The Loop Report

About the Loop Report

The Loop Report provides a systematic approach to optimizing the performance of a control loop by monitoring the loop performance and providing diagnostic data about the loop. The report contains various charts and tables that help in assessing the performance of a control loop. The data used for assessing the performance of the loop is derived from the tags associated with the control loop assets.

Note: CLPM analytics process raw tag data and produce results that are interpolated. These interpolated results are then used to produce the Loop Report charts and tables.

Note: The measures presented in the Loop Report are derived from KPIs that are produced by CLPM analytics. Consult the KPI Reference for details on these KPIs.

Note: Unless otherwise stated, only data of good quality is considered when calculating the measures represented in these tables and charts. Bad quality data is ignored.

The Loop Report: Charts

The Loop Report contains the following charts:

Process Variable Performance
Manipulated Variable Distribution (%)
Control Overview
Error Distribution

The Loop Report: Tables

The Loop Report contains the following tables:

Control Mode Summary
Controller Performance
PV Performance
Error Statistics
Controller Configuration

Access the Loop Report

About This Task

This topic describes how to access the Loop Report from the module navigation menu.

Procedure

In the OPM navigation menu, go to Intelligence > Control Loop Performance.
The fleet dashboard appears, displaying the Average Control Loop Performance graph, diagnostic alerts filtering, and the Control Loop Performance Table on selecting the required asset in the Select Context window.
In the Control Loop Performance Table of an associated fleet report, select the link in the loop column.
The Loop Report appears, displaying the preconfigured widgets for graphs and tables. The report contains data for the selected asset context from the Fleet Report.
Note: If there is no context selected, select the required asset by selecting the Select Context tab in the header.
Note: Control Loop Performance reports are also accessible from the Dashboard menu.

Modify the Date for a Loop Report

About This Task

This topic describes how to modify the date for a Loop Report.

Procedure

Note: By default, the Loop Report is plotted with data reported for the current date. For example, when you directly access the loop report on 12th November, 2018 20:00:00, the dashboard is plotted with data reported from 12th November, 2018 00:00:00 to 12th November, 2018 20:00:00 (till the latest available data point). The loop report can be displayed for a time period of one day only.

Access the Loop Report whose date you want to modify.
The Date Selector box appears, displaying the default date. You can access data for a single day. Data is reported till the current time of the day. For example, if the current date and time is 20th November, 2018 20:00:00, and you select 20th November, 2018, then data is reported from 20th November, 2018 00:00:00 to 20th November, 2018 20:00:00. However, if the current date and time is 20th November, 2018 20:00:00, and you select 19th November, 2018, then data is reported from 19th November, 2018 00:00:00 to 20th November, 2018 00:00:00.
Select the Date Selector box.
The date selector window appears.
Select the date you want to set, and then select Apply.
The date is modified, and the report is updated. The date for which the data is reported appears in the upper-right corner of the report.
Tip: You can reset the date to the default value by selecting reset.

The Process Variable Performance Chart

The process variable performance (PVP) chart helps in analyzing the trend of the process variable (PV) against the setpoint (SP).

The chart contains the following axes:

x-axis: Represents the time period selected in the control loop report.
y-axis: Represents the PV and SP values.

The trend of each value over the selected time period appears as a step chart, which helps you understand the magnitude of change at a specific timestamp. The following trend lines are plotted on the chart:

Trend Line	Description
PV	A step chart representing the trend of PV over the time period selected in the report. Consult the CLPM Terminology table for the definition of the PV.
SP	A step chart representing the trend of SP over the time period selected in the report. Consult the CLPM Terminology table for the definition of the SP.
Upper Limit	A step chart representing the trend of the acceptable upper limit for the PV value. The Upper Limit on this chart represents the Upper SP Threshold KPI. Consult the KPI Reference for the definition of the Upper SP Threshold.
Lower Limit	A step chart representing the trend of the acceptable lower limit for the PV value. The Lower Limit on this chart represents the Lower SP Threshold KPI. Consult the KPI Reference for the definition of the Lower SP Threshold.

Interpreting the PVP Chart

Based on the values plotted on the PVP chart, you can identify performance issues in the process control loop. The following table lists a few scenarios that may appear in the chart and what each scenario indicates about the loop performance:

Note: If data for a tag is missing, a message appears at the top of the page, specifying the tag for which the data is missing.

What You See	Interpretation	Suggested Action
The trend of the PV values is centered around the trend of the SP values.	Process is under control.	None. Maintain the parameter settings.
The trend of the PV values exceeds the trend of the upper or lower limit.	Process is not under control.	Tune the control loop to reduce process variation.
Gaps in the trend line.	The plotted data contains a mix of good and bad quality data.	Investigate why the quality of some data is bad.
A flat trend line appears.	There has been no change in data for the time period selected. The last recorded value is maintained. -or- The connection to a real-time server has been lost.	Investigate why there is no change in data. Fix the connection to the real-time server.
An empty chart.	The quality of all the data for the selected time period is bad.	Investigate why the quality of data is bad.

The Manipulated Variable Distribution Chart

The manipulated variable distribution (%) chart is a histogram that helps you analyze the efficiency of a control element and evaluate the suitability of the element for the process.

A control element receives the output signal from the controller and controls the operating conditions such as flow, pressure, temperature, and liquid level in response to the signal. The manipulated variable (MV) is a percentage measure of the value at which the control element is functioning. For example, in the temperature control loop in an air conditioner, based on how much cooling is required (that is, setpoint), the thermostat (that is, the controller) sends a signal to manipulate the flow of cooling agent such that the room temperature (that is, the process variable) is adjusted to match the desired temperature. In this example, MV is the percentage of flow of cooling agent allowed through the valve.

The chart contains the following axes:

x-axis: Represents the value of the MV measured in percentage
y-axis: Represents the count of samples of the MV

The histogram represents the count of samples that the control element was set to at each percentage value, and not the length of time the element remained at each value. Therefore, you must always consider the distribution pattern of MV when interpreting the statistical significance of the samples displayed in this histogram.

Interpreting the Manipulated Variable Distribution Chart

Based on the values plotted on the chart, you can identify performance issues in the controller. The following table provides a few scenarios that may appear in the chart and what each scenario indicates regarding the controller performance.

Note: If data for a tag is missing, a message appears at the top of the page, specifying the tag for which the data is missing.

What you see	Interpretation	Required action
Red bars appear.	The samples can be interpreted as follows: < 6%: Indicates that the control element is operating at a very low saturation level and that the element is oversized. > 95%: Indicates that the control element is operating at a very high saturation level and that the element is undersized. A controller operating at the extreme high or low values of its capacity will result in asset fatigue over time.	Install a different type of controller, either a larger one that is more suitable for the purpose, or a smaller one that is more energy-efficient and cost-effective.
Yellow bars appear.	The samples can be interpreted as follows: 6% - 30%: Indicates that the control element is operating close to its lower saturation level. 71% - 95%: Indicates that the control element is operating close to its higher saturation level. A controller operating at high or low values of its capacity will result in asset fatigue over time.	Monitor the control element for signs of asset fatigue.
Blue bars appear.	The controller is operating at the desired capacity, that is, in the range of 31% through 70%. More samples in this range indicate that the controller is well-designed.	None. This is the ideal value.
Image displays a message stating that there is no data.	Data is not available for the selected time period.	Investigate if there is a loss of connection with the database.
An empty histogram appears.	The quality of all the data for the selected time period is bad.	Investigate why the quality of data is bad.
One trend interval (bin) appears with majority of data counts.	This indicates that there has been no data change, and that the last recorded value has been maintained. This can possibly occur as a result of loss of connection to a real-time server.	Verify and fix the connection to the real-time server.
Flat histogram, with no discernible peaks, appears.	The control element is operating over its whole range to control the PV. This typically indicates that the control element is too small for the system and will cause asset fatigue over time.	Optimize the size of the control element.

The Control Overview Chart

The control overview chart displays the trend of the manipulated variable (MV). The chart contains the following axes:

x-axis: Represents the time period selected in the report.
y-axes (two in number): Represent the MV value and the control mode in which the control loop was operating over the time period. The following table provides the number that represents each control mode:
Number Control Mode
1 Manual
2 Auto
3 Cascade
4 Shutdown

Number	Control Mode
1	Manual
2	Auto
3	Cascade
4	Shutdown

Trend lines appear in the following colors in the chart:

Blue: Indicates the control mode in which the system is operating. The control mode can change over the recording period.
Red: Indicates the trend of the MV value over the total calibrated range.

Interpreting the Control Overview Chart

Based on the values plotted on the chart, you can identify performance issues in the controller. The following table provides a few scenarios that may appear in the chart and what each scenario indicates regarding the controller performance.

Note: If data for a tag is missing, a message appears at the top of the page, specifying the tag for which the data is missing.

What you see	Interpretation	Required action
The blue trend line is set to Shutdown.	Indicates that the control element is in the Shutdown mode.	Ensure that the system is operating in the required control mode. Investigate causes of a change to Shutdown mode.
The red trend line indicates the MV percentage functioning value over the total calibrated range.	< 5%: Indicates that the control element is operating at a very low saturation level and that the element is oversized. 5 - 30%: Indicates that the control element is operating close to its lower saturation level. 30 - 70%: Indicates that the control element is operating at its optimal value. This is the ideal value for the variable. 70 - 95%: Indicates that the control element is operating close to its higher saturation level. > 95%: Indicates that the control element is operating at a very high saturation level and that the element is undersized.	Optimize the size of the controller.
The blue trend line is set to Bad.	The data was of bad quality and loop statistics could not be calculated.	Identify the reason for bad quality data. Check the connection to the server or database.
A report with no value for MV in the y-axis appears.	Either the MV has no data or the data is of bad quality.	Investigate which of these is true and why.
Gaps in the trend line appear.	Data was a mixture of good and bad quality.	Investigate why the quality of some data is bad.
A flat trend line appears.	There has been no change in data for the time period selected. The last recorded value is maintained. -or- The connection to a real-time server has been lost.	Investigate why there is no change in data. Fix the connection to the real-time server.
The Control Mode and MV values are responding quickly relative to the PV and SP values in the PV trend.	The control element has an appropriate reaction to changes in the PV.	None. The controller is well-tuned.
The Control Mode and MV values are responding very slowly relative to the PV and SP values in the PV trend.	The control element has a sluggish reaction to changes in the PV.	Tune the control loop PIDF parameters.

The Error Distribution Chart

The error distribution chart displays a histogram that represents the distribution of the amount of time the controller operated at each error value. Controller error is calculated as the difference between the values, PV and SP. The chart contains the following axes:

x-axis: Represents the controller error.
y-axis: Represents the time for which the controller was operating at the PV error value.

Interpreting the Error Distribution Chart

Based on the values plotted on the chart, you can identify performance issues in the controller. The following table provides a few scenarios that may appear in the chart and what each scenario indicates regarding the controller performance.

Note: If data for a tag is missing, a message appears at the top of the page, specifying the tag for which the data is missing.

What you see	Interpretation	Required action
The histogram bars appear in red.	The error is out of acceptable limits.	Control the PV so that it functions within the defined process limits.
The histogram bars appear in blue.	The error is in acceptable limits.	None.
Bimodal or oscillating distribution of histogram bars appears.	Possible friction exists in control element.	Check the functioning of the control element.
Histogram bars appear primarily in the higher error range.	Possible errors in loop tuning exist, or the control element is not working effectively.	Check the functioning of the control element. Tune the PIDF controller parameters.
One trend interval (bin) appears with majority of data counts.	There has been no change in PV error for the time period selected. The last recorded value is maintained. Or, the connection to a real-time server has been lost.	Investigate why there is no change in data. Fix the connection to the real-time server.
An empty histogram appears.	The quality of all the data for the selected time period is bad.	Investigate why the quality of data is bad.

The Control Mode Summary Table

The control mode summary table helps you assess the performance of the control loop based on the percentage of time the loop operated in each control mode. The table contains a row for each of the following control modes:

Manual
Auto
Cascade
Shutdown

The table contains the following information for each control mode:

Column name	Description
Duration (%)	Indicates the percentage of time the control loop operated in each controller mode. This is the average value of the Percentage <control mode> KPI.
Lower Limit Exceeded (%)	Indicates the percentage of time the loop operated below the lower limit. This is the average value of the Percentage <control mode> LL Exceeded KPI.
Upper Limit Exceeded (%)	Indicates the percentage of time the loop operated above the upper limit. This is the average value of the Percentage <control mode> UL Exceeded KPI.
Total Limits Exceeded (%)	Indicates the total percentage of time that the loop operated out of limit. This value is calculated as the sum of the Lower Limit Exceeded (%) and Upper Limit Exceeded (%) values.

Note: Consult the KPI Reference for the definition of each KPI referenced in the preceding table.

The last row in the table, Total, contains the sum of values in each column for all control modes, except the Shutdown mode.

In the Total row, if the value in the Duration (%) column is not 100%, it indicates missing data for the selected time period, possibly due to bad quality data.

The Controller Performance Table

The controller performance table helps you analyze the performance of the control element using a range of KPIs. It contains the following information.

KPI	Interpretation	Required action
Manipulated Variable [%]	The average value of the control variable, expressed as a percentage. < 5%: Indicates that the control element is operating at a very low saturation level and that the element is oversized. 5 - 30%: Indicates that the control element is operating close to its lower saturation level. 30 - 70%: Indicates that the control element is operating at its optimal value. This is the ideal value for the variable. 70 - 95%: Indicates that the control element is operating close to its higher saturation level. > 95%: Indicates that the control element is operating at a very high saturation level and that the element is undersized. This is the average value of the Percentage Controller Output KPI.	If the variable is not in the ideal range, install a different type of controller. Depending on the variable value, install either a larger controller that is more suitable for the process, or a smaller one that is more energy-efficient and cost-effective.
Total MV Movement	An indication of the absolute sum of all changes made in the MV. The closer the value for this variable is to zero, the closer the MV is to staying at a constant value. You can use this statistic to help you keep the PV operating within process limits. This is the average value of the Movement Index KPI.	Investigate and optimize the size of the control system.
Average MV Change [%]	The average percentage change in the MV between samples. The closer the value for this variable is to zero, the closer the MV is to staying at a constant value. This is the average value of the Control Amplitude KPI.	Investigate and optimize the size of the control system.
MV Oscillation Count [#]	The number of times that the MV changes direction. This indicates the level of noise in the system. The closer this value is to zero, the less noise there is in the system. All data is taken into account for this statistic, regardless of the quality. This is the average value of the MV Oscillation Count KPI.	Add a better filter to the control system.
Average oscillation amplitude [%]	The average percentage change in the MV before changing direction. 0: The closer this value is to zero, the closer the MV is to staying at a constant value. <5% Indicates a good control system. > 5%: Indicates a possibility of damage or failure, but must be viewed in conjunction with the number of controller oscillations. This is the average value of the Reversal Amplitude KPI.	Investigate and optimize the control element.
MV Saturation [%]	The percentage of the reporting window for which the controller output is saturated. The controller output is considered saturated when the MV has a value of 0 (the lower limit for controller output saturation) or 100 (the upper limit for controller output saturation). The closer this is to zero, the more likely it is that the control element is appropriately sized and functioning correctly. This is the average value of the Percentage MV Saturation KPI.	Investigate for a possibility of an undersized or oversized control element, a malfunctioning control element, or other causes for MV saturation, and optimize the control element.
Duration Not Utilized [%]	The percentage of the reporting window for which the loop is not in use. The loop is considered to be not in use if it is in manual mode or if the controller output is saturated. The controller output is considered saturated when the MV has a value of 0 (the lower limit for controller output saturation) or 100 (the upper limit for controller output saturation). The closer this is to zero, the more likely it is that the loop is in a mode other than manual and the control element is appropriately sized and functioning correctly. This is the average value of the Percentage Not Utilized KPI.	If the percentage of time not utilized is too high this can be for either or both of the following reasons: The loop spends a large proportion of time in manual mode. Investigate the reasons for that behavior. Investigate for a possibility of an undersized or oversized control element, a malfunctioning control element, or other causes for MV saturation, and optimize the control element.

Note: Consult the KPI Reference for the definition of each KPI referenced in the Interpretation column of the preceding table.

The PV Performance Table

The process variable performance table helps you analyze the performance of the process variable based on values as specified in the following table.

Column name	Interpretation
Average PV Limits exceeded	This value is an average of the percentage of time the PV exceeded the upper or lower limits. This is the average value of the Percentage Limits Exceeded KPI.
PV Variance [%]	This value is a measure of the average deviation of the PV from the average PV, expressed as a percentage of the reporting window span. This is the average value of the PV Variance KPI.
PV Variability	This value is an averaged measure of how spread or closely clustered the PV data set is, expressed as a percentage This is the average value of the PV Variability KPI.

Column name

Interpretation

Average PV Limits exceeded

This value is an average of the percentage of time the PV exceeded the upper or lower limits.

This is the average value of the Percentage Limits Exceeded KPI.

PV Variance [%]

This value is a measure of the average deviation of the PV from the average PV, expressed as a percentage of the reporting window span.

This is the average value of the PV Variance KPI.

PV Variability

This value is an averaged measure of how spread or closely clustered the PV data set is, expressed as a percentage

This is the average value of the PV Variability KPI.

Note: Consult the KPI Reference for the definition of each KPI referenced in the preceding table.

The Error Statistics Table

The error statistics table contains the statistics that indicate the extent at which the process variable deviates from the set point. The table contains the following values:

Measured variable	Interpretation
Integrated Error	This value indicates the percentage time the process has spent out of limits. If there is a substantial integrated error, investigate the functioning of the PV, and tune the system to maintain the PV within the defined limits. This is the sum of the Integrated Sum KPI values for the window.
Average Error	This value indicates the average tag error. Tag error is the difference between process variable and set point, expressed as a percentage. This is the average value of the PV Error Average KPI.
Average Absolute Error	This value indicates the average absolute value of the tag error. This is the average value of the PV Error Absolute Average KPI.
PV Error Standard Deviation	This value indicates the standard deviation of the tag error, where the tag error is the difference between process variable and set point, expressed as a percentage. This is the average value of the PV Error Standard Deviation KPI.

Note: Consult the KPI Reference for the definition of each KPI referenced in the preceding table.

The Controller Configuration Table

The controller configuration table contains the Proportional (P), Integral (I), Derivative (D), or Filter (F) values at the beginning and end of the selected time period.