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Oracle IoT Production Monitoring Cloud Service

In this learning path, you create the required entities for configuring the Oracle IoT Production Monitoring Cloud Service. You set up entities, floor plans, create custom Key Performance Indicators(KPIs), rules, and anomalies. You also monitor the performance of factories and machines.

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beginner Beginner
duration 19 Min
modules 6 Modules

Learning Path Contents

Module Sections Topics and more

  • Introduction
      duration 0 Min
    After completing this learning path, you will be able to configure the required entities for Oracle IoT Production Monitoring Cloud Service. You will also be able to monitor all of the created business entities and view results.
    • In Oracle IoT Production Monitoring Cloud Service, you can create entities that represent factory models, and any type of machines and sensors. When all the previous entities are created, you can monitor them and simulate different scenarios to trigger rules.

  • Production Monitoring Simulator Setup
      duration 5 Min
    Use the Production Monitoring simulator to create the entities you need to test the functionality of the Production Monitoring application. You’ll use the existing Tablet factory model to create a factory with machines, products, and sensors. After you have created the simulated factory and associated business objects, you will open the Production Monitoring application and upload a factory floor plan and place machines within the plan, you'll also review the production plan for the day.
  • Monitor Factory and Machines Performance
      duration 5 Min
    Use the Production Monitoring application to identify the factory that is not meeting the production targets specified in the production plan. You'll also identify the specific machine within the factory that is causing the production delays. You’ll use the Production Monitoring simulator to correct the issues with the machine and eliminate the production delays. To achieve these objectives, You’ll complete these tasks: 1) Monitor factory and machine performance in real-time, 2) Identify the factory that is not meeting the production targets, and 3) Identify the machine causing the production delay.
  • Create Custom KPIs
      duration 3 Min
    Use an expression builder to create custom key performance indicators (KPIs) to monitor factory and machine performance. To create my custom KPIs, you’ll create a custom KPI to identify factories that not meeting the production quotas defined in the production plan, and create a custom KPI to identify the number of idle machines.
  • Create Rules
      duration 3 Min
    Create rules that generate incident or warning messages when the conditions defined in the rules are met or exceeded. To achieve these objectives, you’ll create a rule that generates an incident when glue viscosity falls below a set threshold.
  • Create Anomalies
      duration 2 Min
    Create an anomaly that helps you determine why a factory is under performing. To achieve this objective, you’ll create a factory level anomaly using sensor data from the machine down metric.