DIGITAL TWIN DATA STORAGE FOR INDUSTRIAL ROBOT KINEMATICS
DOI:
https://doi.org/10.32782/tnv-tech.2024.4.10Keywords:
Digital Twin, Data Storage, Industrial Robotics, Kinematics, Denavit-Hartenberg Method.Abstract
In response to the increasing demand for efficient and automated production processes, Digital Twins have emerged as a vital tool for optimising industrial operations and preemptively identifying equipment issues. An important component of the Digital Twin is the storage of historical data on equipment operation. This research focuses on developing a universal database structure for storing position data of various industrial robots, including Cylindrical, SCARA, Articulated, and Cartesian/Gantry robots. The proposed database uses the Denavit-Hartenberg (DH) method, widely recognised for representing robot kinematics. Combining the Denavit-Hartenberg method with relational database technology provides a flexible and scalable solution for managing the diverse and complex data associated with robot configurations. This structure makes it possible to apply this development in industrial environments where robots with different degrees of freedom and different kinematic chains are used. The combination of the Denavit-Hartenberg method with relational database technology provides a flexible and scalable solution for managing diverse and complex data related to robot configurations. The database design supports the creation of Digital Twins for industrial robots, facilitating enhanced operational monitoring, predicting maintenance, identifying wear patterns, detecting abnormal behaviour and predicting potential equipment failures. This approach minimises downtime and extends the lifetime of robotic systems, which ultimately contributes to sustainable production and is in line with the concept of Industry 4.0. In this study, we present a database framework specifically for storing data on the position of equipment nodes. The created entities allow storing data on the position of each robot node. When the position of a node changes, only those Denavit- Hartenberg parameters that have changed are stored in the database. This allows you to optimise memory usage without losing the collected data. The database structure can be expanded by adding data from other sensors installed on the robot or other peripheral devices, or data generated by the Digital Twin. Further research will test the effectiveness of the database structure.
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