Design and implementation of cluster management system for automatic screw machine based on Kubernetes

This paper proposes a design and implementation scheme for an automatic screwdriver cluster management system based on the Kubernetes cloud platform. To address issues such as low efficiency and unreasonable task allocation in the traditional manual management model, this study deploys the Machinekit system in LXD containers to achieve efficient cluster management and monitoring of multiple screwdrivers. An improved monotonic rate scheduling algorithm, QRM, is introduced to meet the real-time control requirements of the automatic screwdrivers. Experimental results show that, compared to manual management, the Kubernetes management model can significantly improve production efficiency by 42.86 %, validating the effectiveness of this scheme in enhancing the production efficiency and stability of automatic screwdrivers. This provides technical support for the development of automation and intelligence in the manufacturing industry.