基于过程挖掘与复杂网络集成的制造过程资源建模与关键加工节点识别

doi:10.3901/JME.2019.03.169

机械工程学报 ›› 2019, Vol. 55 ›› Issue (3): 169-180.doi: 10.3901/JME.2019.03.169

基于过程挖掘与复杂网络集成的制造过程资源建模与关键加工节点识别

董晨阳, 郑小云, 余建波

同济大学机械与能源工程学院上海 201804

收稿日期:2018-03-09 修回日期:2018-07-29 出版日期:2019-02-05 发布日期:2019-02-05
通讯作者: 余建波(通信作者),男,1978年出生,博士,教授,博士研究生导师。主要研究方向为智能制造、设备智能维护。E-mail:jbyu@tongji.edu.cn
作者简介:董晨阳,男,1994年出生。主要研究方向为工作流管理,智能制造。E-mail:yunyiqingyang@163.com;郑小云,女,1993年出生,硕士研究生。主要研究方向为深度学习,智能制造。E-mail:xiaoyuncloudy@163.com
基金资助:
国家自然科学基金（71777173）、中央高校基本科研业务费学科项目和上海科委创新科技行动计划（17511109204）资助项目。

Resource Modeling of Manufacturing Process and Critical Nodes Recognition Based on the Integration of Process Mining and Complex Network

DONG Chenyang, ZHENG Xiaoyun, YU Jianbo

School of Mechanical Engineering, Tongji University, Shanghai 201804

Received:2018-03-09 Revised:2018-07-29 Online:2019-02-05 Published:2019-02-05

摘要/Abstract

摘要： 为了解决多任务复杂制造过程中的工作流变异导致的流程和资源的不确定性，进而导致制造资源模型出现实时变化，提出了基于过程挖掘与复杂网络集成的制造过程资源模型，得到了流程与资源信息集成的资源复杂网络模型与分析方法。首先，从制造过程中实时产生的事件日志出发，提出了一种基于统计α算法的过程挖掘算法，解决了制造过程工作流重构问题，可实时发掘实际制造过程中的工作流模型。接着，通过集成过程挖掘算法和复杂网络理论，构建了集流程信息与资源信息于一体的资源网络模型，提出了资源节点与流程节点的关联性分析方法，识别制造过程中的关键加工节点。最后，结合一个复杂的锥齿轮轴-轴承套组件装配过程实例，全面验证了所提出方法在制造过程工作流重构、资源网络模型建模、资源特性分析与关键加工节点的识别上的有效性。

关键词: 复杂网络, 工作流模型, 过程挖掘, 制造过程, 资源建模

Abstract: In order to solve the uncertainty of the resource network caused by the process variation under the multi-tasks complex manufacturing work-flow, a manufacturing resource model that based on the integration of process mining and complex network theory is proposed. Firstly, a manufacturing work-flow reconstruction method that based on process mining statistical α-algorithm is proposed to obtain work-flow model in real time from manufacturing event logs. Secondly, a resource network model that based on the integration of process mining and complex network theory combines process information and resource information, which can be used to analyze the relevance between resource node and process node, and to recognize the critical nodes in manufacturing work-flow. Finally, with the application of an assembly process, the effectiveness of the methods on manufacturing process reconstruction, resource network modeling, resource characteristic analysis and critical nodes recognition is verified.

Key words: complex network, manufacturing process, process mining, resource modeling, work-flow model

中图分类号:

TG156

董晨阳, 郑小云, 余建波. 基于过程挖掘与复杂网络集成的制造过程资源建模与关键加工节点识别[J]. 机械工程学报, 2019, 55(3): 169-180.

DONG Chenyang, ZHENG Xiaoyun, YU Jianbo. Resource Modeling of Manufacturing Process and Critical Nodes Recognition Based on the Integration of Process Mining and Complex Network[J]. Journal of Mechanical Engineering, 2019, 55(3): 169-180.

参考文献

[1] 林忠钦,来新民,金隼,等. 复杂产品制造精度控制的数字化方法及其发展趋势[J]. 机械工程学报,2013,49(6):103-113. LIN Zhongqin,LAI Xinmin,JIN Wei,et al. Digital method and development trend of manufacturing product accuracy control[J]. Journal of Mechanical Engineering,2013,49(6):103-113.
[2] SHETTY J,ADIBI J. Discovering important nodes through graph entropy the case of Enron email database[C]//Kdd Proceedings of International Workshop on Link Discovery,2005:74-81.
[3] 姜洪权,高建民,陈富民,等. 基于网络特性的分布式复杂机电系统脆弱性分析[J]. 计算机集成制造系统,2009,15(4):791-796. JIANG Hongquan,GAO Jianmin,CHEN Fumin,et al. Vulnerability analysis of distributed complex electromechanical systems based on network characteristics[J]. Journal of Computer Integrated Manufacturing Systems,2009,15(4):791-796.
[4] PAGE L,BRIN S,MOTWANI R,et al. The PageRank citation ranking:Bringing order to the web[R]. Stanford InfoLab,1999.
[5] LI Q,ZHOU T,LÜ L,et al. Identifying influential spreaders by weighted LeaderRank[J]. Physica A:Statistical Mechanics and its Applications,2014,404:47-55.
[6] 顾亦然,朱梓嫣. 基于LeaderRank和节点相似度的复杂网络重要节点排序算法[J]. 电子科技大学学报,2017,46(2):441-448. GU Yiran,ZHU Ziyan. Ranking algorithm of important nodes in complex networks based on LeaderRank and node similarity[J]. Journal of University of Electronic Science and Technology of China,2017,46(2):441-448.
[7] DUENAS-OSORIO L,VEMURU S M. Cascading failures in complex infrastructure systems[J]. Structural Safety,2009,31(2):157-167.
[8] 梁峰,江志斌,陶俐言. 基于元资源的制造资源建模方法研究[J]. 计算机集成制造系统,2008,14(12):2306-2311. LIANG Feng,JIANG Zhibin,TAO Liyan. Research on modeling method of manufacturing resources based on meta-resources[J]. Computer Integrated Manufacturing Systems,2008,14(12):2306-2311.
[9] TURSI A,PANETTO H,MOREL G,et al. Ontological approach for products-centric information system interoperability in networked manufacturing enterprises[J]. Annual Reviews in Control,2009,33(2):238-245.
[10] 朱李楠. 云制造环境下资源建模及其匹配方法研究[D]. 杭州:浙江工业大学,2014. ZHU Linan. Research on resource modeling and matching method in cloud manufacturing environment[D]. Hangzhou:Zhejiang University of Technology,2014.
[11] TAYLOR I J,DEELMAN E,GANNON D B,et al. Workflows for e-science:Scientific workflows for grids[M]. London:Springer Publishing Company,Incorporated,2014.
[12] LIU T,YI H,NI Z,et al. A closed-loop workflow management technique based on process mining[C]//International Conference on Mechatronics and Machine Vision in Practice. IEEE,2009:435-440.
[13] 余建波,董晨阳,李传锋,等. 基于统计α算法的临床路径过程挖掘[J]. 浙江大学学报,2017,51(10):1881-1890. YU Jianbo,DONG Chenyang,LI Chuanfeng,et al. Clinical path process mining based on statistical α algorithm[J]. Journal of Zhejiang University,2017,51(10):1881-1890.
[14] MEDEIROS A K A,WEIJTERS A J M M,AALST W M P. Using genetic algorithms to mine process models:Representation,operators and results[M]. Miami:Beta,Research School for Operations Management and Logistics,2005.

基于过程挖掘与复杂网络集成的制造过程资源建模与关键加工节点识别

Resource Modeling of Manufacturing Process and Critical Nodes Recognition Based on the Integration of Process Mining and Complex Network

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