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基于AHP与CBR技术的注射模智能报价方法研究
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摘要
随着现代工业快速发展和产品更新换代周期急剧缩短,模具的需求量日益增长。这在给模具制造企业带来了巨大机遇的同时,也带来了更为激烈残酷的市场竞争。努力赢得订单是现今模具制造企业生存和发展的基础,因此,面对客户的询价,如何对模具产品进行准确、快速地报价是每个模具制造企业面临的重大课题。本文就此展开了研究,在参考大量文献的基础上,创造性地提出了分组报价的思路和报价软件个性化定制的思想,结合层次分析法(AHP)与CBR技术,并融合CAD参数自动提取技术,建立了计算机辅助智能报价模型,开发了一个注射模计算机辅助智能报价的原型系统。以下是本文各章内容的概述:
     第一章探讨了对模具产品进行准确、快速地报价的重大意义,着重回顾了国内外模具报价方法以及计算机辅助模具报价系统的研究现状,并提出了本文的研究对象和研究内容。
     第二章详细介绍了AHP与CBR的一些基本原理、发展概况和关键实现技术,尤其是对AHP层次结构模型的构建、CBR实现技术中事例的表示与存储,检索和修改以及事例库的维护作了详细的论述。
     第三章抽取了一系列对注射模价格产生重要影响的问题特征,连同模具价格构成注射模价格事例的表示模型。研究了DXF文件信息的自动提取技术。选用了改进的Kolodner距离作为注射模价格事例相似度的度量公式。根据问题特征取值类型的不同,定义了数值型问题特征的相似度函数和字符型问题特征的相似度表,针对采用CBR技术问题特征权重不易确定的问题,利用层次分析法对各问题特征权重进行了专门的研究,使得权重赋值具有系统性和自动化功能,另外给出了注射模价格事例库两个维护原则。
     第四章介绍了智能报价模型的报价流程,详细讨论了报价模型中的四个主要模块:软件个性化定制模块、整体模具价格检索模块、分组价格检索模块和分组直接计算模块,并对各模块的要点作了详尽分析。
     第五章在前面几章理论研究的基础上,以Visual FoxPro 9.0为系统开发工具,开发了注射模计算机辅助智能报价系统,并对开发的原型系统的各个功能模块进行了概述。最后给出了一个注射模具价格估算的应用实例,对系统的可行性作了验证。
     第六章总结了全文的主要研究内容成果,并对今后研究方向提出展望。
With the rapid development of modern industry and the sharp shortening of products' upgrading period, demand for moulds is ever growing. This leads to more opportunity to mold-making companies as well as fiercer competition. In order to survive and keep on developing, mold-making companies must make arduous efforts for more orders. So how to quote a mold accurately and quickly becomes an important problem when in the face of inquiry. Thus a research was made by this paper. Having consulted many literatures, this paper put forward the method of quoting by the parts and customization and adjustability of quotation software in a creative way. Using AHP and CBR technology, combined with automatic extraction of CAD parameters, a CAD intelligent quotation model was established and a prototype system was developed. The outlines of each chapter of this paper are as follows:
     Chapter one discussed the importance of quoting a mold quickly and exactly at first, and then focused on reviewing mold quotation methods and current situation of computer-aided mould quotation system at home and abroad. Lastly it proposed the contents and goals of the research.
     Chapter two presented the basic principles、phytogenies and key technologies of AHP and CBR in detail. This chapter laid the emphases on the construction of AHP hierarchical structure and key technologies of CBR such as case presentation, case storage, case retrieval, case adaptation and case-library update.
     Chapter three extracted several features that play an important role in the cost of injection molds, and then introduced a presentation model using the above features and mold price. Intelligent extraction of DXF files' information was studied in this paper. It adopted improved Kolodner distance as the formula to calculate similarity between price cases. Considering differences between features, this paper defined similarity functions for digital features and similarity tables for character features. With respect to the diffculty of determing case feature weights, a pertinent research was made in this paper using AHP to make weights-determing automatic and systematic. At last how to update and maintain the price case library of injection molds was also discussed.
     Chapter four introduced the quoting flow of the intelligent quotation model. It discussed the four main modules in detail: customization module, quoting on the whole mold module, quoting on the parts module and part calculating module.
     Chapter five, on the basis of theory research in former chapters, built a computer-aided quotation system for injection molds with Visual FoxPro 9.0 as the development tool, and then introduced each function module of the system in general. In the end of this chapter, an example of injection molds was used to test the system's reliability.
     Chapter six summarized the main contents and achievements of this paper, and put forward the direction for the future research.
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