring Programmes for further details.
Where can Statistical Process Control (SPC) Analysis Dashlets be found in Safefood360°?
Statistical Process Control (SPC) Analysis Dashlets can be found in the following places of the Monitoring module:
In the Monitoring module there is a Tab called 'Analysis - SPC'. This Tab allow you to quickly see any 'Out of Control' Attribute or Variable Tests based on SPC Rules, using historical data.
An 'Out of Control' Result will only:
- Appear in the Analysis - SPC Tab when the Tests 'SPC Result' has Resulted in a Fail in the latest row of a 'Saved & Submitted' Monitoring Record Workflow Stage.
- Disappear in the Analysis - SPC Tab when the Tests 'SPC Result' has Resulted in a Pass in the latest row of a 'Saved & Submitted' Monitoring Record Workflow Stage.
Image: Analysis - SPC Tab
1. No.: The number of the Monitoring Programme containing the Test, will appear here.
2. Date: The date the Monitoring Record containing the Test was completed, will appear here.
3. Programme: The name of the Monitoring Programme that the Monitoring Record was generated from, will appear here.
4. Test: The name of the Test will appear here.
5. View: Click the 'View' button to populate the Test dashlet to the right. Each Test will have its own dashlet.
6. Choose Test: When the Analysis - SPC Tab is accessed first, the dashlet will say 'Choose Test' as the dashlet cannot populate until you click the 'View' button on the Test you wish to see the Analysis on. See below for the details on the dashlet for:
Image: Variable Test Analysis - SPC Dashlet
1. Name of Dashlet: The name of the Test will appear here once the 'View' button is clicked.
2. Data Type: The type of Test will appear here, e.g. Attribute or Variable.
3. Status: The status will note as 'Out of Control'.
4. SPC Charts: The data shown in the SPC Charts will depend on the type of Test and sample size selected. See below for further information on:
Image: Variable Single Selection SPC Dashlet
1. Specification Limits: The Upper, Lower, Warning Limits and Target Spec for the Test will appear here. These limits are set within the Test in Master Data.
2. Total Sample Size: The total sample size is shown here (This is the previous 25 results for the test plotted on the chart).
3. Process Mean (x̄): The process mean is the average of the observed values.
4. Standard Deviation (σ): The standard deviation is a measure of the amount of variation or dispersion of a set of values.
5. Upper Control Limit/Lower Control Limit: Control limits are calculated from your data. The upper and lower control limits are based on the random variation in the process and helps to 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.)
6. 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).
7. 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).
8. Distribution Chart: The chart displays the frequency of various outcomes in a sample.
9. Control Chart - Individual: Different control charts will be displayed here and it depends on several factors. A Control Chart - Individual is displayed if the test was set as a Variable Single Selection.
Image: Variable Multiple Selection with a Sample Size of less than 10 SPC Dashlet
1. Sample Size: The sample size of the Variable Multiple Selection Test is shown here.
2. Process Deviation (σ): This displays the mean standard deviation value.
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. Process Mean (x̄): The process mean is the average of the observed values.
6. X Upper Control Limit/Center Line/Lower Control Limit: Control limits are calculated from your data. The upper and lower control limits are based on the random variation in the process and they help to 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.)
7. Process Range (R): This is the range for the current test (range is the highest value minus the lowest value).
8. R Upper Control Limit/Center Line/Lower Control Limit: Control limits are calculated from your data. The upper and lower control limits are based on the random variation in the process and they help to 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.)
9. Distribution Chart: The chart displays the frequency of various outcomes in a sample.
10. X-Bar Chart and R-Bar Charts: The X-Bar Chart and R-Bar Chart will be displayed if the test is Variable Multiple Selection with a sample size of less than 10.
Image: Variable Multiple Selection with a Sample Size of more than 10 SPC Dashlet
1. Sample Size: The sample size of the Variable Multiple Selection Test is shown here.
2. Process Range (R): The process range is
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. Process Mean (x̄): The process mean is the average of the observed values.
6. X Upper Control Limit/Center Line/Lower Control Limit: Control limits are calculated from your data. The upper and lower control limits are based on the random variation in the process and they help to 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.)
7. Process Deviation (σ): The standard deviation is a measure of the amount of variation or dispersion of a set of values.
8. S Upper Control Limit/Center Line/Lower Control Limit: Control limits are calculated from your data. The upper and lower control limits are based on the random variation in the process and they help to 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.)
9. Distribution Chart: The chart displays the frequency of various outcomes in a sample.
10. X-Bar Chart and S-Bar Charts: The X-Bar Chart and S-Bar Chart will be displayed if the test is a Variable Multiple Selection with a sample size of more than 10.
Image: Sample Sizes for Variable Multiple Selection Tests and the SPC Charts Related
Image: Attribute Test Analysis - SPC Dashlet
1. Name of Dashlet: The name of the Test will appear here once the 'View' button is clicked.
2. Data Type: The type of Test will appear here, e.g. Attribute or Variable.
3. Status: The status will be noted as 'Out of Control'.
4. Upper Control Limit: The highest level of quality acceptable for a test (Calculation: Process mean + 3x the Standard Deviation).
5. Lower Control Limit: The lowest level of quality acceptable for a test (Calculation: Process mean - 3x the Standard Deviation).
6. Avg. Sample Size: The average number of tests conducted in the last 25 days where tests occurred.
7. Avg. # Nonconforming: The average number of tests conducted in the last 25 days were tests failed.
8. Total Sample Size: The total number of tests conducted in the last 25 days where tests occurred.
9. Total # Nonconforming: The average number of tests conducted in the last 25 days which failed.
10. Process Mean: The total number of tests failed/by the total number of tests conducted.
11. Standard Deviation: Measure to quantify the amount of variation within a set of data values.
12. Control Chart - P Chart: Plots the percentage of non-conforming over time. A P-Chart is used to look at variation in yes/no type attribute data. There are only two possible outcomes: either the item is defective or it is not defective. The P-Chart is used to determine if the fraction of defective items in a group of items is consistent over time.
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In the Monitoring Programme Overview Page, there is a dropdown called 'Statistical Process Control'. This dropdown allows you to quickly see the SPC Dashlets for Variable or Attribute Tests located in the Monitoring Programme that have SPC Analysis enabled.
To access the Monitoring Programme Page, select the Monitoring Programme from the 'Plan' tab in the Monitoring module.
Remember: If there not enough data to populate a SPC Dashlet, the Dashlet will note 'Insufficient Data Available' as seen in the image below.
Image: Navigation to Monitoring 'Plan' Tab and Selecting Monitoring Programme
Image: Monitoring Programme Page With Statistical Process Control Arrow to Open Dashlets
Note: The data shown in the SPC Analysis Dashlets will depend on the type of Test and sample size selected.
See below for further information on:
Remember: For SPC Analysis to appear, you must complete 25 instances of that Variable Test. For example:
- Example 1: The Variable Test is completed 25 times in the 1 Monitoring Record. These 25 instances, must be completed in 25 different sample rows of the 1 Monitoring Record.
or
- Example 2: The Variable Test is completed 1 time in 25 different Monitoring Records. These 25 Monitoring Records can be completed in 1 day or over a number of different days.
Image: Variable Test - Single Selection Single Data Point SPC Dashlet
1. Name of Dashlet: The name of the Test will appear here.
2. Data Type: States the nature of the Test data, e.g., Variable or Attribute.
3. Status: The 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.
Image: 'Out of Control' Example
4. Specification Limits: The Upper Limit, Lower Limit and Target Spec for the Test will appear here. These limits are set within the Test in Master Data.
5. Total Sample Size: The total sample size is shown here (This is the previous 25 results for the test plotted on the chart).
6. Process Mean: The average of the last 25 test results (Calculation: sum of all test results/sample size).
7. Standard Deviation: Measure to quantify the amount of variation within a set of data values.
8. 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.
9. 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.
10. 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).
11. Cpk: Cpk is calculated using specification limits, the standard deviation, and the mean. This 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).
12. Distribution Chart: Summarises values and their frequency. Displays a sample size of up to 100 tests.
13. Control Chart - Individual: Test data plotted over time indicating control limits (Shows last 25 results).
Remember: For SPC Analysis to appear, you must complete 25 instances of that Variable Test. For example:
- Example 1: The Variable Test is completed 25 times in the 1 Monitoring Record. These 25 instances, must be completed in 25 different sample rows of the 1 Monitoring Record.
or
- Example 2: The Variable Test is completed 1 time in 25 different Monitoring Records. These 25 Monitoring Records can be completed in 1 day or over a number of different days.
Image: Variable Test - Multiple Selection with a Sample Size of Less than 10 SPC Dashlet
1. Name of Dashlet: The name of the Test will appear here.
2. Data Type: States the nature of the Test data, e.g., Variable or Attribute.
3. Status: The 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.
Image: 'In Control' Status Example
4. 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).
5. Cpk: Cpk is calculated using specification limits, the standard deviation, and the mean. This 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).
6. Sample Size: The total sample size is shown here (This is the number of previous results for the test plotted on the chart).
7. Specification Limits: The Upper Limit, Lower Limit and Target Spec for the Test will appear here. These limits are set within the Test in Master Data.
8. Standard Deviation(σ): The standard deviation is a measure of the amount of variation or dispersion of a set of values.
9. Distribution Chart: Summarises values and their frequency. Displays a sample size of up to 100 tests.
10. Process Mean (x̄): The process mean is the average of the observed values.
11. 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 helps to 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.
12. 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.
13. 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 helps to 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 an orange dotted line.
14. 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.
15. Process Range: This is the range for the current test (range is the highest value minus the lowest value).
16. 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 helps to 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.
17. 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.
18. 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 helps to 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 an orange dotted line
19. R-Bar 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.
Remember: For SPC Analysis to appear, you must complete 25 instances of that Variable Test. For example:
- Example 1: The Variable Test is completed 25 times in the 1 Monitoring Record. These 25 instances, must be completed in 25 different sample rows of the 1 Monitoring Record.
or
- Example 2: The Variable Test is completed 1 time in 25 different Monitoring Records. These 25 Monitoring Records can be completed in 1 day or over a number of different days.
Image: Variable Test - Multiple Selection with a Sample Size of More than 10 SPC Dashlet
1. Name of Dashlet: The name of the Test will appear here.
2. Data Type: States the nature of the Test data, e.g., Variable or Attribute.
3. Status: The 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.
Image: 'Out of Control' Status Example
4. 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).
5. Cpk: Cpk is calculated using specification limits, the standard deviation, and the mean. This 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).
6. Sample Size: The total sample size is shown here (This is the number of previous results for the test plotted on the chart).
7. Specification Limits: The Upper Limit, Lower Limit and Target Spec for the Test will appear here. These limits are set within the Test in Master Data.
8. Range: When a variable test is set up as multiple selection with a sample size of more than 10 you will see SPC Analysis with a X-Bar Chart and S-Bar Chart, the range value will be displayed here instead of a R-Bar Chart.
9. Distribution Chart: Summarises values and their frequency. Displays a sample size of up to 100 tests.
10. Process Mean (x̄): The process mean is the average of the observed values.
11. 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 helps to 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.
12. 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.
13. 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 helps to 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 an orange dotted line.
14. 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.
15. Process Deviation (σ): This displays the mean standard deviation value.
16. S Upper Control Limit: The upper control limit is based on the random variation in the process and helps to 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 upper control limit is marked on the S-Bar Chart with an orange dotted line.
17. 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.
18. S Lower Control Limit: The lower control limit is based on the random variation in the process and helps to 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.
19. 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.
Remember: For SPC Analysis to appear, you must complete 25 instances of that Attribute Test.
- The Attribute Test is completed 1 time in 25 different Monitoring Records. These 25 different Monitoring Records must be completed over 25 different days, resulting in 25 different days worth of data.
When SPC Analysis is enabled for an Attribute Test a P-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.
Image: Attribute Test SPC Dashlet
1. Name of Dashlet: The name of the Test will appear here once the 'View' button is clicked.
2. Data Type: States the nature of the Test data, e.g., Variable or Attribute.
3. Status: The 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.
Image: 'Out of Control' Status Example
4. Upper Control Limit: The highest level of quality acceptable for a test (Calculation: Process mean + 3x the Standard Deviation).
5. Lower Control Limit: The lowest level of quality acceptable for a test (Calculation: Process mean - 3x the Standard Deviation).
6. Avg. Sample Size: The average number of tests conducted in the last 25 days where tests occurred.
7. Avg. # Nonconforming: The average number of tests conducted in the last 25 days were tests failed.
8. Total Sample Size: The total number of tests conducted in the last 25 days where tests occurred.
9. Total # Nonconforming: The average number of tests conducted in the last 25 days which failed.
10. Process Mean: The total number of tests failed/by the total number of tests conducted.
11. Standard Deviation: Measure to quantify the amount of variation within a set of data values.
12. Control Chart - P Chart: Plots the percentage of non-conforming over time. A P-Chart is used to look at variation in yes/no type attribute data. There are only two possible outcomes: either the item is defective or it is not defective. The P-Chart is used to determine if the fraction of defective items in a group of items is consistent over time.
A X-Bar Chart is used to monitor the mean of a process based on samples taken from the process at given times.
A R-Bar Chart indicates how the range of the subgroups changes over time. The range of a sample is simply the difference between the largest and smallest observation.
A S-Bar 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.
A P-Chart (Also known as P-Control Chart) is used in statistical quality control to graph the proportions of defective items.
Important Note on SPC Analysis
Variable Test:
For SPC Analysis to appear, you must complete 25 instances of that Variable Test. For example:
- Example 1: The Variable Test is completed 25 times in the 1 Monitoring Record. These 25 instances, must be completed in 25 different sample rows of the 1 Monitoring Record.
or
- Example 2: The Variable Test is completed 1 time in 25 different Monitoring Records. These 25 Monitoring Records can be completed in 1 day or over a number of different days.
Attribute Test:
For SPC Analysis to appear, you must complete 25 instances of that Attribute Test.
- The Attribute Test is completed 1 time in 25 different Monitoring Records. These 25 different Monitoring Records must be completed over 25 different days, resulting in 25 days worth of data.