Abstract: In view of the facts that once the workshop disturbance occured, it would seriously affect the production operations of the workshop, in order to deal with disturbances quickly and efficiently, and to restore normal operations of the workshop, a method on intelligent workshop disturbance processing decision was proposed by improved case-based reasoning. The discrete manufacturing workshop disturbance processing under the intelligent manufacturing environment was taken as the research object, the ternary method was used to model the workshop disturbance case, the hierarchical attributes of the case problem domain were analyzed. A multi-dimensional similarity matching algorithm of case feature attributes was proposed, and the corresponding similarity matching formula was designed. Combined with index contribution rate and kernel density estimation, the order relation analysis method was improved to determine the attribute weight values， the accuracy of case matching was improved, the fast and efficient matching of disturbance cases and historical cases was realized, and the specific solutions was provided. The effectiveness and feasibility of the proposed method were verified by a disturbance case of a mold intelligent manufacturing workshop.

Key words: workshop disturbance, discrete workshop, case-based reasoning, order relation analysis method, kernel density estimation

摘要： 车间扰动事件一旦发生会严重影响车间的生产运作。为了快速高效地处理扰动事件，恢复车间正常运作，提出了一种基于改进案例推理的智能车间扰动处理决策方案。以智能制造环境下离散制造车间扰动处理为研究对象，利用三元法对车间扰动案例进行建模，分析了案例问题域的阶梯层次属性，设计了案例特征属性多维相似度匹配算法及对应的相似度计算公式；结合指标贡献率和核密度估计改进了序关系分析法，并计算最终案例属性权重值，提高了案例匹配的精确度，实现了扰动案例与历史案例的快速高效匹配，提供了应对车间扰动的具体解决方案。通过某模具智能制造车间扰动案例验证了所提方法的有效性和可行性。

关键词: 车间扰动, 离散车间, 案例推理, 序关系分析法, 核密度估计