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Research On The Scale-based Product Family Design Technique And Application In The Turbo Expander

Posted on:2009-12-20Degree:MasterType:Thesis
Country:ChinaCandidate:R TianFull Text:PDF
GTID:2132360272466475Subject:Mechanical design and theory
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Mass customization has been used more and more widely in the manufacturing enterprises, the key technique of which is product family design based on the common product platform. Combining the 863 program with the enterprise's specific needs, author exceeded the customer-driven scale-based product family design technique. This paper researched more weightily in the customer requirement modeling and mapping technique for product families planning, construction technique for scale-based product family based on improved NSGA-Ⅱand the evaluation technique for scale-based product family based on similarity, which were successfully used in the design and development for turbo expander serial products in HANGYANG air separation equipments.In the first chapter, the paper introduced existing modeling methods for customer requirement and expounded the technique——Quality Function Development which is used to map the customer requirements into technical requirements; Respectively expounded the technique for modular and scale-based product family design and their key technique were analyzed. Finally, the author pointed out the paper's research background, content and structure.In the second chapter, after analyzing the existing methods to acquire customer requirements, the formal description and decomposition method based on knowledge system modeling were proposed, so the customer requirement modeling based on demand topology structure was realized; Quality Function Development method was introduced and its core component——product planning matrix was used to map the customer requirements into technical requirements. Finally, an example of the turbo expander was provided to realize the customer requirement modeling and mapping for product family planning.In the third chapter, the NSGA-Ⅱbased on hybrid chromosome representation scheme was proposed to optimize the product performances in order to get several optimal design solutions of products in the family. Above that, the improved NSGA-Ⅱwas introduced to acquire optimal combinations of design solutions among different products in the product family, so the product platform parameter planning could be realized. Dual fitness functions were set to the NSGA-Ⅱto control the similarity of design parameters and odds of product performances in the evolution, so product family design solutions with superior comprehensive performances were obtained finally and the scale-based product family for turbo expander was constructed.In the fourth chapter, aiming to the two tradeoff indices for product family evaluation——commonality of the product platform and the individual product performances, their specific implementations in modular and scale-based product family evaluation were analyzed, then commonality indices(SCI) and performance indices(SPI) based on similarity for product family evaluation were proposed. After giving the specific computing method of SCI and SPI, the evaluation flow and model of scale-based product family based on similarity were expanded. Finally, using the turbo expander as example, we demonstrated the feasibility and validity of the method mentioned above.The system HY-PDM was developed to realize the scale-based product family design for the turbo expander. Realizing the customer requirement information processing, the product technical property customization and serial products parameter configuration for the turbo expander through the system, the customer-driven scale-based product family design flow for the turbo expander was shown.In the last chapter, summarized the contents and the achievements of this paper, then pointed out the further research direction.
Keywords/Search Tags:Turbo Expander, Customer Requirement Modeling, Demand Topology Structure, Product Planning Matrix, NSGA-Ⅱ, Hybrid Chromosome Representation Scheme, Multi-objective Optimization, Scale-Based Product Family, Platform Parameter Planning
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