Virtual Simulation Debugging and Optimization of Automotive Connecting Rod Production Line Based on Digital Twin

In the context of intelligent transformation of the automotive industry, higher requirements have been placed on the debugging efficiency and quality control of production lines. Traditional automotive connecting rod production relies on physical prototype testing and manual experience adjustment, which has bottlenecks such as long cycle time, high cost and lack of flexibility. Aiming at the industry pain points of long debugging cycle and lack of flexibility in automotive connecting rod production line, this study proposes a virtual-real collaborative debugging optimization method based on digital twin. By constructing a multi-dimensional digital mirror system that integrates equipment mechanism and process parameters, a simulation debugging framework is established that contains core technologies such as dynamic interactive verification of process parameters and virtual debugging error compensation. The research breaks through the traditional physical prototype debugging paradigm and develops a virtual iterative optimization algorithm for process parameters, which realizes the improvement of process planning efficiency and the shortening of equipment debugging cycle in connecting rod production line. Practice shows that the digital twin system can effectively support parameter optimization and line restructuring for precision parts machining, and provide migratory debugging optimization solutions for intelligent manufacturing systems.