Aiming at the pain points faced by small and medium-sized manufacturing enterprises, including long adaptation cycles of traditional intelligent production lines, strong device heterogeneity, and high line-changeover costs, this study proposes an easily deployable digital twin system architecture based on low-cost sensors and universal industrial equipment. The research integrates modular design concepts with OPC UA protocols to construct a cross-platform data interaction framework supporting Modbus hybrid communication, achieving second-level real-time synchronization between physical entities and virtual models (latency ≤ 0.8 s). By leveraging the Visual Component simulation platform deeply integrated with Siemens S7-PLC, the work establishes a full-chain technical system encompassing 3D modeling, motion logic programming, and virtual-physical debugging, with dynamic bottleneck diagnosis algorithms enabling resource reconfiguration. Experimental results demonstrate that the system deployment cost exhibits significant reduction compared to traditional solutions, with robot motion path length optimized by 24.3%, single-cycle time shortened by 24.6%, and energy consumption reduced by 16.7%. Through the implementation of a Model Predictive Control (MPC) strategy, the joint maximum torque is constrained below 80% of rated values, and emergency stop torque reduction reaches 11.8%, significantly enhancing system safety. This breakthrough addresses digital twin technology’s reliance on high-precision hardware, providing a scalable solution for high-mix low-volume production modes, and demonstrates substantial potential for large-scale applications in 3C electronics, precision machining, and related fields.