Update digital_twin.md

Author: Penubakula

docs/twin/digital_twin.md

@@ -12,10 +12,9 @@ Additionally, the Digital Twin Core contains three essential supporting services
 
 The Change Handler serves as an intermediary layer between the Agent Control and data integration on one side and the State Model on the other, ensuring all state changes are validated and consistent. Model Learning provides basic functionalities for machine learning, enabling the system to learn from historical data. Repository Services provide the capability to persist the State Model, ensuring long-term data retention, versioning, and recoverability of the entire system state.
 
-<div align="center">
-  <img src="../assets/imgs/twin.png" width="500" height="300" alt="Schematic Structure Twin" />
-  <h3>Schematic Structure Twin</h3>
-</div>
+![Schematic Structure Twin](../assets/imgs/twin.png)
+
+### Schematic Structure Twin
 State Model
 The State Model contains the data model of the environment (production and logistics). The idea is that each scenario has its own state model object. This means that no distinction is made between scenarios that reflect the physical world and virtually generated simulation scenarios. In both cases, changes from the environment are included in the state model in the same way (however, in some cases through passing the agents first). Next to environment the planning services such as the factory planner or the scenario analytics are based on the state model. While the "static" state model is the output of the factory planner, the state model serves as input for the scenario analytics. Concluding, the state model is connected to all areas of the digital twin framework.