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docs: Simplified README.md updated arch diagram #8
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| # Real-Time Intelligence for Operations Solution Accelerator | ||||||
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| This solution accelerator provides the architecture and working solution for real-time intelligence for operations. We used simulated manufacturing facility asset data for the process flow. Historical and real-time performance measures such as speed, vibration, temperature, humidity, and defect probability are reported in a real-time intelligence dashboard. As real-time events are streamed in, anomalies are detected with notifications sent to a specified Outlook email account. The solution includes a customized Fabric Data Agent that provides a chat experience to answer users' questions with intelligence derived from the data. | ||||||
| This solution accelerator provides the architecture and working solution for real-time intelligence for operations. We used simulated manufacturing facility asset data for the process flow. As real-time events are streamed in, anomalies are detected with notifications sent to a specified Outlook email account. The solution includes a customized Fabric Data Agent that provides a chat experience to answer users' questions with intelligence derived from the data. | ||||||
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| **Key use cases include:** | ||||||
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@@ -21,7 +21,7 @@ This solution accelerator provides the architecture and working solution for rea | |||||
| Solution overview | ||||||
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| This solution accelerator provides a working solution for manufacturing asset performance monitoring, real-time anomaly detection, and anomaly notification. The manufacturing facility telemetry data is synthetically generated with the `Telemetry Data Simulator`. This architecture can be extended to other industries as long as the appropriate data is generated or actual operations data is ingested into the `Event Hub`, and related component configurations and Kusto Query Language (KQL) code are updated accordingly. For a brief description of the architecture, please refer to [Solution Architecture Overview](./docs/TechnicalArchitecture.md). | ||||||
| This solution accelerator provides a working solution for manufacturing asset performance monitoring, real-time anomaly detection, and anomaly notification. The manufacturing facility telemetry data is synthetically generated with the `Telemetry Data Simulator`. This architecture can be extended to other industries as long as the appropriate data is generated or actual operations data is ingested into the `Azure Event Hub`, and related component configurations and Kusto Query Language (KQL) code are updated accordingly. For a brief description of the architecture, please refer to [Solution Architecture Overview](./docs/TechnicalArchitecture.md). | ||||||
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| This solution accelerator provides a working solution for manufacturing asset performance monitoring, real-time anomaly detection, and anomaly notification. The manufacturing facility telemetry data is synthetically generated with the `Telemetry Data Simulator`. This architecture can be extended to other industries as long as the appropriate data is generated or actual operations data is ingested into the `Azure Event Hub`, and related component configurations and Kusto Query Language (KQL) code are updated accordingly. For a brief description of the architecture, please refer to [Solution Architecture Overview](./docs/TechnicalArchitecture.md). | |
| This solution accelerator provides a working solution for manufacturing asset performance monitoring, real-time anomaly detection, and anomaly notification. The manufacturing facility telemetry data is synthetically generated with the `Telemetry Data Simulator`. This architecture can be extended to other industries as long as the appropriate data is generated or actual operations data is ingested into the `Event Hub`, and related component configurations and Kusto Query Language (KQL) code are updated accordingly. For a brief description of the architecture, please refer to [Solution Architecture Overview](./docs/TechnicalArchitecture.md). |
Copilot
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Dec 1, 2025
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Typo: "EventHouse" should be "Eventhouse" (consistent with line 64 usage and Fabric terminology). The capitalization of "EventHouse" appears incorrect.
Copilot
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Dec 1, 2025
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Redundant phrase: "for details" appears twice in the same sentence ("For details, please refer to Fabric Data Agent Guide for details"). Remove one occurrence.
| - For manufacturing plants, the plant manager or other business stakeholders can use the Fabric Data Agent to get business and operations intelligence quickly without the need to create query code. For details, please refer to [Fabric Data Agent Guide](./docs/FabricDataAgentGuide.md). | |
| - For manufacturing plants, the plant manager or other business stakeholders can use the Fabric Data Agent to get business and operations intelligence quickly without the need to create query code. Please refer to [Fabric Data Agent Guide](./docs/FabricDataAgentGuide.md) for details. |
Copilot
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Dec 1, 2025
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Extra space before the period. The line has two spaces after "dashboard" and before the period, which should be reduced to one space for proper formatting.
| The image below shows the first page of the real-time intelligence operations dashboard, which displays sensor status, quality metrics, and individual sensor data trends. The second page shows additional information such as daily anomaly rate by asset, asset maintenance status, and fault correlations. For more details, please refer to [Real Time Intelligence Operations Dashboard Guide](./docs/RealTimeIntelligenceDashboardGuide.md). | |
| The image below shows the first page of the real-time intelligence operations dashboard, which displays sensor status, quality metrics, and individual sensor data trends. The second page shows additional information such as daily anomaly rate by asset, asset maintenance status, and fault correlations. For more details, please refer to [Real Time Intelligence Operations Dashboard Guide](./docs/RealTimeIntelligenceDashboardGuide.md). |
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[nitpick] The sentence has been modified to remove "Historical and real-time performance measures such as speed, vibration, temperature, humidity, and defect probability are reported in a real-time intelligence dashboard." This removes valuable specific information about what metrics are tracked in the dashboard. Consider keeping this detail as it helps users understand the solution's capabilities.