Application Research on Process Model Generation Method based on Feature Association and Intelligent Reasoning

In traditional 3D process design, the construction of process models relies heavily on manual modeling, which brings about problems such as low efficiency and poor model consistency and restricts the overall quality and efficiency of process design. To solve this problem, this paper proposes an automatic generation method of process models based on feature association and intelligent reasoning. This method establishes a complete process knowledge chain through feature recognition, machining reasoning and intelligent process sequence planning, and realizes one-click generation and update of process models. The system supports automatic PMI annotation, intelligent association of process resources and parameters, as well as structured input of process descriptions, which effectively reduces manual errors. This paper elaborates the business logic, technical framework, core algorithms and implementation procedures of the proposed method. Engineering examples verify that this method can effectively improve design efficiency and guarantee model consistency. It provides a feasible technical route for the intelligent upgrading of 3D structured process design and offers valuable references for the digital transformation of process design.