基于工作流日志的组织结构挖掘研究*

为了从工作流日志中挖掘组织结构设置和执行者之间的交互信息,分析了工作流日志中的活动执行者的信息,并引入多种距离公制用以刻画日志中活动执行者间的各种关系度的强弱,提出了组织结构的三种挖掘方法,即默认挖掘、基于活动相似度的挖掘和基于过程实例相似度的挖掘。通过以上方法对工作流日志进行组织结构挖掘得到组织网络,组织网络能够客观地反映出参与工作流程的组织实体并正确表示出组织结构。通过一个挖掘实例对挖掘过程进行了验证和说明。     

工作流日志中的工作流模式图挖掘技术研究

工作流挖掘技术能够从系统的执行日志中构建出过程,大部分过程挖掘方法都使用了一种图形化的方式来表示模型,也就是控制流图.讨论了工作流模式图挖掘,它实际上是工作流挖掘的一种扩展;对其中所涉及的问题进行了剖析,并介绍了一种模式图挖掘算法.     

多步过程挖掘在工作流重构中的应用研究

针对工作流实例偏离预定义模型的实际情况,提出一种基于工作流日志的多步过程挖掘方法,从而实现工作流重构。基于工作流日志构建马尔可夫转移矩阵,定义关系挖掘规则分析过程中的逻辑关系,设计过程挖掘算法建立活动间的实际结构关系,以某电梯企业标梯合同签订流程为例验证方法的可行性和适用性。     

Business process mining: An industrial application

Contemporary information systems (e.g., WfM, ERP, CRM, SCM, and B2B systems) record business events in so-called event logs. Business process mining takes these logs to discover process, control, data, organizational, and social structures. Although many researchers are developing new and more powerful process mining techniques and software vendors are incorporating these in their software, few of the more advanced process mining techniques have been tested on real-life processes. This paper describes the application of process mining in one of the provincial offices of the Dutch National Public Works Department, responsible for the construction and maintenance of the road and water infrastructure. Using a variety of process mining techniques, we analyzed the processing of invoices sent by the various subcontractors and suppliers from three different perspectives: (1) the process perspective, (2) the organizational perspective, and (3) the case perspective. For this purpose, we used some of the tools developed in the context of the ProM framework. The goal of this paper is to demonstrate the applicability of process mining in general and our algorithms and tools in particular.     

Classification and evaluation of timed running schemas for workflow based on process mining

The system running logs of a workflow contain much information about the behavior and logical structure between activities. In this paper, a mining approach is proposed to discover the structural and temporal model for a workflow from its timed running logs. The mining results are represented in the formalized form of Petri nets extended with two timing factors that allows validation or verification the actual behaviors, especially the temporal constraints between activities. According to the reachability graph of the extended Petri net model mined, all running schemas of a workflow can be generated, which defines the temporal constraints between running activities. By calculating the earliest and latest start time of each activity, the earliest starting and latest existing time of each state in the running schema can be determined. Based on the temporal relations between the timing factors of each running state, the running schemas can be classified into six classes. The effects of the six classes of running schemas on the implementation of the whole workflow are evaluated so as to obtain the best one that can ensure the workflow is finished in the shortest time. The standards for the ideal, reliable and favorable running schemas and their existence conditions are discussed, which can be used to evaluate the running logs and control the future running of a workflow.     

Time prediction based on process mining

Process mining allows for the automated discovery of process models from event logs. These models provide insights and enable various types of model-based analysis. This paper demonstrates that the discovered process models can be extended with information to predict the completion time of running instances. There are many scenarios where it is useful to have reliable time predictions. For example, when a customer phones her insurance company for information about her insurance claim, she can be given an estimate for the remaining processing time. In order to do this, we provide a configurable approach to construct a process model, augment this model with time information learned from earlier instances, and use this to predict e.g., the completion time. To provide meaningful time predictions we use a configurable set of abstractions that allow for a good balance between “overfitting” and “underfitting”. The approach has been implemented in ProM and through several experiments using real-life event logs we demonstrate its applicability.     

A methodology and tool environment for process analysis and reengineering

Most private and public organizations have recently turned their attention to the process by which they operate, to improve service and product quality and customer satisfaction. To support business process reengineering, methods and tools for process modeling and analysis are required. The paper presents the ARTEMIS methodology and associated tool environment for business process analysis for reengineering. In the ARTEMIS methodological framework, business processes are modeled as workflows and are analyzed according to an organizational structure perspective and an operational structure perspective. With these two perspectives, the analyst can plan reengineering interventions based on the degree of autonomy/dependency of organization units in terms of coupling, and the inter-process semantic correspondences, in terms of data and operation similarity, respectively. The ARTEMIS methodology and associated tool environment have been conceived and applied in the framework of the PROGRESS research project. In the paper, we report on a reengineering case study of this project involving the Italian Ministry of Justice.     

Exploring the CSCW spectrum using process mining

Process mining techniques allow for extracting information from event logs. For example, the audit trails of a workflow management system or the transaction logs of an enterprise resource planning system can be used to discover models describing processes, organizations, and products. Traditionally, process mining has been applied to structured processes. In this paper, we argue that process mining can also be applied to less structured processes supported by computer supported cooperative work (CSCW) systems. In addition, the ProM framework is described. Using ProM a wide variety of process mining activities are supported ranging from process discovery and verification to conformance checking and social network analysis.     

Business alignment: using process mining as a tool for Delta analysis and conformance testing

Increasingly, business processes are being controlled and/or monitored by information systems. As a result, many business processes leave their “footprints” in transactional information systems, i.e., business events are recorded in so-called event logs. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs, i.e., the basic idea of process mining is to diagnose business processes by mining event logs for knowledge. In this paper we focus on the potential use of process mining for measuring business alignment, i.e., comparing the real behavior of an information system or its users with the intended or expected behavior. We identify two ways to create and/or maintain the fit between business processes and supporting information systems: Delta analysis and conformance testing. Delta analysis compares the discovered model (i.e., an abstraction derived from the actual process) with some predefined processes model (e.g., the workflow model or reference model used to configure the system). Conformance testing attempts to quantify the “fit” between the event log and some predefined processes model. In this paper, we show that Delta analysis and conformance testing can be used to analyze business alignment as long as the actual events are logged and users have some control over the process.

工作流模型结构化挖掘方法研究

流程挖掘是业务流程管理(business process management,BPM)研究的一项重要内容.提出了一种结构化挖掘方法,实现从事务型日志中挖掘出工作流网.该方法基于工作流模型的4种基本结构(顺序、并行、选择和循环)进行挖掘.定义了可挖掘的工作流模型--结构化工作流网(structural workflow net,SWF),从日志预处理,流程挖掘方法和合理性验证3个方面对挖掘算法进行了详细描述,证明挖掘出的工作流模型满足合理性和安全性的同时,具有可读性和容易理解的特点.     

基于JBPM的服务动态编排及迁移方案

为了适应复杂环境下动态多变的业务需求,对以服务为核心的流程动态编排和再造提供支持,提出了基于JBPM工作流的流程动态编排与迁移方案,该方案分析了目前工作流在流程编排方面的局限性;结合柔性工作流的特点,给出了流程动态编排的模型,并对流程变更所产生的4类操作做了形式化的描述,通过对流程变更引发的流程进行迁移继而实现接续执行这一问题的研究,提出一种流程迁移算法。最后通过实例和性能测试工具验证了算法的可行性和高效性。     

Workflow simulation for operational decision support using event graph through process mining

It is increasingly common to see computer-based simulation being used as a vehicle to model and analyze business processes in relation to process management and improvement. While there are a number of business process management (BPM) and business process simulation (BPS) methodologies, approaches and tools available, it is more desirable to have a systemic BPS approach for operational decision support, from constructing process models based on historical data to simulating processes for typical and common problems. In this paper, we have proposed a generic approach of BPS for operational decision support which includes business processes modeling and workflow simulation with the models generated. Processes are modeled with event graphs through process mining from workflow logs that have integrated comprehensive information about the control-flow, data and resource aspects of a business process. A case study of a credit card application is presented to illustrate the steps involved in constructing an event graph. The evaluation detail is also given in terms of precision, generalization and robustness. Based on the event graph model constructed, we simulate the process under different scenarios and analyze the simulation logs for three generic problems in the case study: 1) suitable resource allocation plan for different case arrival rates; 2) teamwork performance under different case arrival rates; and 3) evaluation and prediction for personal performances. Our experimental results show that the proposed approach is able to model business processes using event graphs and simulate the processes for common operational decision support which collectively play an important role in process management and improvement.     

Business process analysis in healthcare environments: A methodology based on process mining

Performing business process analysis in healthcare organizations is particularly difficult due to the highly dynamic, complex, ad hoc, and multi-disciplinary nature of healthcare processes. Process mining is a promising approach to obtain a better understanding about those processes by analyzing event data recorded in healthcare information systems. However, not all process mining techniques perform well in capturing the complex and ad hoc nature of clinical workflows. In this work we introduce a methodology for the application of process mining techniques that leads to the identification of regular behavior, process variants, and exceptional medical cases. The approach is demonstrated in a case study conducted at a hospital emergency service. For this purpose, we implemented the methodology in a tool that integrates the main stages of process analysis. The tool is specific to the case study, but the same methodology can be used in other healthcare environments.     

基于Petri网化简方法的工作流模型验证

经营过程的建模、分析与优化是支持企业经营过程重组（BPR）的重要基础,行之有 效的模型分析方法是成功进行模型分析的重要的关键技术问题．在深入分析了经营过程工作 流模型特点的基础上,本文提出了一种基于Petri 网图形化简规则的业务过程模型分析与验 证方法,证明了所提出这套化简规则的完备性和多项式时间的复杂性．并应用一个实例证明 了所提出方法的有效性．     

基于语义描述的Web服务工作流动态组合研究

传统静态工作流很难适应动态的、灵活的现代业务流程。近年来Web服务技术不断发展,使得工作流中的活动以Web服务形式的实现,而且工作流本身也可以以Web服务的形式被调用,特别是语义Web技术的发展,为计算机实现自动Web服务工作流提供了可能。本文基于本体论提出了一个半结构化工作流本体模型,并在此基础上设计了基于Agent技术的Web服务工作流系统。     

基于过程挖掘的工作流性能分析

介绍了工作流性能的分析基础和概念。针对复杂和具有非确定性的业务流程,通过基于 工作流日志的工作流过程挖掘算法,得到反映系统基本性能的工作流性能分析网。并应用到具有动 态、模糊控制流程的工作流系统的性能分析中。     

Merging event logs for process mining: A rule based merging method and rule suggestion algorithm

In an inter-organizational setting the manual construction of process models is challenging because the different people involved have to put together their partial knowledge about the overall process. Process mining, an automated technique to discover and analyze process models, can facilitate the construction of inter-organizational process models. This paper presents a technique to merge the input data of the different partners of an inter-organizational process in order to serve as input for process mining algorithms. The technique consists of a method for configuring and executing the merge and an algorithm that searches for links between the data of the different partners and that suggests rules to the user on how to merge the data. Tool support is provided in the open source process mining framework ProM. The method and the algorithm are tested using two artificial and three real life datasets that confirm their effectiveness and efficiency.     

一种基于Web服务的工作流过程模型

工作流管理系统实施是提高企业核心竞争力的有力措施,而工作流过程模型是整个工作流管理系统的基础,在Web服务的基础上提出了一种分层的过程模型,同时在过程模型中增加新的元素事务活动和事务节点,增加了模型对工作流管理系统的分布异构环境以及事务特性的支持.     

基于频繁图模式挖掘的质量管理过程分析

提出了基于频繁图模式挖掘的工作流频繁活动序列分析的方法,分析了质量管理过程中的关键活动链结构,辅助质量管理过程控制和改进。针对质量管理过程循环结构多且复杂的特点,提出了一种基于Apriori的改进频繁活动序列挖掘算法,设计了新的子图连接算子,减少冗余候选频繁子图的产生。以质量外审意见处理流程的分析为例对该算法进行了说明和分析。