Macro Process Driven CAD/CAM Model Associated Retrieval,Reuse And Optimization

With a vast number of machining process cases accumulating and enriching in the enterprise database,process data-driven process planning can effectively improve the intelligent level of NC process decision-making system and shorten the product development cycle.As one of the key technologies of data-driven process planning,3D model retrieval technology provides an effective means for discovery and reuse of similar 3D geometry of parts and their associated NC processes.However,the existing methods follow the principle that if 3D geometry is similar then the process is similar,which cannot ensure the reusability of the similar processes.CAD/CAM model associated retrieval method is to support the search of similar cases through construting the relationship between 3D geometry and NC process,which can ensure the reusability of the associated process.Therefore,how to use the associated retrieval method to conduct multi-dimensional association analysis of NC process cases and integrate NC process into similarity evaluation is an urgent problem.On the other hand,at present,NC process reuse mainly focuses on the reuse of micro process information such as machining parameters,machining strategies,etc.,while macro process information such as working step,machining sequence contains rich high-level process design intent and plays a guiding role in the whole machining process of parts,which also has important reuse value.While the current process planning methods generally assumes that micro process is compatible with macro process,while the reusable process from the subparts of multiple parts is usually difficult to be compatible under the manufacturing requirements of parts to be manufactured,which makes many manual modifications.To solve these problems,the macro process driven CAD/CAM model associated retrieval is studied in this dissertation to further enrich and improve the NC process plannning method based on process reuse,so as to promote the application of data-driven mode in the field of NC process planning.The main contents of the dissertation are presented as follows:(1)A framework for CAD/CAM model associated retrieval,reuse and optimization is constructed.The framework combines process skeleton extraction,3D CAD model retrieval,merging and optimization for multi-source similar subparts,and thus it can support the NC process planning for complex parts more efficiently and optimally.(2)A complex network based NC process skeleton extraction approach is presented.The process skeleton is the key working step sequence reflecting the macro process constraints in the NC process plan.It is the core macro process shared by similar part family instances.The automatic extraction of process skeleton is the basis of macro process reuse.First,the characteristics for the process skeleton are analyzed by reusability,correlation,critical and rationality.The machining process data instances are then transformed into process element attribute adjacency graph.Finally,according to the complex network theory,the process data network is constructed,and the key nodes of process elements are determined to support the automatic discovery of process skeleton.(3)A process skeleton-guided CAD/CAM model associated retrieval approach is proposed.To find the reusable macro process in NC machining process,the CAD/CAM model associated retrieval guided by process skeleton is studied.First,a process skeleton model is introduced to guide the structuralization of process data based on the macro process of existing parts.Then,a probability statistics approach is presented to map machining features of query part onto the macro process of existing part.Finally,process design intent-driven accessible machining region extraction is proposed,and then the part similarity assessment model based on the machining region is established to calculate the macro process similarity between query part and existing part.(4)A macro process-drived merging approach for similar NC process of multi-source subparts is presented.Based on the found reusable macro process and the existing similar NC process of multi-source subparts,in order to generate the NC process scheme quickly and reasonably,the merging for similar NC process of multi-source subparts guided by macro process is studied.First,according to the calculation of semantic distance of process design intent,the micro processes are mapped to the macro process to realize the merging of macro process and micro process.Then,a locally inscribed circle moving frame is established to guide the calculation of machining region and undercut region for complex pocket,and the URs are categorized by the topological structure of its medial axis.Finally,based on the dynamic evolution of the machining regions and the residual regions of the preliminary process scheme,the compatibility evaluation model is established to evaluate the compatibility of the merging results,so as to support the adaptive adjustment of the NC process scheme.(5)A NC process optimization reuse approach is proposed.Aiming at the NC process scheme generated by similar NC process merging of multi-source subparts,the optimization and adjustment of the scheme is studied from the perspective of parts as a whole.First,the optimization strategy of the main parameters of the machining region such as the cutting tool and the cutting depth is designed to generate optimized machining regions by making full use of the tool machining capacity and avoid the air-cutting.Then,the sequence of working steps is optimized by taking advantage of the ant colony optimization algorithm in a global search.Finally,taking the result of working step optimization as the initial solution,the tool path is optimized by taking the advantage of the tabu search algorithm in a local search to obtain the optimization process shceme of the comprehensive considerations of the cutting tool,the machining region,and the tool path.On the basis of the above research,a prototype system for macro process-driven CAD/CAM model retrieval,reuse and optimization was developed.At the same time,some experiments were carried out to verify the feasibility and effectiveness of the proposed method.