个性化定制产品智能设计模型研究及在真空玻璃中的应用
发布时间：2018-08-11 09:38
【摘要】：随着“中国制造2025”和“互联网+”的提出,传统制造模式开始向个性化定制的新型制造模式升级转变,基于消费需求动态感知的产品设计和研发受到了越来越多的重视。因此迫切需要邀请客户参与到产品设计环节,并将客户个性化的需求提炼转换为产品设计领域的术语,为定制产品设计提供决策支持。在此研究背景下,对个性化定制产品智能设计模型进行研究。本文首先建立客户个性化需求到工程特性映射模型,利用质量功能配置将客户个性化需求映射为产品设计的工程特性,并基于最大离差语言多属性群决策理论,计算工程特性与客户个性化需求的关联度(即重要度),掌握客户最关心的定制产品的功能,为定制产品设计提供决策支持;借鉴人工免疫系统自学习、自组织、自适应、记忆等优点进行个性化定制产品智能设计,将提取的工程特性及其重要度作为抗原,输入基于人工免疫系统个性化定制产品智能设计模型,模拟抗体产生,亲和度计算等,匹配与客户个性化需求程度最高的产品方案。在智能设计模型中分为两步,第一步利用基于人工免疫系统个性化定制产品知识检索系统,确定个性化定制产品初始设计方案,第二步以“减少温室气体排放、安全可靠、节能环保”的理念进行定制产品的选材和结构优化设计,在产品设计之初就考虑资源浪费和环境污染等问题。最后利用数值模拟的方法对设计产品的功能进行验证,保证个性化定制产品的品质和可靠性。以个性化定制真空玻璃设计为例,利用客户个性化需求到工程特性映射模型提取与客户个性化需求相关的工程特性及其重要度,并将这些工程特性及其重要度作为抗原输入基于人工免疫系统个性化定制产品知识检索系统,确定满足客户个性化需求的定制产品初始设计方案,之后从节约资源和保护环境的角度进行产品选材,并利用基于人工免疫系统的智能算法对真空玻璃的支撑物直径和间距进行优化设计,保证个性化定制真空玻璃良好的保温性能;最终利用耦合热传导-辐射模型对定制真空玻璃的保温性能进行验证,仿真结果显示个性化定制真空玻璃的传热系数K为0.84Wm-2K-1,表明其保温性能达到了客户个性化的需求,同时也证明基于人工免疫系统个性化定制产品智能设计模型的正确性,可为面向个性化定制的新型制造模式下的产品设计提供参考。本文提出的个性化定制产品智能设计模型为面向个性化定制的新型制造模式提供了新思路,在产品设计阶段兼顾客户个性化需求的同时,将节约资源、环保等理念融入到个性化定制产品的设计中,有助于实现可持续发展,并引入数值模拟的方法对定制产品的功能进行验证,保证个性化定制产品的品质。
[Abstract]:With the development of "made in China 2025" and "Internet", the traditional manufacturing model has been transformed into a new type of customized manufacturing model. More and more attention has been paid to product design and research based on dynamic perception of consumer demand. Therefore, it is urgent to invite customers to participate in the process of product design, and to transform the personalized requirements of customers into terms in the field of product design, so as to provide decision support for customized product design. Under this background, the intelligent design model of customized product is studied. In this paper, the mapping model of customer personalized requirement to engineering characteristic is established, and the customer personalized requirement is mapped to the engineering characteristic of product design by using quality function configuration, and based on the theory of maximum deviation language multi-attribute group decision. To calculate the correlation degree between engineering characteristics and customer's individualized demand (i.e. importance degree), to grasp the function of custom-made product that the customer cares most, to provide decision support for custom-made product design, to learn from artificial immune system self-learning, self-organizing, self-adaptive, Memory and other advantages of personalized customized product intelligent design, the extracted engineering characteristics and their importance as antigen, input based on artificial immune system personalized customized product intelligent design model, simulation antibody production, affinity calculation, etc. Match the product program with the highest degree of customer personalization requirements. The intelligent design model is divided into two steps: the first step is to use the personalized customized product knowledge retrieval system based on the artificial immune system to determine the initial design scheme of the personalized customized product, and the second step is to "reduce greenhouse gas emissions, and be safe and reliable." The idea of energy saving and environmental protection is to select materials and optimize the structure of customized products. The waste of resources and environmental pollution are considered at the beginning of product design. Finally, the function of the designed product is verified by numerical simulation to ensure the quality and reliability of the customized product. Taking the design of customized vacuum glass as an example, using the mapping model of customer's individuation requirement to engineering characteristic, the engineering characteristic and its importance related to customer's individuation requirement are extracted. These engineering characteristics and their importance are used as antigens to input the customized product knowledge retrieval system based on artificial immune system to determine the initial design scheme of customized products to meet the customer's personalized needs. Then the material selection is carried out from the point of view of saving resources and protecting the environment, and the diameter and spacing of the support of vacuum glass are optimized by using the intelligent algorithm based on artificial immune system. Finally, the coupling heat conduction radiation model is used to verify the thermal insulation performance of customized vacuum glass. The simulation results show that the heat transfer coefficient K of the customized vacuum glass is 0.84Wm-2K-1, which indicates that the heat preservation performance meets the customer's individuation requirement, and it also proves the correctness of the intelligent design model of personalized customized product based on artificial immune system. It can provide reference for the product design under the new manufacturing mode of individualized customization. The intelligent design model of personalized customization product proposed in this paper provides a new way of thinking for a new type of manufacturing model oriented to personalized customization. In the stage of product design, it will take account of the individual needs of customers and save resources at the same time. The concept of environmental protection is integrated into the design of customized products, which is helpful to realize sustainable development, and the function of customized products is verified by numerical simulation to ensure the quality of customized products.
【学位授予单位】：河南科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TQ171.7
[Abstract]:With the development of "made in China 2025" and "Internet", the traditional manufacturing model has been transformed into a new type of customized manufacturing model. More and more attention has been paid to product design and research based on dynamic perception of consumer demand. Therefore, it is urgent to invite customers to participate in the process of product design, and to transform the personalized requirements of customers into terms in the field of product design, so as to provide decision support for customized product design. Under this background, the intelligent design model of customized product is studied. In this paper, the mapping model of customer personalized requirement to engineering characteristic is established, and the customer personalized requirement is mapped to the engineering characteristic of product design by using quality function configuration, and based on the theory of maximum deviation language multi-attribute group decision. To calculate the correlation degree between engineering characteristics and customer's individualized demand (i.e. importance degree), to grasp the function of custom-made product that the customer cares most, to provide decision support for custom-made product design, to learn from artificial immune system self-learning, self-organizing, self-adaptive, Memory and other advantages of personalized customized product intelligent design, the extracted engineering characteristics and their importance as antigen, input based on artificial immune system personalized customized product intelligent design model, simulation antibody production, affinity calculation, etc. Match the product program with the highest degree of customer personalization requirements. The intelligent design model is divided into two steps: the first step is to use the personalized customized product knowledge retrieval system based on the artificial immune system to determine the initial design scheme of the personalized customized product, and the second step is to "reduce greenhouse gas emissions, and be safe and reliable." The idea of energy saving and environmental protection is to select materials and optimize the structure of customized products. The waste of resources and environmental pollution are considered at the beginning of product design. Finally, the function of the designed product is verified by numerical simulation to ensure the quality and reliability of the customized product. Taking the design of customized vacuum glass as an example, using the mapping model of customer's individuation requirement to engineering characteristic, the engineering characteristic and its importance related to customer's individuation requirement are extracted. These engineering characteristics and their importance are used as antigens to input the customized product knowledge retrieval system based on artificial immune system to determine the initial design scheme of customized products to meet the customer's personalized needs. Then the material selection is carried out from the point of view of saving resources and protecting the environment, and the diameter and spacing of the support of vacuum glass are optimized by using the intelligent algorithm based on artificial immune system. Finally, the coupling heat conduction radiation model is used to verify the thermal insulation performance of customized vacuum glass. The simulation results show that the heat transfer coefficient K of the customized vacuum glass is 0.84Wm-2K-1, which indicates that the heat preservation performance meets the customer's individuation requirement, and it also proves the correctness of the intelligent design model of personalized customized product based on artificial immune system. It can provide reference for the product design under the new manufacturing mode of individualized customization. The intelligent design model of personalized customization product proposed in this paper provides a new way of thinking for a new type of manufacturing model oriented to personalized customization. In the stage of product design, it will take account of the individual needs of customers and save resources at the same time. The concept of environmental protection is integrated into the design of customized products, which is helpful to realize sustainable development, and the function of customized products is verified by numerical simulation to ensure the quality of customized products.
【学位授予单位】：河南科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TQ171.7
【参考文献】
相关期刊论文 前10条
1 Farshid Abbasi;Alireza Mojtahedi;Mir Mohammad Ettefagh;;Fault diagnosis using noise modeling and a new artificial immune system based algorithm[J];Earthquake Engineering and Engineering Vibration;2015年04期
2 杨涛;杨育;薛承梦;张雪峰;焦W，
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