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Sensor Data Intelligence is Microsoft Dynamics 365’s Latest IoT Update
Posted on: May 8, 2023 | By: Hope Jin | Microsoft Dynamics AX/365, Microsoft Dynamics Manufacturing
If you didn’t know, Microsoft has recently updated the IoT Intelligence feature in Dynamics 365 Supply Chain Management and has renamed it to Sensor Data Intelligence. Sensor Data Intelligence introduces a new deployment model where the required Azure components are deployed on your own Azure subscription rather than being managed by Microsoft. This new model enhances your ability to customize the feature and to integrate it with third-party systems. With this new update, Sensor Data Intelligence opens up new possibilities to optimize supply chain operations with ease. In this blog post, we will explore the capabilities of Sensor Data Intelligence and a couple scenarios of how it can enhance your supply chain management strategies.
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.
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:
- 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.
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