Research on “Intelligence + Digitalization” of Transformer Yoke Insulation Production Unit

Aiming at the three major pain points of low production efficiency, poor positioning accuracy, and insufficient quality inspection reliability in manual operations of transformer yoke insulation production units, this paper conducts research on intelligent and digital transformation. By building a manufacturing platform integrating industrial robots, PLC control, artificial intelligence vision systems, MES, and digital twin technology, a full-process technical closed-loop is realized: industrial robots collaborate with PLC modular programs to complete automated assembly; the vision system achieves millimeter-level positioning guidance and defect detection; the digital twin system based on PQ Factory supports virtual-real synchronous debugging and optimization; the Internet of Things and MES dashboards realize visual management and control of all production elements. The application shows that this scheme significantly improves assembly efficiency, positioning accuracy, and product qualification rate, providing a reusable intelligent transformation path for the manufacturing of core components in rail transit.