| With the developing digitalization and intellectualization in the manufacturing industry,the intelligent planning of assembly sequence has become a crucial link to improve production efficiency throughout the life cycle.It is an important technology to reduce production cost and enhance the competitiveness of enterprises.The development of assembly sequence intelligent planning needs to face assembly information extraction,assembly information expression and assembly knowledge application.This thesis studies the intelligent assembly sequence planning method based on CAD model information and assembly knowledge,explore the information extraction,ontology modelling,assembly sequence planning,assembly simulation,assembly sequence evaluation and other links based on CAD model,and improves the automation and intelligent level of assembly sequence planning.The main research contents are as follows:(1)CATIA is developed based on VB6.0,and its related interfaces are called to realize the automatic extraction of product assembly information,and the extracted data is saved in the data file.Based on the Eclipse development platform,run a Java program to read the stored information and call the Jena package to model the assembly ontology.Automatic extraction of assembly CAD model information and automated construction of ontology model is realized.(2)Based on the ontology knowledge model,the typical structure is extracted by assembly knowledge,and its similar parts are matched and reasoned.The non-typical structure and its similar structure are reasoned by assembly knowledge based on the fuzzy set to realize the assembly sequence planning and infer the primary assembly sequence.The basic assembly sequence is optimized based on the connection relationship,and the complete assembly sequence is output.The intelligent assembly sequence planning method based on assembly knowledge is realized.(3)Based on the established ontology knowledge model and the extracted assembly information,the data needed for BP neural network reasoning is generated.The BP neural network model is established and trained to realize the assembly sequence planning based on BP neural network and infer the primary assembly sequence.For the basic assembly sequence,the assembly sequence optimization method based on sub-assembly recognition is used to output the final assembly sequence.The intelligent assembly sequence planning method based on BP neural network is realized.(4)Assembly sequence simulation method and assembly sequence evaluation method based on CATIA improve the whole process of the assembly sequence.An intelligent assembly sequence planning system is established by integrating the programs and software used in information extraction,ontology modelling,assembly sequence planning,assembly sequence simulation and assembly sequence evaluation.The intelligent assembly sequence planning system based on CAD model information and assembly knowledge is realized.The feasibility and effect of the system are verified by taking worm reducer as an example.To sum up,aiming at the technical problems existing in the assembly sequence planning,this study works on the solution of the critical technology of assembly sequence planning based on the information of CAD model,combined with ontology knowledge,assembly knowledge and BP neural network.It verifies the feasibility of the solution,which provides a new idea and method for the assembly sequence planning method. |
