零件主干工艺路线提取与工艺排序方法及其在锻压装备中的应用

发布时间：2018-05-28 16:02

本文选题：特征加工方法 + 典型主干工艺路线　；参考：《浙江大学》2013年硕士论文

【摘要】：零件工艺设计直接关系到产品的生产效率与质量。在激烈的市场竞争环境下,企业如何提高零件的工艺创新能力,已成为产品设计制造的一个重要问题。本文结合企业需求,研究了零件特征加工方案决策技术、典型主干工艺路线提取技术和零件工艺排序技术,开发了锻压装备工艺设计系统,并且系统在锻压装备产品的零件工艺设计中得到应用,取得了良好的效果。全文主要内容包括：第1章分析了传统零件工艺设计方法存在的问题,介绍了零件工艺设计的关键技术及其研究现状,阐述了本文的研究背景、内容及组织构架。第2章提出了一种基于支持向量机的零件特征加工方案决策方法。介绍了支持向量机的二值分类算法和多值分类算法；建立了特征加工方法选择的集成决策模型,并以内圆特征为例,介绍了子支持向量机的模型结构、输人输出参数的预处理、惩罚参数及核函数的选择；利用LIBSVM软件与Matlab平台实现了零件特征参数的训练与预测。第3章提出了应用聚类分析技术提取零件典型主干工艺路线的方法。构建了主干工艺路线的相似度度量因子,提出了对主干工艺路线进行相似度计算的多级相似度综合度量方法,在相似度计算基础上,构建了主干工艺路线设计结构矩阵并对矩阵数据进行降噪处理；为降低聚类划分的难度和复杂性,运用迭代聚类算法实现了主干工艺路线设计结构矩阵的聚类划分,并从聚类簇中提取到典型主干工艺路线；以锻压装备制造企业工艺数据的典型主干工艺路线提取为例,验证了该方法的有效性。第4章提出了一种基于典型主干工艺路线的零件加工工艺排序方法。结合工步优先权系数和工步约束矩阵,建立了工艺排序的数学模型；利用粒子群算法来进行工步排序,并对所得的最优工步元序列进行组合,形成工序,以获得完整的工艺路线；以锻压机的主轴零件工艺排序进行了应用验证。第5章结合具体的企业项目,开发了锻压装备工艺设计系统,并且该系统在企业工艺设计中得到成功运行与应用,验证了本文所提出的理论和方法的可行性及实用性。第6章对全文的主要研究内容和创新点进行了总结,并展望了以后相关领域工作的努力方向。
[Abstract]:Part process planning is directly related to the production efficiency and quality of products. In the fierce market competition, how to improve the technological innovation ability of parts has become an important problem in product design and manufacture. According to the requirements of the enterprise, this paper studies the decision technology of feature processing scheme, the extraction technology of typical trunk process route and the technology of part process sequencing, and develops the process planning system of forging equipment. The system has been applied in the process design of forging equipment, and good results have been obtained. The main contents of this paper are as follows: The first chapter analyzes the problems existing in the traditional part process planning method, introduces the key technology of the part process planning and its research status, and expounds the research background, content and organization structure of this paper. In chapter 2, a part feature processing scheme decision method based on support vector machine (SVM) is proposed. The binary classification algorithm and multi-valued classification algorithm of support vector machine are introduced, the integrated decision model of feature processing method selection is established, and taking the inner circle feature as an example, the model structure of sub-support vector machine and the pretreatment of input output parameters are introduced. The selection of penalty parameters and kernel functions, and the training and prediction of feature parameters of parts by using LIBSVM software and Matlab platform are realized. In chapter 3, a method of extracting typical trunk process route by cluster analysis is presented. The similarity measure factor of the trunk process route is constructed, and a multi-level similarity comprehensive measure method is proposed to calculate the similarity degree of the trunk process route, which is based on the similarity calculation. In order to reduce the difficulty and complexity of clustering, the main process route design structure matrix is realized by iterative clustering algorithm. The typical trunk process route is extracted from the cluster, and the effectiveness of this method is verified by taking the typical trunk process route extraction from the process data of forging equipment manufacturing enterprise as an example. In chapter 4, a part processing scheduling method based on typical trunk process route is proposed. Combined with step priority coefficient and step constraint matrix, the mathematical model of process scheduling is established, and the process is formed by combining the optimal step element sequence with particle swarm optimization algorithm. In order to obtain a complete process route, the main shaft parts of the forging press process sequencing has been applied to verify. In chapter 5, the process planning system of forging equipment is developed, and the system is successfully run and applied in the enterprise process planning, which verifies the feasibility and practicability of the theory and method proposed in this paper. Chapter 6 summarizes the main contents and innovations of the paper, and looks forward to the future work in related fields.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TH162;TG315

【参考文献】