1：Experimental Design and Method Selection:

The architecture consists of four main units: measurement, data management, simulation, and control. The measurement unit uses image processing for position detection of modules. The data management unit uses asset administration shells for standardized data access and exchange. The simulation unit adapts the virtual system model based on position vectors and performs robot path planning. The control system reads necessary properties from the asset administration shells and sets new states for the devices.

2：Sample Selection and Data Sources:

The concept is evaluated within an experimental setup where a camera is attached to a six-axis robot mounted on a linear axis. The measurement field includes multiple data matrix codes in different well-known positions and rotations.

3：List of Experimental Equipment and Materials:

A monochrome camera with a 4.19 mega pixel sensor and a pixel size of 5.5 μm is used. The camera lens has a focus length of 8 mm and an aperture of 1.

4：19 mega pixel sensor and a pixel size of 5 μm is used. The camera lens has a focus length of 8 mm and an aperture of Experimental Procedures and Operational Workflow:

4. 4. Experimental Procedures and Operational Workflow: The workspace is scanned for available module codes. The position and orientation detection includes six axis of freedom. The image-processing algorithm is split into two sections: position detection and measurement of orientation.

5：Data Analysis Methods:

The deviations in x-, y-, and z-direction are measured, taking into account different radial distances to the camera’s optical axis. The deviation of rotation angles around the z-axis are also measured.