基于流程挖掘的机器人流程自动化优化部署方法

doi:10.19678/j.issn.1000-3428.0069301

计算机工程 ›› 2025, Vol. 51 ›› Issue (8): 396-405. doi: 10.19678/j.issn.1000-3428.0069301

基于流程挖掘的机器人流程自动化优化部署方法

高庆鑫¹, 刘聪¹^,²^,*(), 张在贵³, 郭娜⁴, 苏轩¹, 曾庆田²

1. 山东理工大学计算机科学与技术学院，山东淄博 255002
2. 山东科技大学计算机科学与工程学院，山东青岛 266590
3. 济南浪潮数据技术有限公司，山东济南 250100
4. 山东理工大学电气与电子工程学院，山东淄博 255002

收稿日期:2024-01-25 修回日期:2024-03-25 出版日期:2025-08-15 发布日期:2025-08-27
通讯作者: 刘聪
基金资助:
科技部科技创新2030—“新一代人工智能”重大项目(2022ZD0119501); 国家自然科学基金面上项目(52374221); 山东省泰山学者特聘专家支持项目(ts20190936); 山东省泰山学者工程专项基金(ts20190936); 山东省泰山学者工程专项基金(tsqn201909109); 山东省自然科学基金优秀青年基金(ZR2021YQ45); 山东省高等学校青创科技计划创新团队项目(2021KJ031)

Optimized Deployment Method of Robotic Process Automation Based on Process Mining

GAO Qingxin¹, LIU Cong¹^,²^,*(), ZHANG Zaigui³, GUO Na⁴, SU Xuan¹, ZENG Qingtian²

1. School of Computer Science and Technology, Shandong University of Technology, Zibo 255002, Shandong, China
2. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, Shandong, China
3. Jinan Inspur (Jinan Data) Technology Co., Ltd., Jinan 250100, Shandong, China
4. School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255002, Shandong, China

Received:2024-01-25 Revised:2024-03-25 Online:2025-08-15 Published:2025-08-27
Contact: LIU Cong

摘要/Abstract

摘要：

作为组织数字化转型的关键技术，机器人流程自动化(RPA)近年来得到了学术界和产业界的广泛关注。成功部署RPA的关键是确定哪些活动应该自动化。然而，现有的部署策略缺乏对流程的分析，导致RPA机器人的部署错误，造成资源的浪费。此外，已有的基于流程挖掘的RPA机器人部署方法过度依赖于专家的领域知识，缺乏通用性。针对上述问题，将流程挖掘与RPA相结合，提出一种基于流程挖掘的RPA机器人优化部署方法。首先提出从事件日志中挖掘全局流程模型的方法，挖掘得到含有时间信息的时间Petri网模型；其次通过关键流程路径识别方法得到关键流程路径；最后提出RPA机器人优化部署策略，结合时间和成本约束确定RPA机器人的最佳部署结点集合。该方法已在开源流程挖掘工具平台ProM中实现，并将其与已有的4种部署方法进行时间效率提升实验比较。实验结果表明，与其他部署方法相比，该方法在不依赖于专家领域知识的前提下，流程的性能提升率为22%~41%，RPA机器人的部署正确率达到1，验证了该方法的通用性和准确性。

关键词: 流程挖掘, 机器人流程自动化, 优化部署, 模型挖掘, 时间Petri网

Abstract:

As a pivotal technology driving organization digital transformation, Robotic Process Automation (RPA) has garnered significant attention from both the academic and industrial sectors in recent years. However, current deployment strategies suffer from a lack of process analysis, leading to misguided deployment of RPA robots and resource wastage. Furthermore, existing RPA robots deployment methods based on process mining depend overly on domain-specific expertise, limiting their generality. To address these challenges, this study proposes the integration of process mining with RPA robots and presents a deployment method for RPA robots based on process mining. The method is initiated by introducing an approach to mine the global process model from event logs and extracting a Time Petri net containing temporal information. Subsequently, critical process paths are identified using a method designed to recognize key process paths. Finally, an optimization deployment strategy for RPA robots is introduced, which determines the optimal deployment node set considering the time and cost constraints. The proposed method is implemented using ProM, an open-source process mining tool platform. It is compared with four deployment methods in experiments that focus on improving time efficiency. The experimental results indicate that, compared to other deployment methods, this approach results in a time efficiency improvement ranging from 22% to 41%, and the deployment accuracy reaches 1, without relying on domain-specific expert knowledge, validating its generality and accuracy.

Key words: process mining, Robotic Process Automation (RPA), optimized deployment, model mining, time Petri nets

高庆鑫, 刘聪, 张在贵, 郭娜, 苏轩, 曾庆田. 基于流程挖掘的机器人流程自动化优化部署方法[J]. 计算机工程, 2025, 51(8): 396-405.

GAO Qingxin, LIU Cong, ZHANG Zaigui, GUO Na, SU Xuan, ZENG Qingtian. Optimized Deployment Method of Robotic Process Automation Based on Process Mining[J]. Computer Engineering, 2025, 51(8): 396-405.

https://www.ecice06.com/CN/Y2025/V51/I8/396

图/表 15

图1 时间Petri网示例

Fig.1 Time Petri net example

图2 基于流程挖掘的RPA机器人优化部署方法框架

Fig.2 Framework of the optimized deployment method of RPA robots based on process mining

图3 ProM插件实例

Fig.3 The ProM plug example

图4 时间Petri网及关键流程路径

Fig.4 Time Petri net its critical process path

图5 RPA机器人的优化部署过程

Fig.5 Optimized deployment process of the RPA robots

图6 优化后的流程性能信息

Fig.6 Optimized process performance information

图7 流程完成时间变化结果(活动持续时间下限)

Fig.7 Results of process completion time change results (lower limit of activity duration)

图8 流程完成时间变化结果(活动持续时间上限)

Fig.8 Results of process completion time change (upper limit of activity duration)

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