Mining business process variants: Challenges, scenarios, algorithms

During the last years a new generation of process-aware information systems has emerged, which enables process model configurations at buildtime as well as process instance changes during runtime. Respective model adaptations result in a large number of model variants that are derived from the same process model, but slightly differ in structure. Generally, such model variants are expensive to configure and maintain. In this paper we address two scenarios for learning from process model adaptations and for discovering a reference model out of which the variants can be configured with minimum efforts. The first one is characterized by a reference process model and a collection of related process variants. The goal is to improve the original reference process model such that it fits better to the variant models. The second scenario comprises a collection of process variants, while the original reference model is unknown; i.e., the goal is to “merge” these variants into a new reference process model. We suggest two algorithms that are applicable in both scenarios, but have their pros and cons. We provide a systematic comparison of the two algorithms and further contrast them with conventional process mining techniques. Comparison results indicate good performance of our algorithms and also show that specific techniques are needed for learning from process configurations and adaptations. Finally, we provide results from a case study in automotive industry in which we successfully applied our algorithms.     

Complexity Measures for Process Evolution

The foundation for process evolution research is the modelling of process structural complexity. With such a model, process systems can be directed toward acquiring good maintainability attributes according to the principles of engineering. In this paper a process management (PM) model is developed to acquire directly from the target process codes the knowledge hidden among and within components of process systems. With the knowledge acquired by the PM model, process structural complexity measures in terms of partitioning, restructuring and rewriting criteria are developed; a systematic process remodularization schema is derived, and algorithms for scheduling process changes are presented. These criteria and mechanisms are used to guide the process production chain.     

半边图模型之多层次认知系统

针对具有多层次性和复杂性的认知问题提出一个动态可增殖的多层次自组织认知系统,每个层次具有形式上一致的知识表示方法,各层的自组关联、自组聚合、归约和样本表达四个知识处理模型是实现系统自组织层次增殖的核心模型。提出信息粒和容器的概念,信息粒演进流程模拟认知过程的静态归约,容器演进流程对应于认知的动态模拟,这两个流程在每个系统层次上对每个输入样本完成一个完整的模拟认知与归约表达。以自组图演算为理论模型,给出了每个层次内以及相邻层次之间的信息处理与传递的详细设计规范。     

有色量测噪声下机器人同步定位与地图构建

针对有色量测噪声模型,提出一种有色量测噪声下的轮式机器人同步定位与地图构建算法。通过重新组合轮式机器人的过程模型和量测模型,将有色量测噪声量测模型转化为虚拟的白噪声量测模型。为使过程噪声和量测噪声不相关,对过程模型进行不相关条件处理。算法按照构造的虚拟过程模型和量测模型进行滤波估计和地图构建。仿真结果验证了算法的一致性和鲁棒性。     

面向仿真训练系统的过程模型研究

该文首先说明了过程模型的功能，根据功能需求对相关过程建模方法进行分析，找出了适合于仿真系统中过程模型的描述方法，并重点给出了一种基于有限状态机方法的训练过程模型框架、过程模型实时调度方法和应用实例。该过程模型框架由演示过程、物理行为过程、混合过程、过程转移、转移条件等对象类组成，在仿真训练系统开发中，通过定义和扩展这些对象类，对基于有限状态机的过程模型进行控制与调度，准确而全面地描述和管理仿真训练过程，从而有效地解决了仿真训练系统中的过程模型开发问题。     

一种基于模型融合的CMM实施过程建模方法

提出了一种基于模型融合的CMM实施过程建模方法．该方法使用软件过程工程元模型SPEM建立CMM过程模型CPM和企业过程模型EPM，通过融合CPM和EPM来获得CMM实施过程模型CIPM．文中利用带标记的有向图描述过程模型。给出了模型融合方法，并进行了一致性证明．最后通过一个过程模型融合原型工具和实例说明了方法的应用情况．     

一种支持柔性的工作流过程元模型

工作流管理系统的动态自适应能力在很大程度上取决于过程模型的动态支持能力。本文分析和讨论了过程模型的动态特性和工作流管理联盟WfMC定义的过程元模型。在此基础上,引入柔性工作流定义、同步器、变换器等新元素,改进和扩展过程定义元模型。改进和扩展后的过程元模型具有更大的柔性和重构性。由于引入了变换器,为增强过程元模型的智能性做了基础性工作。另外,对描述过程元模型的定义语言WPDL也做了改进和扩展。     

过程实例跃迁正确性判定准则研究

过程模型的动态更改会引起运行中的过程实例向更改后的过程模型跃迁,必须保证过程实例跃迁后运行的一致性。由于多分支结构的影响,不同过程实例的跃迁条件不易确定。研究了过程模型更改机制,通过删除、插入、修改三类元更改操作构造更改域。将过程执行历史能否重放作为过程实例跃迁正确性的判定准则,提出一种高效的过程实例精确跃迁条件评判方法,可以确定拥有不同路由结构、不同运行状态的过程实例的跃迁策略。该方法能适应多分支的过程模型,灵活性高,便于实现过程模型动态更改和实例跃迁的自动化。     

基于完全有限前缀展开的行为等价过程树生成算法

过程树能够兼具过程模型的行为和结构，对简化模型结构的复杂度方面具有重要意义.现有过程树转化仅能将基于块结构的简单过程模型转化为过程树，但是无法将具有复杂结构的过程模型转化过程树.为此，提出了一种基于完全有限前缀展开的行为等价过程树生成算法，用于将与过程树行为等价的过程模型转化为行为等价过程树.该方法首先利用完全有限前缀展开技术分析过程模型，抽取模型的活动关系;其次通过分析活动关系，进而对模型进行重构.最终通过活动关系判断和模型重构的不断迭代操作，构建行为等价过程树.在实验部分通过在测试模型上的实验，验证了该算法在行为等价过程树生成方面的正确性和可行性.     

一种模型驱动的工作流过程定义途径

传统的工作流管理系统在互操作性，可复用性，可移植性和开发效率等方面遇到了挑战，MDA是解决上述挑战和问题的一种途径。在模型驱动的工作流管理系统中，工作流模型处于核心地位，本文首先给出了扩展的工作流元模型和基于Petri网的形式化工作流模型过程网。其次，运用模型驱动的途径，依据给出的工作流模型，本文提出了一种模型驱动的，用于快速构造工作流管理系统的框架。针对工作流过程模型，着重讨论了从基于EPC的过程CIM到基于过程网的过程PIM的转换（转换过程和转换规则），并以扩展的Petri网标注语言E-PNML规约了过程PIM。     

一种弹性的软件过程模型验证工具

过程模型验证是保证软件过程定义正确性的重要手段.针对目前过程模型验证中的一些问题,首先提出了一种以活动为中心的软件过程元模型,并以XML对其进行描述.在此基础上,从行为、资源、组织视图结合的角度,提出了保证软件过程模型正确性的语义约束规则.最后,提出了一种弹性的用于验证XML描述的过程模型的机制,并基于此实现了过程模型验证工具,来验证过程模型的正确性.     

Detection of model-plant mismatch in closed-loop control system

The performance of model-based control systems depends a lot on the process model quality, hence the process model-plant mismatch is an important factor degrading the control performance. In this paper, a new methodology based on a process model evaluation index is proposed for detecting process model mismatch in closed-loop control systems. The proposed index is the ratio between the variance of the disturbance innovation and that of the model quality variable. The disturbance innovations are estimated from the routine operation data by an orthogonal projection method. The model quality variable can be obtained using the closed-loop data and the disturbance model estimated by adaptive Least absolute shrinkage and selection operator (Lasso) method. When the order of the disturbance model is less than 2 or the process time delay is large enough, no external perturbations are required. Besides, the proposed index is independent of the controller tuning and insensitive to the changes in disturbance model, which indicates that the proposed method can isolate the process model-plant mismatch from other factors affecting the overall control performance. Three systems with proportional integral (PI) controller, linear quadratic (LQ) controller and unconstrained model predictive control (MPC) respectively are presented as examples to verify the effectiveness of the proposed technique. Besides, Tennessee Eastman process shows the proposed method is able to detect process model mismatch of nonlinear systems.     

支持虚拟企业的过程建模和工作流管理系统

针对虚拟企业提出了一种基于产品开发制造全过程分解和活动描述的形式化过程建模方法,在组成过程的任务中存在许多约束关系,如使能约束和促进约束,每个任务可以分解成许多活动,可以用企业本体论来表示这些活动、任务、状态和约束等,企业本体论是以情景演算来表示语义的,同时,建立了与过程模型相分离的组织模型活动、任务、状态和约束等,企业本体论是以情景演算来表示语义的。同时,建立了与过程模型相分离的组织模型;在此基础上,建立了一个工作流管理系统来支持虚拟的运行。文中提出一种由活动模型、意向模型、技能模型和伙伴模型等构成的Agent模型,来实现工作流管理,并通过构建可嵌套的Agent联帮增强系统的柔性。     

A practical data-flow verification scheme for business processes

Data in business processes becomes more and more important. Current standard languages for process modeling like BPMN 2.0 which include the data flow reflect this. Ensuring the correctness of the data flow in processes is challenging. Model checking, i.e., verifying properties of process models, is a well-known technique to this end. An important part of model checking is the construction of the state space of the model. However, state-space explosion typically is in the way of an effective verification. We study how to overcome this problem in our context by means of reduction. More specifically, we propose a reduction on the level of the process model. To our knowledge, this is new for the data-flow analysis of processes. The core of our approach are so-called regions of the process model that are relevant for the verification of properties describing the data flow. Non-relevant regions are candidates for reduction of the process model, yielding a smaller state space. Our evaluation shows that our approach works well on industrial process models.     

过程感知信息系统中过程的动态演化

支持过程模型的动态修改并将过程模型的修改传播到当前正在运行的过程实例上,是柔性过程感知信息系统的基本要求.过程实例迁移是应对过程感知信息系统中过程动态演化的主流技术途径,它将尚未执行结束的过程实例动态地迁移到修改后的过程模型上继续执行,从而使得这些过程实例可以享受到过程优化带来的便利.过程实例迁移的挑战在于保证过程实例迁移的正确性以及过程实例迁移检验的高效性,以此为切入点,综述了过程感知信息系统中过程动态演化技术的研究进展.最后,展望了过程演化技术未来应当关注的研究方向.     

Grey box modelling for model predictive control of a heating process

This paper presents a rational modelling procedure of a pilot heating process by using the grey box modelling method. A simplified nonlinear continuous model, based on the conservation of energy, is formed and unknown parameters of the model are estimated by using measured data from an experiment with the process. The model is expanded with a wider model structure by testing formulated hypothesis about the process. The model is also expanded in an engineering way by considering the shape of the residuals. During the model expansion the Likelihood ratio test is applied for falsification tests. The study uses the continuous model for both estimating the states of the process and controlling the system. A continuous-discrete extended Kalman filter estimates the model states and time varying disturbances. The model predictive controller is based on the continuous process model, but the optimisation of the control performance index is made at discrete sampling instances. The control law compensates for changing temperature references and compensate for varying load situations. Besides using the model for control purposes the case demonstrate the possibility of using the grey box modelling technique to estimate physical process parameters such as the thermal diffusivity of the process.     

大规模定制下产品配置设计过程管理研究

产品配置是利用客户需求对配置模型进行实例化的过程．在这个过程中,需要对那些不能直接从已有零部件库中选配到的零部件进行新的设计．在研究产品配置设计工作流程和管理内容的基础上,针对需要设计的实例单元提出了一个产品配置设计过程模型,给出了配置设计过程中设计活动分解的三种结构、三个层次和两个模板,实现了配置中的实例单元数据和设计活动的集成．最后给出了模型在电梯产品配置设计过程中的实际应用．     

PS转炉造渣过程的动态优化控制

建立了Pierce-Smith(PS)转炉造渣过程的非线性状态空问模型,并提出了基于生产质量指标反馈校正的铜锍造渣过程的动态优化控制方案.该方案首先基于最优模型求得最优控制律.为消除吹炼过程中的扰动以及其他不确定因素所带来的影响,再引入基于生产质量指标的反馈调整机制.其中反馈信息由软测量模犁根据进出转炉的物料计算得到,智能控制单元根据反馈的质量信息和期望的质量目标间的偏差对最优控制律进行补偿修正.并在该动态优化控制方案基础上,设计并开发了铜锍吹炼过程的优化控制指导决策系统.实际运行结果表明该系统优化了产品的质量,同时也实现了铜锍生产过程的节能.     

工作流系统中的业务过程描述及分析

过程模型是业务过程的形式化定义,它的正确性直接影响业务目标的实现。定义了一种过程描述语言并对使用这种语言描述的过程模型进行分析,之后给出了工作流执行的控制算法。     

基于随机系数回归模型的退化过程及维修策略

随机系数回归模型是一种描述设备退化过程的重要模型.在基本随机回归系数模型的基础上,运用加速失效时间模型,加入协变量的影响,对设备的退化过程进行建模分析.针对退化过程设置两类更新阈值,一类是预防性维修更新阈值,一类是故障更新阈值.当设备的运行状态被监测到达到或超过预防性更新阈值时,设备将被预防性维修更新,一个预防性更新周期完成;当设备的运行状态被监测到达到故障阈值时,设备将被故障更新,一个故障更新周期完成.运用更新回报定理,对两类更新周期内的单位时间期望维修费用建立模型,对模型求解可得设备的最优监测区间和最优预防性维修阈值.为进一步对所建立的模型进行验证,设计仿真过程求解最优值,并运用数值案例对所建立的模型和仿真过程进行计算.