UC-Digital Twin for Lifecycle Stage Tracking

Description

This use case enables organizations to represent every key product, module, or component as a digital twin. Each twin is enriched with metadata such as current lifecycle phase, responsible owner, and geographical region. The system actively tracks these assets through their entire lifecycle — from development to retirement — and issues real-time alerts on critical lifecycle events such as:

• End-of-Life (EOL) risk,

• Quality issue recurrence, or

• Scheduled upgrade windows.

It provides stakeholders with real-time visibility, proactive alerting, and workflow automation, allowing informed decision-making and faster responses throughout the product lifecycle.

Actors

• Product Manager: Monitors lifecycle phases and risks; initiates lifecycle transitions.

• Quality Engineer: Analyzes recurring quality issues and responds to alerts.

• Manufacturing Lead: Coordinates production updates based on lifecycle status.

• IT Administrator: Manages digital twin infrastructure and integrations.

• Support Engineer: Acts on alerts regarding upgrade needs or obsolescence.

• Automation System (Power Automate): Triggers notifications and workflows.

Preconditions

• Digital representations (twins) of all products/modules are created and registered in Azure Digital Twins.

• Lifecycle metadata (phase, region, owner) is populated and synced from Dataverse.

• Rules and thresholds for lifecycle events (e.g., EOL, upgrade window) are defined.

• Integration between Azure Digital Twins, Power BI, Power Automate, and Dataverse is configured.

Flow of Events

1. Initialization:

   • Digital twins are modeled in Azure Digital Twins with metadata from Dataverse.

   • Lifecycle rules and alerts are defined in the system.

2. Monitoring:

   • Twins continuously track lifecycle stages in real-time.

   • Metadata changes (e.g., ownership transfer, phase shift) are logged automatically.

3. Event Detection:

   • Events such as EOL proximity, repeated quality issues, or missed upgrade windows are detected.

4. Notification & Response:

   • Power Automate triggers alerts to relevant actors via email, Teams, or dashboards.

   • Support or Product Managers initiate corrective or transition actions.

5. Analysis & Optimization:

   • Power BI dashboards visualize lifecycle distribution, bottlenecks, or risks.

   • Teams use insights to make proactive decisions (e.g., schedule upgrades, prioritize redesigns).

Postconditions

• Lifecycle transitions are proactively managed.

• Product risks and upgrade windows are addressed in time.

• Quality and support issues are resolved faster due to early alerts.

• Accurate and real-time visualization of product status across lifecycle.

Benefits

• Improved traceability of product lifecycle stages across global teams.

• Early warning system reduces operational disruptions.

• Enables predictive and preventive decision-making.

• Reduces cost associated with late upgrades or EOL failures.

• Supports collaborative planning among R&D, manufacturing, and support.

Tools & Technology Used

• Azure Digital Twins: Core platform for modeling and monitoring digital twins.

• Power BI: Visualizes lifecycle data, events, and performance metrics.

• Power Automate: Automates alerts, escalations, and workflow triggers.

• Dataverse: Central metadata repository linked to product and lifecycle data.