Process mining methods and tools are largely used in industry to monitor and improve operational processes. This paper presents a new technique to analyze performance characteristics of processes using event data. Based on event sequences and their timestamps, semi-Markov models are discovered. The discovered models are further used for performance what-if analysis of the processes. The paper studies a trade-off between the order of models discovered and accuracy of representing performance information. The proposed discovery and analysis techniques are implemented and tested on real-world event data.
翻译:开采工艺的方法和工具主要用于工业监测和改进作业过程,本文件介绍了一种利用事件数据分析过程性能特点的新技术,根据事件序列及其时间戳,发现了半马尔科夫模型,发现的模式进一步用于对过程进行何种分析;论文研究了所发现的模型顺序与表现效果信息的准确性之间的权衡;拟议的发现和分析技术在现实世界事件数据上得到实施和测试。