Abstract: To cope with intense market competition, automotive enterprises need to constantly revise product configuration schemes, offering a more diversified range of configurations to meet users' personalized needs. Configuration changes have a broad and complex impact to part engineering changes. This paper innovatively proposes a new model for configuration changes management. By using the multi-structured and multi-featured databases accumulated by enterprises in change management and combing application of data mining techniques, it develops a configuration change decision-making model based on a knowledge graph. Utilizing this model, through intelligent analysis of product configuration plans and bill of material (BOM), it automatically identifies functional characteristics and parts involved in the changes, generates configuration combinations automatically, and recommends part engineering change proposals automatically. It enhances the efficiency and accuracy of configuration changes.

Key words: configuration changes; knowledge graph; part engineering changes; BOM

摘要： 为了应对激烈的市场竞争，车企需要不断对产品配置方案进行变更，以更加多元的配 置系列满足用户个性化需求。针对配置变更影响范围广泛、零件工程变更复杂的特点，文章 提出了一种配置变更管理的新模式，利用企业在变更管理中积累的多结构、多特征数据库， 综合运用数据挖掘技术，开发了一种基于知识图谱的配置变更决策模型，利用该模型，通过 对产品配置规划书和整车物料清单（BOM）的智能解析，自动识别涉及变更的功能特征及零 件，自动生成配置组合，并自动推荐零件工程变更方案，极大提升了配置变更的效率和准确 率。

关键词: 配置变更；知识图谱；零件工程变更；BOM