基于过程挖掘的物流运作风险发现研究

为了探究物流运作过程中存在的风险,提高物流运作效率,增强物流企业管理能力,以真实的事件日志为基础,运用过程挖掘方法发现物流企业运作过程中的风险。首先以Petri网理论为基础,构建了理想的工作模型,然后使用过程挖掘工具ProM,运用模糊挖掘算法和启发式挖掘算法,对物流运作过程中产生的真实事件日志进行挖掘,获得实际的客观视图,最后利用ProM工具的一致性检查发现物流运作过程中的异常行为模式,并分析物流运作过程中的偏差以及存在的风险。结果表明,过程挖掘能客观地揭示事件日志中活动之间的依赖关系,并发现物流企业自身运作过程中的偏差和风险。研究结果为全面、系统地分析物流企业潜在风险提供了新思路,有助于物流企业发现运作过程中的问题,对物流企业优化运作过程和提高管理效率具有重要的借鉴意义。

Research on logistics operation risk discovery based on process mining

In order to explore the risks existing in the process of logistics operation, improve the efficiency of logistics operation and enhance the management ability of logistics enterprises, based on the real event log, the process mining method is used to discover the potential risks in the process of logistics operation. Firstly, the ideal work model is constructed by Petri net. Then using the ProM tool, the Fuzzy Miner and the Heuristics Miner are used to mine the real event log in the process of logistics operation to obtain the actual objective view. Finally, The conformance checking of ProM tools is used to find out the abnormal behavior patterns in the process of logistics operation, and analyze the deviations and risks in the process of logistics operation. The results show that the process mining algorithms can objectively reveal the dependency relations between activities in the event log, and find out the deviation and risks in the process of logistics operation. The research results provide new ideas for the comprehensive and systematical analysis of potential risks of logistics enterprises, help logistics enterprises to find problems, and have some reference for logistics enterprises to optimize the operation process and improve management efficiency.