Concurrent modeling language (CML) for discrete process modeling,simulation and control

Modern manufacturing systems can be viewed as distributed concurrent discrete processes, using extensive communication internally and with the environment. The concurrency and reactive nature of the system make it difficult to model and analyze correctly. This paper presents a genuine high level and concurrent modeling language, CML, that can be used for modeling and control of manufacturing processes. In addition, it can be used for simulation and analysis of the system's operation. The CML language is based on flat concurrent prolog which is a declarative concurrent logic programming language, therefore, highly expressive, and theoretically sound.     

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。     

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.     

A simulation study of logistics activities in a chemical plant

This article describes an application of discrete-event simulation to study logistics activities in a chemical plant. Most chemical production involves continuous flow of materials, such as liquid, gas or solid through the manufacturing and logistics processes. Some simulation issues in this area are conceptualizing production operations for simulation, discretization of continuous processes and building adequate level of detail in the models. The purpose of this study is to determine the required capacity of logistics operations to allow continuous operations of a chemical manufacturing plant. The application has been used to provide critical decision support. The value of the simulation study is not only the simulation model itself but also the process of building it.     

基于混杂系统理论的制造系统仿真

根据制造系统连续事件与离散事件并存的特点,提出一种制造系统半实物仿真方法,设计连续事件和离散事件并存时仿真系统的时间推进机制。在Arena环境中实现对离散事件系统的建模,在Labview环境中实现特定连续变量事件的半实物仿真。设计并实现离散事件系统与连续事件的接口连接。仿真实验结果表明,该系统能较好地反映出整个制造系统的混杂特性,为混杂制造系统的仿真提供一种新的思路。     

基于仿真的生产计划与调度系统集成

针对航天制造企业和产品生产特点,描述了一个生产计划、仿真和调度集成系统.分析了该类型企业在生产管理上存在的主要问题,描述了集成系统的框架及主要组件的功能,以及集成系统的运行机制.该系统利用仿真技术将企业的生产计划与作业调度紧密集成,实现了计划部门与生产部门在信息和流程上的紧密关联.最后通过实例验证了该集成系统的可行性与有效性.     

A software system for the simulation of robot based manufacturing processes

A simulation system is described which supports programming of robot based manufacturing processes. A cad system is used for geometric modelling. The system allows modelling of different object classes like robots, end-effectors, sensors, workpieces as well as the robot's environment. Control functions on different control hierarchies in the manufacturing system can be emulated. The emulation of the virtual robots is displayed graphically. Analysis and evaluation methods are applied to detect errors and conflicts in the simulated manufacturing process with the purpose of optimizing the program.     

An admissible-behaviour-based analysis of the deadlock in Petri-net controllers

This paper addresses the problem of verifying the discrete control logic that is typically implemented by programmable controllers. Not only are the logical properties of the controller studied during verification, the behaviour of the overall controlled system is also examined. An approach that combines the calculation of the safety-oriented interlock controllers in terms of supervisory control theory (SCT), the corresponding calculation of the admissible behaviour of the system, and the specification of the desired system operation by Petri nets is proposed. A potential deadlock in the controlled system is then verified by taking the admissible-behaviour model as a process model. The analysis of the simultaneously operated supervisory-control-based interlock controller and the Petri-net-based sequential controller is performed with a C-reachability graph. The paper focuses on the calculation of the graph, and the approach is illustrated with an example of a simple manufacturing cell.     

一类Petri网及其在离散事件系统的仿真与控制中的应用

设计和实现了一类Petri网--控制Petri网,基于控制Petri网,给出了离散事件系统的仿真与控制的算法和离散事件系统控制的实现方案,最后以柔性机床为例,演示了基于控制Petri网的离散事件系统的仿真与控制过程.结果表明,使用控制Petri网可以有效地模拟和控制离散事件系统.     

Focusing qualitative simulation using temporal logic: theoretical foundations

We illustrate TeQsim, a qualitative simulator for continuous dynamical systems that combines the expressive power of qualitative differential equations with temporal logic to constrain and refine the resulting predicted behaviors. Temporal logic is used to specify constraints that restrict the simulation to a region of the state space and to specify trajectories for input variables. A propositional linear‐time temporal logic is adopted, which is extended to a three valued logic that allows a formula to be conditionally entailed when quantitative information specified in the formula can be applied to a behavior to refine it. We present a formalization of the logic with correctness and completeness results for the adopted model checking algorithm. We show an example of the simulation of a non‐autonomous dynamical system and illustrate possible application tasks, ranging from simulation to monitoring and control of continuous dynamical systems, where TeQsim can be applied. This revised version was published online in June 2006 with corrections to the Cover Date.     

Intelligent Control Paradigm for Dynamic Discrete Event System Simulation

Simulation based control of discrete event systems has been a potential approach to support decision-making in the manufacturing scenario. In this paper, a knowledge intensive simulation modelling approach for a discrete even system is investigated. Based on the proposed simulation model, a robust control mechanism is presented that is believed to add significant value to discrete event dynamic system. The algorithm utilises neural network feedforward control plus robust proportional derivative feedback control to achieve control performance and output stability. The novel simulation approach, as well as the proposed controller, is implemented in an Extend TM environment and the effectiveness and usefulness of the proposed controller are verified, industrially, in the hard disk drive assembly process, a significant component of the Singapore manufacturing economy.     

Integration of neurocomputing and system simulation for modeling continuous improvement systems in manufacturing

The use of a neural network embedded in a larger general-purpose simulation system (GPSS) simulation used to model continuous improvement systems (CIS) policies in a factory setting is described. The neural network is used to accelerate the identification of an effective CIS policy by providing a more realistic simulation framework. The interface between general simulation theory and neural network simulation is examined. Neural networks, when embedded in larger general-purpose simulations, are found to offer the potential for improving on the capabilities of those simulations, in particular manufacturing simulations for continuous improvement of production processes.     

A framework and a simulation generator for kanban-controlled manufacturing systems

A generalized framework for the definition of kanban-controlled manufacturing systems and a simulation generator based on this framework are introduced in this paper. Kanbans are used between and within workstations to trigger product flow or production. The simulation generator is capable of modeling complex manufacturing systems with multiple parts, multiple work centers and multiple processes at each work center. Multiple process definition capability enables users to define convergent and divergent points in a manufacturing system. Several decision rules are defined and incorporated into the generator. The simulation generator can be used as a completely interactive tool that is data-driven and requires no programming skills.     

Knowledge based system for scheduling and control of an automated manufacturing cell

Cell Manager (Cm) is a prototype knowledge based system for real-time control and short-term planning of an automated manufacturing facility. It uses background of mathematical programming, simulation, and heuristic search. The Cm engine allows tracking of time related events and facts in discrete or continuous time. The use of Cm is illustrated on a cell that processes discrete batches of parts. There are four workstations and the material handling system consists of automated guided vehicles.     

The use of a generic simulation model in evaluating manufacturing processes

In recent years the application of simulation models to analyze the production capabilities of manufacturing processes has been increasing at IBM's Poughkeepsie plant. To avoid major programming effort for each new application, a generic simulation model was developed. The model, written in SIMPL/1 (Simulation Language Based on PL/1), was designed in modules defined on a functional basis. This language was chosen because it allowed full use of the PL/1 programming language, reduced the excessive run times experienced with large, specialized GPSS models, simplified the procedure for making input changes and provided output that could be easily interpreted by the non-programmer. The input data bases are user-oriented so that changes can be made to the system being modeled without programming support. The output generated by the model can provide the user with information on resource utilization, major process bottlenecks, overtime requirements, process throughput and process cycle time. This data is evaluated by the user to determine how well the process functions under given operating conditions so that cost effective decisions can be made. An example is provided on the model's application to a logic and memory card assembly process.     

Dynamic simulation and neural network compliance control of an intelligent forging center

Automation of forging processes is important for both safety and efficiency in today's advanced manufacturing operations. This work supports the development of an Intelligent Open Die Forging System which will integrate state-of-the-art modelling techniques, automatic die selection and sequencing, full system dynamic simulation, automatic machine programming and coordination, and sensor-based process control to enable the production of more general and complex workpiece geometries than are achievable using current forging methods. Effective automation of this open die forging system requires the coordination and control of the major system components: press, robot, and furnace. In particular, forces exerted on the robot through its manipulation of the workpiece during forging must be minimized to avoid damage to the manipulator mechanism. In this paper, the application of neural networks for compliance control of the forging robot to minimize these forces is investigated. Effectiveness of the neural network-based compliance control module is evaluated through a full dynamic system simulation, which will later form a central part of the complete Intelligent Forging System. Dynamic simulation of the robot is achieved using an efficient O(N) recursive algorithm, while material flow of the workpiece is modeled with a finite element approach. Simulation and timing results for the complete processing system for a specific open die forging example are presented.     

仿蟹机器人基于MATLAB与ADAMS单足联合仿真分析

利用ADAMS和MATLAB及其动态仿真集成环境Simulink分别建立机器人机械系统模型和控制系统模型,然后应用ADAMS/Control将ADAMS的机械系统模型与MATLAB的控制系统模型连接起来,在参数自调整模糊控制系统软件环境下进行交互式仿真,仿真完成后对机器人的运动学和动力学特性进行分析,并可进一步评估控制系统的稳定性,从而简化了机器人的理论计算,提高了实际效率。     

数据驱动的汽车总装线建模与仿真技术研究

现代制造业的生产模式向柔性制造和客户化定制方向发展,为了提高制造系统的快速响应能力,实现快速仿真分析,提出基于数据驱动的建模与仿真方法,其具有建模周期短、模型可读性、可重用性较高的特点.利用IDEFIX建模方法建立模型的底层数据结构,基于Arena构建仿真模型生成器,利用已建好的数据模型提供的属性信息,自动生成目标系统...     

Development of a multi-agent-based distributed simulation platform for semiconductor manufacturing

Since the semiconductor manufacturing system is a large-scale complex system, it is difficult to solve complex problems in semiconductor manufacturing by the mathematical modeling method. This paper presents a multi-agent-based distributed simulation platform to support the extremely complex semiconductor manufacturing analysis. A multi-agent-based distributed simulation platform framework and a multi-agent collaborative control model are proposed to provide a flexible infrastructure and a multi-agent coordination mechanism in distributed environment for semiconductor manufacturing simulation. A multi-agent time synchronization model for distributed simulation is designed to keep events in the correct logical time order in simulation and steps of time synchronization are given. An interaction model and message formats are presented to describe how agents communicate with each other in simulation. The platform development and the design of graphical user interface are also exploited in this paper. Finally, evaluation of this multi-agent-based platform was illustrated with a case study. It indicates that the platform is effective in modeling and simulating the complex semiconductor manufacturing and provides the insights about how to improve the semiconductor manufacturing process with well targeted measures.