Oracle by Example brandingMonitor Factory Operations in an Oracle IoT Production Monitoring Cloud Service Application

section 0Before You Begin

This 15-minute tutorial shows you how to monitor the performance of machines in a factory by using the Oracle Internet of Things (IoT) Production Monitoring Cloud Service application, and get started as a factory manager.

This is the third tutorial in Quick Start Tutorials for the Oracle IoT Production Monitoring Cloud Service Application. Read the tutorials sequentially.

Background

Vision Corp., a manufacturer of tablets and smartphones, has implemented the Oracle IoT Production Monitoring Cloud Service application to improve the yield, quality, and reliability of the products that are manufactured in the factory. The machines in the factory are the display picker, glue dispenser, and display mounter. The application is configured to detect anomalies, trigger incidents, display the historical and current values of the sensor data, and display the status of the incidents.

In this tutorial, you monitor the machines and factories in the Oracle IoT Production Monitoring Cloud Service application by viewing existing metrics, and defining custom metrics. You use a simulator application that generates data about the machines and factories.

What Do You Need?

section1 Monitor Factory Performance

In this section, you change the status of several machines in a factory by using the Oracle IoT Production Monitoring simulator application. You then monitor the performance of that factory in the Oracle IoT Production Monitoring Cloud Service application.

  1. Sign in to the Oracle IoT Production Monitoring Simulator application at https://your Oracle IoT Cloud Service instance name/pm-sim.
  2. On the Production Monitoring Dashboard page, click Tablet Factory.
  3. On the Tablet Factory Model page, click SF Factory.
  4. On the Factory: SF Factory page, for one display picker machine, one glue dispenser machine, and one display mounting machine, click Down.
  5. Sign in to your instance of the Oracle IoT Production Monitoring Cloud Service application.
  6. Click Menu Menu icon, and then click Map. On the map, zoom in on San Francisco, and then click SF Factory SF Factory icon.
  7. Notice that the metrics ribbon displays the Factory Metrics section and Machine Metrics section for SF Factory. Observe that in the Machine Metrics section, the Down metric displays 50% because three machines in SF Factory are down.
    Metrics of SF Factory
    Description of the illustration metrics_ribbon.png
  8. To view the SF Factory metrics for the past 24 hours or more, click Comparative View Comparative View icon. From the Time Period drop-down list, select 24 hrs.
    Metric Details of SF Factory
    Description of the illustration metric_details.png
  9. To go back to the map view, click Comparative View Comparative View icon.

section 2 Compare Factory Performances

In this section, you view the comparative analysis data for SF Factory and SJ Factory.

  1. On the map, zoom out to ensure that you see SF Factory and SJ Factory. On the metrics ribbon, verify that the Factories metric displays 2. Notice that the Down metric displays 25% because 3 of the 12 machines are down.
  2. On the metrics ribbon, click Down, and then click Comparative View Comparative View icon.
  3. Examine the comparative data of the factory metrics and machine metrics for the two factories. In the Factories Behind Plan section, observe that SJ Factory is performing better than SF Factory.
    Metric Details of SF Factory
    Description of the illustration comparative_metrics_data.png
  4. Click Historical View Historical View icon, and then in the Factory Metrics section, select the Factories Behind Plan metric. Notice that the graph displays an overlay of the Best Factory instance that enables you to do a comparative analysis.
    Metrics in Graph Format
    Description of the illustration chart_view.png
  5. Navigate to the Oracle IoT Production Monitoring Simulator application at https://your Oracle IoT Cloud Service instance name/pm-sim.
  6. On the Factory: SF Factory page, for the three machines that are down, click In Use. The Quantity value for the machines increases.
  7. After a few minutes, navigate to the Oracle IoT Production Monitoring Cloud Service application. Click Menu Menu Icon, and then click Map.
  8. On the map, zoom out to ensure that you see SF Factory and SJ Factory. In the Factory Metrics section, verify that the value of the Factories Behind Plan metric decreased because the three machines restarted production.
  9. In the Machine Metrics section, verify that the value of the In Use metric increased to 100%.

section 3 Diagnose Machine Performance

In this section, you examine a machine's performance, and troubleshoot the cause of its low performance.

  1. Click Menu Menu Icon, and then click Map. Zoom in on San Francisco, and then click SJ Factory Factory Icon.
  2. On the metrics ribbon, in the Machine Metrics section, click Machine Behind Plan. Record the value displayed on the SF_Factory_Glue Dispensing_M2 SF_Factory_Glue Dispensing_M1 icon machine that appears on the floor plan.
  3. To view the sensor values and metrics, click SJ_Factory_Glue Dispensing_M2 SF_Factory_Glue Dispensing_M1 icon.
  4. On the Machine: SJ_Factory_Glue Dispensing_M2 page, modify the values in the Time Period drop-down list, and observe the changes in the metric values.
  5. Click the Sensor Sensor icon tab, and then from the Sensor Attributes drop-down list, select glue_temperature, flow_rate, and glue_viscosity.
  6. In the Add Comparative Data Changes options, select State Changes, and then from the Time Period drop-down list, select LIVE.
  7. Monitor the data for the glue dispenser machine. Notice that the glue viscosity is high and the glue flow rate is low.

    Note: In the simulator, you can increase the glue temperature to reduce the glue viscosity, and then consequently, the glue flow rate increases.

    Sensor Attributes in a Graph
    Description of the illustration sensor.png
  8. Sign in to the Oracle IoT Production Monitoring Simulator application at https://your Oracle IoT Cloud Service instance name/pm-sim, and then on the Tablet Factory Model page, click SF Factory.
  9. On the Factory: SF Factory page, scroll down to the SJ_Factory_GlueDispensingM2 machine, and select 300F. After a few minutes, verify that the Quantity value increases.
  10. Navigate to the Oracle IoT Production Monitoring Cloud Service application. Click Menu menu icon, and then click Map.
  11. On the map, zoom in on San Francisco, and then click SJ Factory Factory Icon. In the Machine Metrics section, click Machine Behind Plan. Notice that the metric value that is displayed on SJ_Factory_Glue Dispensing_M2 SF_Factory_Glue Dispensing_M1 icon is less than the value you recorded in Step 2.
  12. Repeat Steps 3 through 7, and then in the graph, notice the increase in the temperature, decrease in the glue viscosity, and rise in the glue flow.
  13. To go back to the factory floor plan, click outside the machine details page.

section 4Create a Custom Metric for a Factory

System metrics are predefined in the application and cannot be edited, deleted, or cloned. In this section, you create a custom metric to retrieve the count of the factories that lag behind in production. You use the Behind Plan system metric to create the custom metric.

  1. Click Menu Menu Icon, and then click Configuration.
  2. On the Configurations page, click the Metrics Metrics Icon tab. The list of metrics is displayed.
  3. Click Create New Create New Icon, and then on the Create Metric page, in the Details section, enter or select the following values:
    • Name: Slacking Factories
    • Entity Type: All Factories
    • Metric Type: Query
    • Calculate: On Schedule for All Factories
    • Calculate: Live
  4. To retrieve the count of the factories, that have a Behind Plan metric that is greater than 50, in the Formula section, click Count, and then click the Add Filter button.
  5. Next to Add Filter Property Icon, click Formula Menu Brackets Icon, and then select Property, Metric, and then Behind Plan.
  6. In the Behind Plan Metric, from the Product drop-down list, select Tablet.
  7. Click Formula Menu Brackets Icon, click Operators, and then select >.
  8. Click Formula Menu Brackets Icon, click Number Number Icon, and then enter 50.
    Formula of the Custom Metric
    Description of the illustration formula.png
  9. Click Validate Formula and ensure that you receive the Validate OK message.
  10. Click Save, and then click Publish. Wait until the message Publishing KPI Metrics - Pending modifies to Publishing KPI Metrics - Activated. Click Back.
  11. On the Configuration: Metrics page, verify that the Slacking Factories metric is displayed in the list of metrics.

section 5Display the Custom Metric

In this section, you add the custom metric to the dashboard, and then use the custom metric to monitor factories.

  1. Click Menu Menu Icon, and then click Map.
  2. On the map, click Dashboard Edit icon.
  3. In the Factory Metrics page, click Edit Edit icon, and then click Add New Gadget Add icon.
  4. On the Create Metric page, select the following, and click OK:
    • Metric: Slacking Factories
    • Label: Slacking Factories
    • Unit: Orange
  5. Verify that on the Factory Metrics page, the Slacking Factories metric is visible. Click Save.
    Edit Metrics Page
    Description of the illustration edit_metrics.png

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