Research On Module Division And Model Planning Of Complex Product

As a typical representative of national high-end equipment,the complex products are playing an essential role in the field of constructing powerful manufacturing country,improving innovation ability et al.,and yet the R&D and manufacturing of complex products is always a huge difficult problem in engineering.However,the modular design is an effective measure for solving this difficult problem.As the key technology of modular design,module division and modular spectrum planning have some shortcomings.Among them,the research focuses more on the division of modules,but most of the existing modular methods focus on the function,structure,and product life cycle factors of the same period,and lack of consideration of product evolution performance,that is,the risk of change,the modular system structure cannot effectively support its Evolutionary process control.The research on modular spectrum planning is less,and the treatment of customer needs has not been fully considered.Therefore,this paper proposes a complex product module division method that considers the risk of component changes and a customer demand-driven complex product module spectrum planning method for the problem of module division and modular spectrum planning in complex products.The specific research content is as follows:(1)The division of complex product modules considering the risk of component changes.Continuous evolution is an inevitable trend of complex products.In order to reduce the impact of evolution,when dividing complex products into modules,three factors,including function,structure,and risk of change,are considered at the same time.The complex network theory is applied to the modeling of complex product structures,with components as nodes and the relationship between components as edges to establish a complex product component network model.The product is divided into two modules by a two-stage module division method.First,the initial division scheme of the product module is solved based on LinkRank’s community discovery algorithm,and then the community division algorithm based on network similarity optimization is used to obtain the final division scheme.Finally,the feasibility and effectiveness of the proposed method are verified by using a certain type of motorcycle engine as an example.(2)Complex product modular spectrum planning driven by customer demand.After obtaining the modular structure of a complex product,a module is constructed based on customer needs to respond to customer demand network models and identify module types.According to the flexible modules,the value of the module parameters is planned according to the relevant customer needs.First,use the quality function to expand customer demand analysis to obtain the range of module parameter values.Based on this,an improved hybrid data clustering algorithm is used to cluster customer needs to obtain the number of module parameter values.Finally,it is determined based on the customer demand distribution characteristics.The specific values of the module parameters are used to complete the modular spectrum planning.In addition,taking a drop-off mechanism of a large-tonnage crane as an example,the module spectrum planning is performed on it,and the results show that the obtained planning scheme is in line with the actual engineering.The method proposed in the paper has certain theoretical and practical significance in the design stage of complex products.It has established a comprehensive method system for achieving the modular design of complex products,and provides technology for promoting the evolution of complex product structures from integrated structures to modular structures.To ensure the rapid development of complex product variants.In the end,it can help companies improve the rate of knowledge reuse,shorten the development cycle of variant products,and then improve their competitiveness.The thesis includes 25 figures,17 tables and 122 references.