基于元模型的组件化制造过程建模仿真系统研究

文章分析了基于功能和基于过程的两种制造系统建模仿真方法,提出了面向过程的建模仿真系统的元模型结构,详细设计了制造系统多个视图模型中的主要建模元素。在此基础上,采用面向对象分析和软件组件技术,实现了组件化制造过程建模仿真系统中的各个组成模块。该软件应用于实际,与CIMS其它子系统集成运行,提高了制造企业的整体业务水平。     

基于SysML的船厂堆场作业系统建模与仿真*

研究了基于系统建模语言SysML的船厂堆场作业系统建模及仿真实现问题。首先基于SysML的系统建模方法建立了堆场作业系统的系统需求、结构及行为模型;然后利用仿真系统ARENA解决SysML模型的实现问题,并设计了从SysML模型到ARENA模型的转换方法。实例验证结果表明,SysML在系统建模方面具有良好的表达性,利用ARENA对SysML模型进行仿真实现是可行的。     

离散制造系统规划与仿真建模研究

对离散制造过程的规划、建模和仿真技术进行了研究，建立了面向对象的系统模型，分析了仿真运行机理，通过仿真分析优化生产制造系统性能指标。应用实例，介绍了基于eM—Plant环境进行生产线建模仿真、设备布局、瓶颈分析的过程，为离散制造过程研究提供了有效的方法。     

基于信息融合思想的水电仿真建模方法的研究

针对水电仿真建模中的复杂性、时变性等问题，将信息融合思想引入到水电仿真系统的建模过程中，利用融合系统的传感施动模型的系统化设计方法，提出了一种基于信息融合思想的水电仿真系统建模方法，为仿真系统建模提供了一种新的思路与方法。将该方法应用于丰满水电仿真系统调速系统的建模过程中，经实际应用表明，该模型在性能上优于传统的调速器仿真模型。     

经济系统中的非线性建模与仿真

文章分析了经济学中传统非线性建模方法的不足,提出利用基于多智能体的整体建模仿真方法来建立经济系统的非线性仿真模型,作者利用swarm仿真软件平台生成了一个产品供求关系的非线性仿真模型,研究了供求平衡出现的条件和系统中的非线性现象,证明了这种方法的可行性和优越性。     

CIMS仿真建模方法

仿真建模问题对于计算机集成制造系统（CIMS）的研究和应用是十分重要的，建立模型的方法直接影响到系统仿真软件的开发和实现。针对一般计算机集成制造系统（CIMS）中仿真建模所存在的覆盖面小和灵活性差的问题，陔文通过对一般CIMS的功能层次分析，采用分别处理的方法，提出了在CIMS应用系统中经营管理、生产制造和设备控制三个层次的仿真建模模型和建模方法。为CIMS各层次的仿真软件的开发提供依据。     

轴流压气机旋转失速建模与检测:基于确定学习理论与高阶Moore-Greitzer模型的研究

喘振和旋转失速是轴流压气机研究领域中重要而困难的问题. 本文基于确定学习理论及动态模式识别方法提出一个旋转失速初始扰动 近似准确建模和快速检测的方法. 首先,基于高阶Moore-Greitzer模型（Mansoux模型）,利用确定学习理论提出一个对旋转失速初始扰动的内在系统动态的近似准确建模方法;其次,基于以上近似准确建模,利用 动态模式识别方法提出一个对旋转失速初始扰动的快速检测方法. 基于MIT的Mansoux-C2模型仿真研究验证了 所提方法的有效性. 最后,在北京航空航天大学航空发动机重点实验室的低速轴流压气机试验台上开展了试验研究. 通过对低速轴流压气机试验台参数进行测量,得到基于北航低速轴流压气机试验台的Mansoux模型. 通过对基于北航试验台Mansoux模型进行仿真研究,验证了所提方法的有效性.     

基于Repast Simphony平台的建模与仿真技术

随着计算机技术的发展, 基于Agent的建模与仿真技术被认为是研究复杂系统的有效方法, Repast Simphony平台为基于Agent的建模与仿真提供了有利条件. 针对如何利用Repast Simphony平台构建复杂系统仿真模型的问题, 重点介绍了Repast Simphony仿真平台, 分析了它的技术优势, 与同类仿真平台进行了比较分析, 并在分析平台主要类库的基础上, 总结出建模仿真的一般流程. 最后, 通过一个改进的Schelling模型仿真实例进一步阐述了利用平台构建复杂系统的设计与实现方法, 对使用Repast Simphony平台进行基于Agent的建模与仿真研究具有一定的指导意义.     

基于Agent的城市废物计量收费方案仿真研究

提出一种基于Agent的城市废物计量收费仿真模型.由于城市废物计量收费仿真模型属于复杂适应性系统(CAS),传统的建模仿真方法无法完好地刻画城市废物计量收费仿真模型,而基于多Agent的建模仿真方法(ABS)是当前研究复杂适应性系统的最有利工具之一.有必要进行深入研究.在简单介绍复杂适应性系统、基于多Agent的建模方法的研究概况,以及多Agent建模工具--Repast仿真甲台以及它的结构、主要类库与建模步骤后,以城市废物计茸收费仿真模型为研究对象,进行基于多Agent的建模仿真实验,结果表明基于多Agent的建模仿真方法非常合适复杂适应性系统的研究,具有很大的发展空间.     

Matlab和Web应用相结合及其在eMTM 在线系统中的应用

从满足电子化量身定制(eMTM系统快速实时的3D人体建模的要求入手,提出一种利用Matlab和传统Web应用相结合的方法,并用此方法建立了一个独立于Matlab平台的基于Web／Http的人体三维模型在线构建和仿真系统的模型,最后通过一个试验性应用示例表明了该方法的具体实现过程,试验结果表明了该方法在基于Web的实时快速人体3D模型的仿真方面具有较好的有效性。这些研究结果对于服装行业eMTM的发展具有积极的意义。     

Data driven production modeling and simulation of complex automobile general assembly plant

Flexible manufacturing and customization has long been a topic in modern manufacturing society. However, challenges still remain on the responsiveness of production system to the fluctuation of market demand. In this paper, we developed a data driven simulation methodology to automatically model a production system and rapidly modify the model corresponding to dynamic requirements and real time information. This methodology provides a “rapid prototyping” capability for production system modeling and enables a quick analyzing and remodeling capability to respond to the fluctuation of demands. The approach is developed and applied to an automotive general assembly plant with an online material handling system. A complete information model based on IDEF1X is constructed for this domain specific modeling and simulation. The main simulation modules for assembly line and material handling system of the plant floor are analyzed and a simulator is implemented in ARENA by SIMAN/VBA program. The case study of an automotive assembly plant shows that the data driven approach enables the modeling and simulation of the complex assembly plant in a “real-time” fashion and therefore effectively improve the responsiveness and flexibility of the production line.     

A data-driven generic simulation model for logistics-embedded assembly manufacturing lines

Simulation has been used to evaluate various aspects of manufacturing systems. However, building a simulation model of a manufacturing system is time-consuming and error-prone because of the complexity of the systems. This paper introduces a generic simulation modeling framework to reduce the simulation model build time. The framework consists of layout modeling software and a data-driven generic simulation model. The generic simulation model was developed considering the processing as well as the logistics aspects of assembly manufacturing systems. The framework can be used to quickly develop an integrated simulation model of the production schedule, operation processes and logistics of a system. The framework was validated by developing simulation models of cellular and conveyor manufacturing systems.     

A lab-scale manufacturing system environment to investigate data-driven production control approaches

Controlling production and release of material into a manufacturing system effectively can lower work-in-progress inventory and cycle time while ensuring the desired throughput. With the extensive data collected from manufacturing systems, developing an effective real-time control policy helps achieving this goal. Validating new control methods using the real manufacturing systems may not be possible before implementation. Similarly, using simulation models can result in overlooking critical aspects of the performance of a new control method. In order to overcome these shortcomings, using a lab-scale physical model of a given manufacturing system can be beneficial. We discuss the construction and the usage of a lab-scale physical model to investigate the implementation of a data-driven production control policy in a production/inventory system. As a data-driven production control policy, the marking-dependent threshold policy is used. This policy leverages the partial information gathered from the demand and production processes by using joint simulation and optimization to determine the optimal thresholds. We illustrate the construction of the lab-scale model by using LEGO Technic parts and controlling the model with the marking-dependent policy with the data collected from the system. By collecting data directly from the lab-scale production/inventory system, we show how and why the analytical modeling of the system can be erroneous in predicting the dynamics of the system and how it can be improved. These errors affect optimization of the system using these models adversely. In comparison, the data-driven method presented in this study is considerably less prone to be affected by the differences between the physical system and its analytical representation. These experiments show that using a lab-scale manufacturing system environment is very useful to investigate different data-driven control policies before their implementation and the marking-dependent threshold policy is an effective data-driven policy to optimize material flow in manufacturing systems.     

Development of real-time sketch-based on-the-spot process modeling and analysis system

Contemporary manufacturing processes require faster real-time controls against dynamic and volatile production environments. While a corresponding simulation model is considered a prerequisite system for the real-time control of a contemporary manufacturing process, simulation modeling and relevant analysis have supported these real-time features comparatively less. These issues might cause procrastination of the simulation modeling, and result in wrong decisions and inaccurate controls. In order to overcome these issues, a new real-time simulation modeling and analysis system is proposed. The proposed system supports sketch-based simulation modeling. The simulation model is constructed using modelers’ sketches of predefined simulation symbols. The sketches are converted automatically into a corresponding stochastic queueing network using Self-organizing Map, a type of neural network. Then, the model is simulated and analyzed using the embedded stochastic queueing analyses. The effectiveness of the proposed system is proven with the modeling, simulation and analyses of several real-time manufacturing cases.     

时空轨迹数据驱动的自动驾驶场景元建模方法

时空轨迹数据驱动的汽车自动驾驶场景建模,是当前汽车自动驾驶领域中驾驶场景建模、仿真所面临的关键问题,对于提高系统的安全性具有重要研究意义.近年来,随着时空轨迹数据建模及应用研究的快速发展,时空轨迹数据应用于特定领域建模的研究引起人们的广泛关注.但由于时空轨迹数据所反映现实世界的多元性和复杂性以及时空轨迹数据的海量、异构、动态等特点,基于时空轨迹数据驱动的安全攸关场景建模的研究仍面临着挑战,包括：统一的时空轨迹数据元模型、基于时空轨迹数据的元建模方法、基于数据分析技术的时空轨迹数据处理、数据质量评价等.针对汽车自动驾驶领域的场景建模需求,我们提出一种基于MOF元建模体系构建时空轨迹数据的元建模方法,根据时空轨迹数据的特征及自动驾驶的领域知识,构建了面向汽车自动驾驶的时空轨迹数据元模型;并基于此,提出基于时空轨迹数据元建模技术体系的自动驾驶安全场景建模方法,并使用场景建模语言ADSML实例化安全场景,构建安全场景库,旨在为此类系统的安全关键场景建模提供一种可行的方案.结合变道超车场景的案例,展示了时空轨迹数据驱动的自动驾驶安全场景元建模方法的可用性,为场景模型的构建、仿真、分析奠定了基础.     

数字化生产线制造过程建模仿真系统研究

文章分析了生产线制造过程的数字化制造环境,提出了基于扩展事件过程链的生产线制造过程建模仿真方法。在此基础上,采用面向对象软件方法,详细设计和实现了生产线制造过程建模仿真系统的各个组成模块。该软件系统应用于实际生产线的规划设计,对生产线进行仿真分析和性能优化,与CIMS其它子系统集成运行,提高了生产线制造过程的整体性能和经济效益。     

Data-driven modeling and simulation framework for material handling systems in coal mines

In coal mining industry, discrete-event simulation has been widely used to support decisions in material handling system (MHS) to achieve premiums on revenues. However, the conventional simulation modeling approach requires extensive expertise of simulation during the modeling phase and lacks flexibility when the MHS structure changes. In this paper, a data-driven modeling and simulation framework is developed for MHS of coal mines to automatically generate a discrete-event simulation model based on current MHS structural and operational data. To this end, a formal information model based on Unified Modeling Language (UML) is first developed to provide MHS structural information for simulation model generation, production information for simulation execution, and output requirement information for defining simulation outputs. Then, Petri net-based model generation procedures are designed and used to automatically generate a simulation model in Arena® based on the simulation inputs conforming to the constructed information model. The proposed framework is demonstrated for one of the largest open-pit coal mines in the USA, and it has been demonstrated that the framework can be used to effectively generate the simulation models that precisely represent MHS of coal mines, and then be used to support various decisions in coal mining such as equipment scheduling.     

Implementing a hybrid simulation model for a Kanban-based material handling system

Plant floor material handling is a loose loop in most assembly plants. Simulation offers a quick, controllable and tunable approach for prototyping complex material handling processes in manufacturing environments. This paper proposes a hybrid simulation approach, using both discrete event and agent-based technologies, to model complex material handling processes in an assembly line. A prototype system is implemented using a commercial multi-paradigm modeling tool. In this prototype, JIT principles are applied to both the production and the material handling processes. The system performance is evaluated and system optimization directions are suggested. The proposed hybrid modeling approach facilitates the implementation of a responsive and adaptive environment in that various “what-if” scenarios can be simulated under different simulation configurations and real-time situations.     

Balancing and simulating of assembly line with overlapped and stopped operation

In order to avoid undesirable idling or fuss of the manufacturing resources, the assembly workshop’s scheduler evaluates the effect of different online sequence of parts on production cycle, balances workload and utilization ratio, minimizes span of the assembly line. This paper studies modeling and simulation of assembly line with overlapped and stopped operation, builds mathematical model for the assembly line both under certainty and uncertainty environment. Assembly line problem with these two conditions is simulated, and a simulation prototype system is developed. The assembly line simulation at assembly workshop in an auto company of Beijing validates the effectiveness and correctness of the prototype system.