Research On Key Technologies In Modular Configuration Design Of Mechanical Products Based On Product Family

Mass customization, being committed to provide various and individual productsto the market with high efficiency and low cost of mass production, has already been themain trend of modern manufacturing. As one of the key enabling technologies of masscustomization achievement, product configuration design contributes to improve theorder acquisition ratio, shorten the product design cycle, save the cost, and increaseresponse ability and competition ability of firms. Module-based configuration design,regarded as a primary configuration technique, is the core and key of realizing rapidproduct customization. Several academic and technological problems weresystematically and deeply studied in this thesis. The overall scheme of modularconfiguration design was proposed, and some critical technologies such as moduleidentification and optimization, product platform development, multi-objectiveconfiguration optimization, configuration performance prediction, configurationfunction solving, and configuration system development were derived, which form atechnological architecture that could cover the whole configuration design process. Themain achievements are described as follows:(1) A new method for module identifying and optimizing based on unevengranularity was put forward. The parts of a product were fuzzily clustered usingrelativity analysis so as to set up a hierarchical structure. All the universes of thegranular layers in the hierarchical structure were gathered and the uneven granularitybased module clustering scheme was formally presented. Four quantified indices wereproposed to set up four optimization objective functions. Use nondominated sortinggenetic algorithm II to solve the problem in order to obtain the Pareto optimal set. Thisapproach makes module identification more flexible, enlarges the solution space ofmodule clustering, and administers to reach the global optimum solution. Moreover, theproposed method can satisfy diverse and dynamic requirements of customers andcompanies to different objectives, which helps to enhance the adaptability of moduleschemes to customers’ requirements and enterprise emphasis.(2) A bottom-up method for module-based product platforming through mapping,clustering and matching analysis was presented. The framework consisted of three steps:mapping parameters from existing product families to functional modules, clustering themodules within existing module families based on their parameters so as to generatemodule clusters, and selecting the satisfactory module clusters based on commonality,and matching the parameters of the module clusters to the functional modules in orderto capture platform elements. This method ensures the effectiveness of design resourcereusing, and is helpful to obtain a balance between the universal requirements orientedto mass production and individual requirements oriented to personalized customization. The approach could enable the developed product platform be representative andfeasible.(3) A new multi-objective optimization approach to configuration design with theconsideration of several types of uncertain information was brought forward. Theuncertain configuration information was uniformly described with interval numbers. Amulti-objective optimization model was generated by integrating three mathematicalmodels such as the performance, cost and term. The non-dominated sorting geneticalgorithm II was used to solve the model and a Pareto optimal set of productconfiguration schemes was obtained. This method can effectively deal with the problemof configuration optimization under uncertain information, which remedies the defectsof specific configuration and fuzzy configuration. Therefore, the scope of theconfiguration optimization approach could be further extended.(4) A novel prediction approach based on the integration of grey relational analysisand support vector machine through discovering the knowledge from the historicalconfiguration information was proposed. Product performance prediction at the end ofthe configuration process can estimate the performance parameter values through thesoft computing method instead of practical test experiments, which is propitious toreduce the cost, shorten the development cycle, decrease the complexity of predictionmodel and reduce the prediction error. This methodology, ensuring the performanceprediction executed in a short period of time with a high degree of precision, even underthe small sample conditions, leads to a new technique for predicting configurationperformance.(5) An approach to function solving and modeling oriented to configuration designwas raised. Considering rational design domains including function, working principle,behaviour and structure, a hierarchical functional solving model with hybrid mappingswas established, which could be used to address the problem during the post processingstage of configuration design. The model can effectively combine the creative thinkingof designers with the power of reasoning computing of computers, and administers tothe implementation of inheritance and innovation. The application of this functionalsolving model to configuration design could ensure the validity and feasibility of designresults and the maximization of the customers’ satisfaction.(6) A prototype of computer-aided modular configuration design software wasdeveloped and implemented to verify the above theories and technologies. Theprototype was built based on the general CAD platform and consisted of the functionssuch as configuration data management, configuration model establishment,configuration model management and configuration model solving. The preliminaryapplication was carried out to demonstrate the proposed methods. This prototype,covering the whole process of product configuration design, enables to realizesynchronous visualization and complete control of the configuration process, improve the efficiency and success rate of configuration design, and it shows a broad marketableprospect.