Sensor Data Intelligence home page (preview)
[This article is prerelease documentation and is subject to change.]
Sensor Data Intelligence for Microsoft Dynamics 365 Supply Chain Management enables organizations to drive business processes in Supply Chain Management, based on Internet of Things (IoT) signals from machines and equipment on the production floor. It's an updated, renamed version of the IoT Intelligence feature that was previously available for Supply Chain Management.
Sensor Data Intelligence lets you perform the following tasks:
- Collect details from machines and equipment to update maintenance asset counter values in Supply Chain Management and drive predictive maintenance.
- Set up the solution by using a simple onboarding wizard instead of manually installing and configuring components in Microsoft Dynamics Lifecycle Services (LCS).
- Deploy components on your own subscription, so that you have more flexibility to manage Azure components.
- Configure, scale, and extend the solution as business logic that runs on Azure components. Those components are now managed on your own subscription. Therefore, you can customize them as required to meet your unique business needs.
Important
- This is a preview feature.
- Preview features aren’t meant for production use and might have restricted functionality. These features are subject to supplemental terms of use, and are available before an official release so that customers can get early access and provide feedback.
Business scenarios
Sensor Data Intelligence enables several types of functionality, each of which is represented by a specific scenario in the system. Each scenario provides a specialized set of configuration options in the system, as detailed in the following table.
| Scenario | Description |
|---|---|
| Asset downtime | Accurately track the efficiency of machine assets by using sensor data to track machine downtime. |
| Asset maintenance | Minimize maintenance cost and extend asset life by improving maintenance plans based on sensor readings of critical control points for machine assets. |
| Machine status | Ensure operation efficiency by using sensor readings to notify planners about machine outages and provide options for mitigating potential delays. |
| Product quality | Ensure the quality of product batches by comparing sensor readings for actual properties of each product batch, such as moisture, temperature, or custom-defined quality metrics. The system will notify users when deviations occur. |
| Production delays | Use sensor readings to compare actual cycle time to planned cycle time, and notify supervisors when production isn't on schedule. Supervisors can then intervene as required to ensure maximum operation efficiency. |
Architecture
The following architectural diagram provides an overview of the solution and its components.
Note
For more information about about how to connect sensors to the Azure IOT Hub, see Azure industrial IoT analytics guidance.