| Assembly is an important part of product production and processing,and assembly sequence planning is the study of assembly sequencing of various components of a product under corresponding constraints.Reasonable assembly sequences can reduce the average time of product assembly,save labor and material costs,and improve the final quality of the product.With the continuous development of the manufacturing industry,many mechanical and electrical products that need to be assembled will have some components that are flexible components,which have physical properties differences from general rigid components.These differences,such as the characteristics of flexible components that can deform themselves under the action of force to avoid interference,have led to differences in the assembly process and assembly requirements of flexible components and rigid components.In the current research on assembly sequence planning,there are few relevant documents that consider the characteristics of flexible components.Enterprises still rely more on existing experience when assembling flexible products,without scientific and standardized specific operating standards.Aiming at the unique impact of flexible components on the assembly process,thesis constructs a mathematical model for assembly sequence planning that considers the characteristics of flexible components.At the same time,the flower pollination algorithm is discretized and improved to search and solve the assembly sequence planning model,and finally,a product assembly sequence optimization scheme that considers the characteristics of flexible components is obtained.The main work of thesis is as follows:(1)According to the difference between flexible components and rigid components in the judgment criteria for interference and collision during assembly,a unique assembly stress matrix for flexible components is defined.The numerical information recorded in the matrix can be used to determine the feasible assembly direction of flexible components and the maximum stress borne by components during assembly along each feasible assembly direction.Further,BP neural network is applied to establish a machine learning model to predict and judge the matrix elements of the assembly stress matrix through the model,and the extraction speed of the assembly stress matrix is accelerated.(2)Considering the impact of flexible components on product assembly,a mathematical model for assembly sequence planning considering the characteristics of flexible components is constructed.The model adjusts constraints and evaluation indicators based on flexible components,including assembly stress constraints for flexible components,stress values during assembly of flexible components,and assembly switching times for flexible and rigid components.After each indicator is determined,the weight value of each indicator is scientifically quantified through fuzzy analytic hierarchy process.(3)Based on the mathematical model of assembly sequence planning considering the characteristics of flexible components,an improved flower pollination algorithm(FPA)is proposed to solve the optimal feasible assembly sequence.In the specific solution process of the algorithm,the algorithm process is discretized according to the characteristics of the assembly sequence planning problem,and the algorithm process is optimized combining with the improvement strategy of genetic algorithm.Finally,through a case study,the reasonable interval of each parameter of the algorithm was determined based on different tests.On this basis,the feasibility and effectiveness of the improved algorithm was further partially verified. |
PDF Full Text Request