一种基于案例推理的零件热处理装炉算法

A Furnace Loading Algorithm Based on Case-Based Reasoning for Heat Treatment Operation

针对热处理调度中分炉分批任务,先利用数据挖掘方法,从历史案例中提取有价值的知识信息;再将知识运用于案例推理过程,利用规则引擎对待处理任务进行分炉分批求解,得到新实例;最后根据新产生的应用实例,对案例库进行扩充,实现从"案例-知识-规则-应用实例-案例"的闭环流程。历史记录和新产生的实例可用于生成并丰富知识,使得推理准确率随着知识的积累不断提升。最后通过实例验证了该方案的可行性与可用性。

To the batching tasks in heat treatment scheduling,this paper introduced a set of knowledge that can be extracted from historical cases by data mining techniques from the perspective of case-based reasoning.In addition,the rule templates used for rule engine and the reasoning routines were designed,and new batches are got after calculation.New batches will be added to historical cases.The whole procedure is a closed-loop process that is from ＂Case＂to＂Knowledge＂to＂Rule＂to＂Inferenced Batch＂and back to＂Case＂.The newly generated cases can enrich knowledge,so that the accuracy of this algorithm will increase with time.Finally,an example is used to verify the feasibility and availability of the solution.