云设计环境下任务域与能力域的匹配机制研究
发布时间：2018-07-16 12:20
【摘要】：随着信息技术的不断发展,云制造、物联网等技术理论为如何实现设计制造资源的快速聚集和有效应用提供了新的解决思路。云制造借鉴了云计算的思想,旨在实现制造资源的虚拟化与制造能力的服务化。作为云制造技术重要分支的云设计理论,由于其可以动态的聚集企业外部设计资源、快速提高企业设计能力的特点,得到了越来越多的关注。云设计服务平台依托于互联网技术将企业内部复杂产品设计任务与企业外部设计资源有效地连接在一起,通过动态的资源组织向用户提供技术服务。在云设计服务平台的开发过程中,由于设计任务的多样性、能力资源的动态性以及任务分配过程的复杂性,造成了该模式运行效率较低,适用产品范围较小。为此,本文深入研究了基于信息熵测度理论的任务建模方法和云设计环境下设计资源聚集方法,并且将任务相似度与任务复杂度相结合,作为匹配优化目标,实现基于多分辨率聚类算法的任务-能力匹配过程,从而大幅提高云设计过程的效率,缩短了产品设计周期。(1)根据信息熵理论,重新定义了产品设计任务复杂度的概念,把任务设计操作复杂度、操作逻辑复杂度和信息复杂度合理地融合在了一起,并且结合分解树模型和有向图理论分别提出了产品设计任务分解模型和时序模型。基于汽车模具产品的实例对计算方法和任务建模过程给出了进一步说明。(2)通过对设计资源的深入分析,提出了云设计环境下的设计能力单元模型,将设计能力单元的属性分为基本能力属性、技术能力属性和动态能力属性。根据设计能力单元已完成任务与待分配任务之间的相似度,计算得出设计能力单元与待分配任务之间的匹配度,并基于模糊集理论提出设计任务完成周期预估方法。(3)提出了基于任务相似度的设计任务域与设计能力域的匹配流程以及基于多分辨率聚类算法的任务-能力匹配算法,确保了设计任务匹配过程的准确性。并且基于实例验证了本文所提出的分配算法的有效性。(4)基于本文的研究基础,开发了基于云设计理论的汽车及模具产业链服务平台,实现了汽车模具云设计模式。
[Abstract]:With the continuous development of information technology, cloud manufacturing, Internet of things and other technical theories provide a new solution for how to realize the rapid aggregation and effective application of design and manufacturing resources. Cloud manufacturing draws lessons from cloud computing and aims to realize virtualization of manufacturing resources and service of manufacturing capabilities. As an important branch of cloud manufacturing technology cloud design theory has been paid more and more attention because it can dynamically aggregate external design resources and improve the design ability of enterprises. Cloud design service platform relies on Internet technology to effectively connect complex product design tasks and external design resources, and provide technical services to users through dynamic resource organization. In the development process of cloud design service platform, due to the diversity of design tasks, the dynamic nature of capability resources and the complexity of task allocation process, the operation efficiency of the model is low and the product scope is small. Therefore, the task modeling method based on the information entropy measure theory and the design resource aggregation method in the cloud design environment are studied in this paper, and the task similarity is combined with the task complexity as the target of matching optimization. The task-capability matching process based on multi-resolution clustering algorithm is implemented, which greatly improves the efficiency of the cloud design process and shortens the product design cycle. (1) according to the information entropy theory, the concept of task complexity in product design is redefined. The task design operation complexity, the operation logic complexity and the information complexity are reasonably combined together, and the product design task decomposition model and the time series model are put forward based on the decomposition tree model and the directed graph theory, respectively. Based on the examples of automobile mould products, the calculation method and task modeling process are further explained. (2) through the in-depth analysis of design resources, the design capability unit model under cloud design environment is proposed. The attributes of design capability unit are divided into basic capability attribute, technical capability attribute and dynamic capability attribute. According to the similarity between the completed task and the task to be assigned, the matching degree between the design capability unit and the task to be assigned is calculated. Based on fuzzy set theory, a design task completion cycle prediction method is proposed. (3) the matching process between design task domain and design capability domain based on task similarity and the task-ability matching algorithm based on multi-resolution clustering algorithm are proposed. Ensure the accuracy of the design task matching process. And the effectiveness of the proposed allocation algorithm is verified based on an example. (4) based on the research foundation of this paper, the service platform of automobile and die industry chain based on cloud design theory is developed, and the cloud design pattern of automobile mold is realized.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP311.52;TB472
[Abstract]:With the continuous development of information technology, cloud manufacturing, Internet of things and other technical theories provide a new solution for how to realize the rapid aggregation and effective application of design and manufacturing resources. Cloud manufacturing draws lessons from cloud computing and aims to realize virtualization of manufacturing resources and service of manufacturing capabilities. As an important branch of cloud manufacturing technology cloud design theory has been paid more and more attention because it can dynamically aggregate external design resources and improve the design ability of enterprises. Cloud design service platform relies on Internet technology to effectively connect complex product design tasks and external design resources, and provide technical services to users through dynamic resource organization. In the development process of cloud design service platform, due to the diversity of design tasks, the dynamic nature of capability resources and the complexity of task allocation process, the operation efficiency of the model is low and the product scope is small. Therefore, the task modeling method based on the information entropy measure theory and the design resource aggregation method in the cloud design environment are studied in this paper, and the task similarity is combined with the task complexity as the target of matching optimization. The task-capability matching process based on multi-resolution clustering algorithm is implemented, which greatly improves the efficiency of the cloud design process and shortens the product design cycle. (1) according to the information entropy theory, the concept of task complexity in product design is redefined. The task design operation complexity, the operation logic complexity and the information complexity are reasonably combined together, and the product design task decomposition model and the time series model are put forward based on the decomposition tree model and the directed graph theory, respectively. Based on the examples of automobile mould products, the calculation method and task modeling process are further explained. (2) through the in-depth analysis of design resources, the design capability unit model under cloud design environment is proposed. The attributes of design capability unit are divided into basic capability attribute, technical capability attribute and dynamic capability attribute. According to the similarity between the completed task and the task to be assigned, the matching degree between the design capability unit and the task to be assigned is calculated. Based on fuzzy set theory, a design task completion cycle prediction method is proposed. (3) the matching process between design task domain and design capability domain based on task similarity and the task-ability matching algorithm based on multi-resolution clustering algorithm are proposed. Ensure the accuracy of the design task matching process. And the effectiveness of the proposed allocation algorithm is verified based on an example. (4) based on the research foundation of this paper, the service platform of automobile and die industry chain based on cloud design theory is developed, and the cloud design pattern of automobile mold is realized.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP311.52;TB472
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