知识与财富的链接
备件需求不确定性表现为随机性、多样性、时变性、信息不充分性,预测过程中很难精确地描述备件消耗与影响因素之间错综复杂的关系.以智能计算理论为代表的处理不确定性的各种方法和工具迅速发展.梳理处理备件需求预测不确定性的相关文献,按照不确定性的随机性、模糊性、不完全性、复合不确定性四大类属性,对每个大类分别进行了综述,并总结了相关研究的局限性与发展方向.研究成果可为装备备件管理提供参考.
It is difficult to describe the complex relationship between spare parts consumption and influencing factors accurately in the prediction process. The resons includes the randomness, diversity, time-varying and insufficient information of spare parts demand. The Intelligent Computing theories and tools for dealing with uncertainty have developed rapidly. This article summarized relevant literature on handling the uncertainty of spare parts demand prediction, according to the four categories of uncertainty, namely, randomness, fuzziness, incompleteness and compound uncertainty. The limitations and development direction of relevant research are summarized. The research results serve as references for equipment spare parts management.
