注塑模改模知识归纳方法研究

A Study of Knowledge Induction for Injection Mould Repair

改模方案被许多模具企业视为重要的企业知识,然而随着改模方案的不断增加,如何从大量不规范表达的改模方案中归纳改模知识成为有效利用改模方案的关键。本文在分析改模方案表达的基础上,提出了一种基于粗糙集的改模知识归纳模型。首先分别从特征和特征值表达两个方面建立改模方案的分层递阶表达模型及知识建模方法。然后结合实例给出基于方案描述级别的方案重构和模糊化方法,以及在不同方案描述级别下基于粗糙集的改模知识归纳方法。最后通过利用粗糙集软件工具包ROSETTA实例验证了改模方案表达模型及其知识归纳方法。

The injection mould repair schemes are viewed as pieces of knowledge in many mould manufacturers. With the increase of injection mould repair schemes, knowledge induction becomes the key to using knowledge effectively in making injection mould repair schemes. According to the analysis of representation characteristics in injection mould repair schemes, knowledge induction model based on rough set for repair schemes is firstly put forward in this paper. Firstly, as the basis of the model, feature and concept hierarchy model （FCHM） is presented from two aspects： feature hierarchy and concept hierarchy. Then knowledge representation for repair schemes can be provided by using FCHM. After reconstruction and fuzzy process for repair schemes, knowledge induction can be done by using attribute reduction and rule induction based on rough set. Finally, through the toolkit software of rough set theory named ROSETTA, an experiment is carried out to induce knowledge from repair schemes in accordance with the representative models on different layers.