Alarm Benchmark Module By Konnection Introduction Overview Description

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1 Introduction 1 Overview 1 Description 1 Known Compatible Database Versions 1 Supported Ignition Versions 2 Component Listing 2 Getting Started 2 Requirements 2 How to Use 2 Terminology 2 Trial Limitations 2 Components 3 Component Common Features 3 How Alarm Metrics Are Calculated 3 Behavior Properties 4 Data Properties 4 Extension Functions 5 Filter Properties 5 Initial Setup 7 Troubleshooting 8 There is an error with querying the database. 8 Component returns no results. 8 Component doesn t show accurate results. 8 Contact Us 8 Alarm Benchmark Module By Konnection Introduction Overview Description The alarm benchmark module provides a series of components that provide users with metrics that allow them to benchmark their alarm system and refine it. This module uses the data stored in a SQL database by Ignition s alarming system. Known Compatible Database Versions SQL Server 2012 MySQL 5 Oracle 12C

2 Other versions of SQL Server, MySQL, and Oracle may be compatible. Listed above are only the versions which have been explicitly tested. Users are encouraged to try other versions however. Supported Ignition Versions 7.8 Component Listing Alarm Benchmark Controller Getting Started Requirements To use the alarm benchmark module, the user must have created a database connection with a database type/version supported by this module on the Ignition installation where the alarm benchmark module is installed. There must exist the tables named alarm_events and alarm_event_data in the target database as they were created by Ignition s alarming system. Once these alarm tables exist in the database, the user can start using the alarm benchmarking components. It is recommended that the Ignition installation s alarming system has been in use so that there is adequate alarm data present to benchmark. The Alarm Benchmarking module requires that the reporting module be installed on the gateway to function. The reporting module need not be licensed however. How to Use Drag any component from the alarm benchmarking module tab onto the screen in the designer. Set the Datasource property to the database connection associated with the alarming system by using the dropdown list on the property. Set any filters or additional properties (see Properties section) and then set the Querying property to true. Data should now populate the component. Terminology Flooding A flood event occurs when a large number of alarms become active in a short period of time. A flood event begins when the number of alarms that have become active in a 10- minute period exceeds ten alarms and ends when the number of alarms becoming active per 10-minute period falls below five. Chattering A chattering event occurs when a single alarm becomes active and then clears frequently. If an alarm becomes active and clears three times within a single minute, then it is chattering. Stale A stale alarm is one that has been active for 24 hours or more. Trial Limitations An alarm benchmarking module installation that is still in trial mode is subject to two restrictions: 1. When the two hour demo period expires, the component will not be able to query the database and will have the trial overlay in both the designer and client until the trial is reset. 2. The number of alarms queried from the database will be limited to 30 for any given query. To remove these restrictions, please purchase a full copy of the alarm benchmarking module.

3 Applying Database Indexes In order for the Alarm Benchmarking module to efficiently get alarm data, the database needs to have indexes configured on the alarm_events and alarm_event_data table. Below will be some example indexes and keys to apply to those tables for MSSQL, MySQL, and Oracle. The configuration need not exactly match what is listed below. Any similar configuration will most likely suffice. Your particular needs may call for different configuration. MSSQL: ALTER table alarm_events ADD CONSTRAINT PK_alarm_events_id PRIMARY KEY CLUSTERED (id) MySQL: CREATE NONCLUSTERED INDEX IX_alarm_events_eventid ON [dbo].[alarm_events] ([eventid]) INCLUDE ([eventtype],[eventtime], [priority], [source], [displaypath] ) ALTER TABLE alarm_event_data ADD CONSTRAINT FK_alarm_event_data_alarms_events FOREIGN KEY (id) REFERENCES alarm_events(id) CREATE NONCLUSTERED INDEX IX_alarm_event_data ON [dbo].[alarm_event_data] (propname) INCLUDE ([dtype],[intvalue], [floatvalue], [strvalue]) ALTER TABLE alarm_events ADD PRIMARY KEY (id) CREATE INDEX IX_alarm_events_eventid ON alarm_events(eventid) USING BTREE ALTER TABLE alarm_event_data ADD FOREIGN KEY (id) REFERENCES alarm_events(id) CREATE INDEX IX_alarm_event_data_propname ON alarm_event_data(propname) USING BTREE Components Component Common Features How Alarm Metrics Are Calculated Most number of alarms in an interval/percent of x in time interval This appears several times in the alarm benchmarking module. It is calculated using fixed windows. For example, if calculating the most number of alarms in a 10-minute period then the alarm benchmarking component will only look at the periods with minutes 00 to 10, 10 to 20, 20 to 30, and so on. The 10-minute period with the most alarms will never be 12:12:00 to 12:22:00, but it could be 11:30:00 to 11:40:00. Presently the alarm benchmarking module only uses alarms that have already cleared for analysis purposes.

4 Behavior Properties Datasource Name Tells the component which database connection to use when querying for alarms. Data Properties Average Alarms Per 10-Minute Interval Average number of alarms per ten-minute interval. Uses fixed intervals for calculations. Example: 4:00 to 4:10 but never 4:05 to 4:15. Average Alarms Per Flood Average number of alarms per instance of flooding. Average Alarms Per Day Average number of alarms per ten-minute interval. Uses fixed intervals for calculations (midnight to midnight). Average Daily Alarms Without Chatter Average daily alarms excluding all chattering alarms. Useful for comparison against regular daily rate. Average Alarms Per Hour Average number of alarms per ten-minute interval. Uses fixed intervals for calculations. Example: 3:00 to 4:00 but never 3:05 to 4:05. Number of Alarms By Day Number of alarms grouped by the day in which they occurred. Number of Alarms By Hour Number of alarms grouped by the hour in which they occurred. Max Alarm Count In Any Flood The count of alarms in the ten-min interval where there were the most alarms while the system was experiencing a flood condition. Most # Alarms in Day Interval The most number of alarms that have occurred in any day. Most # Alarms in Hour Interval The most number of alarms that have occurred in any hour. Most # Alarms in Ten Minute Interval The most number of alarms that have occurred in any ten-minute interval. Most Stale Alarms in A Day The most number of stale alarms that occurred in any day. Total Number of Alarms The total number of alarms for the selected criteria. Total Number of Floods Number of times the system was in a flood condition. Alarms Occurrences Chattering The number of alarm occurrences among all chattering events. For instance, an alarm may go active 5 times in 30 seconds. This constitutes a single chattering event that had 5 alarm occurrences. Number of Stale Alarms The number of stale alarm occurrences. Number of Unique Chatter Alarms Number of unique alarms that have chattered (unique by alarm source path). Percent Ten Most Frequent Alarms Percent of the ten most frequently occurring alarms out of all alarms occurrences. Percent of Critical Priority Alarms Percent of critical priority alarms out of all alarms occurrences. Percent of Diagnostic Priority Alarms Percent of diagnostic priority alarms out of all alarms occurrences. Percent of High Priority Alarms Percent of high priority alarms out of all alarms occurrences. Percent of Hours More Than 30 Alarms Percent of hours that contain more than 30 alarms. Percent of Low Priority Alarms Percent of low priority alarms out of all alarms occurrences. Percent of Medium Priority Alarms Percent of medium priority alarms out of all alarms occurrences. Percent of Alarms Chattering Percent of all alarms occurrences that are considered chattering.

5 Percent of Time in Flood Percent of time that the system is in a flood state. Percent Ten Minute Intervals With More Than Ten Alarms -- Percent of ten-minute intervals where more than 10 alarms occurred. Pie Chart Data Grouped By Associated Data Dataset suited for use in a pie chart where the alarms have been grouped by their associated data value. Pie Chart Data Grouped By Priority Dataset suited for use in a pie chart where the alarms have been grouped by priority. Stale Alarms Cumulative Dataset of overall characteristics of stale alarms that have occurred. accumulatedtime is the duration this alarm has been active during every it has been stale (given in minutes). count describes the number of times this alarm has been stale. Stats By Source Path Dataset of statistics on a per source path basis. o count The number of times this alarm has been active. o duration Total amount of time this alarm has been active, given in minutes. o chatterevents The number of chatter events this alarm has produced. o numalarmschattering The number of times this alarm has gone active during its chattering events. Number of Alarms By 10-Minute Intervals Number of alarms grouped by the ten-minute interval in which they occurred. Total # Chattering Events Number of chattering events that have occurred. For instance, an alarm may go active 5 times in 30 seconds. This constitutes a single chattering event that had 5 alarm occurrences. Total # Alarms in All Floods Number of alarms summed between all flood events. Querying This property is true when the component is trying to query against the database. No changes to other properties will be reflected in a component s dataset until this property is set to true and the database is queried again. If the user would desire the alarm benchmarking components to poll then this property can be bound to a timer component. Extension Functions evaluateresults This functions gives the opportunity add dynamic properties to the component. This function should return a dictionary whose keys are the desired property names and whose values are the properties' values. Permissible datatypes for values are Short, Long, Double, Float, Integer, Dataset, Date, String, and Color. Arguments: self This argument is a reference to the component itself. results This argument is all the data of the component given as a map. Filter Properties Date Filter Tells a component whether or not to filter by date when querying the database for alarms. This property is only on some components. If it is false and the module is not in trial mode then data will be returned on all alarms regardless of when they occurred. Start Date and End Date Component will only return alarms between these dates as specified in the How Alarm Metrics Are Calculated section. Alarm Name Filter Filters alarms by name. Source Path Filter Filters alarms by source path. Display Path Filter Filters alarms by display path.

6 Associated Data Name Filters by the names of associated data properties on alarms. All filters which are strings, except the Associated Data Name filter, use typical SQL syntax for wildcards: the percent sign. A filtering string is not case sensitive and will look for an exact match. For example, if an alarm name is Motor Run Fault and the user sets the alarm name filter to Run' then the alarm will not be returned. However, if the user instead enters %Run%, %run%, or Motor Run Fault then the alarm will be included.

Initial Setup The following screenshot shows how the alarms could be configured. In this case, the conveyor UDT has an AlarmWord tag, each bit representing an alarm.

7 Initial Setup The following screenshot shows how the alarms could be configured. In this case, the conveyor UDT has an AlarmWord tag, each bit representing an alarm. There are four alarms configured based upon this tag. Each one of them has an appropriate priority assigned as well as two Associated Data properties. Only one Associated Data property is necessary but this demonstration shows how the Pie Chart data could show specific classes of alarm or general classes of alarms. For example, the Class property is basically the name of the alarm. However, the Category property is a more general grouping of the alarms. The 10% and 20% Slowdown alarms are in the category, Hazard Monitoring. Likewise,

8 the Plug Switch alarm is in the category, Safeties. Any number of Associated Data properties can be added to use. Troubleshooting There is an error with querying the database. Check that the database connection being used by the component has the tables alarm_events and alarm_event_data. Check that the database version/type being used is supported by the alarm benchmarking module. Check that the database connection is enabled and not faulted. Component returns no results. Check to see if the datasource property is set to a database that contains alarms and that the alarms in the database fit the criteria specified by the filters on the component. Are the start and end date set to a time period with alarms? Component doesn t show accurate results. Review the section on How Metrics Are Calculated. If the module is still in trial, then the results will be limited to a small set of the alarms in the database so it may not appear correct. Contact Us If you believe that you have found a bug or would like to give Konnection feedback on the Alarm Benchmarking Module, then you can developer@konnection.com.

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