A study for optional inspection policies in a flexible manufacturing cell

The objective of the paper is to determine the location of inspection stages in order to minimize the expected total manufacturing cost while satisfying the high-quality product demand of customers in a flexible manufacturing cell (FMC). This allows a designer to examine alternative designs in order to select those which are optimal, or near optimal, in manufacturing cost terms. To accomplish this objective, we have formulated a total manufacturing decision model consisting of machine set-up and processing costs. Inspection set-up and inspection costs, and cost due to defective. A case study and sensitivity analysis are presented to demonstrate the application of the decision model developed.     

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Arena的仿真优化系统架构设计

利用Arena软件建立了航空兵场站飞行保障过程模型。针对Arena的第三方优化软件OptQuest不能对用户设置的属性进行优化并且不能处理多目标优化问题的局限,以及利用Visual Basic程序从外部分别获取Arena模型和优化算法的仿真优化架构的运行效率低等问题,设计了1种新颖的仿真优化系统架构。该架构是利用Arena内嵌的VBA技术和VBA block模块联合编程实现了以下功能：控制仿真模型、集成优化算法以及向仿真模型重新输人参数3个功能。仿真优化结果表明,这种通过内部调用仿真模型的仿真优化架构是成功有效的。     

Berth allocation planning in Seville inland port by simulation and optimisation

We study the problems associated with allocating berths for containerships in the port of Seville. It is the only inland port in Spain and it is located on the Guadalquivir River. This paper addresses the berth allocation planning problems using simulation and optimisation with Arena software. We propose a mathematical model and develop a heuristic procedure based on genetic algorithm to solve non-linear problems. Allocation planning aims to minimise the total service time for each ship and considers a first-come-first-served allocation strategy. We conduct a large amount of computational experiments which show that the proposed model improves the current berth management strategy.     

考虑同质设备不同加工能力的模块化制造单元资源配置优化

针对传统制造单元易出现在制品的积压、加工效率低下的问题,提出一种模块化制造单元资源配置模型及算法。按照模块化思想进行制造单元划分,为了保证单元内部均衡,工作站内可配置若干个同类设备。考虑到同类设备之间的加工效率不同,建立以总加工成本最小及制造单元内与单元间的均衡为目标的数学模型,应用模拟植物生长算法进行求解。最后通过算例验证了模型与算法的有效性。     

基于Vega的舰载捷联惯导虚拟平台的航迹仿真

运用虚拟现实技术(Virtual Reality;VR)对捷联惯导系统(Strapdown Inertial Navigation System,SINS)进行模拟的方案,可以有效地提高研发效率,节约研发成本;现在利用Multigen Vega交互仿真环境与VC++6.0开发环境,建立虚拟方针环境;随之针对建立的舰载惯性导航系统航迹仿真的数学模型,分别利用毕卡逼近算法、双子样算法和三子样算法,进行导航解算;最后由真值和所得解算值,实时同步绘制了原始轨迹和解算轨迹,实现了在模拟平台下的航迹仿真;两组轨迹的结果显示的误差,能直观显示出算法的计算误差大小;如此,使得惯性系统的仿真数据可以更加直观的表现出来。     

An improved algorithm for layout design in cellular manufacturing systems

Layout has a significant role on the efficiency of manufacturing systems, but it has not received attention of researchers in comparison to cell formation in cellular manufacturing systems. In this paper, a mathematical model for facility layout in a cellular manufacturing system is proposed that minimizes both inter-cell and intra-cell material handling costs. A variant of simulated annealing algorithm is developed to solve the model. The developed algorithm produces solutions with better quality and less computation time in comparison with the benchmarked algorithm. The superiority of the algorithm in computation time is considerable especially when the size of the problem increases.     

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...     

Artificial neural networks for job shop simulation

This paper explores the use of artificial neural networks (ANNs) as a valid alternative to the traditional job-shop simulation approach. Feed forward, multi-layered neural network metamodels were trained through the back-error-propagation (BEP) learning algorithm to provide a versatile job-shop scheduling analysis framework. The constructed neural network architectures were capable of satisfactorily estimating the manufacturing lead times (MLT) for orders simultaneously processed in a four-machine job shop. The MLTs produced by the developed ANN models turned out to be as valid as the data generated from three well-known simulation packages, i.e. Arena, SIMAN, and ProModel. The ANN outputs proved not to be substantially different from the results provided by other valid models such as SIMAN and ProModel when compared against the adopted baseline, Arena. The ANN-based simulations were able to fairly capture the underlying relationship between jobs' machine sequences and their resulting average flowtimes, which proves that ANNs are a viable tool for stochastic simulation metamodeling.     

知识化制造系统的任务分配决策

为解决知识化制造系统(KMS)的任务分配问题,给出一种基于Agent的KMS体系结构,提出一种特征控制的概念和一种基于Tabu搜索的优化算法,在建立的数学模型基础上,对特征控制的动态过程进行描述,并给出算法的详尽步骤,该算法和特征控制的结合使任务分配决策系统能够动态地响应任务和Agent的变化,最后的仿真实例验证了该方法的有效性。     

Interbay物料自动搬运系统性能分析

Interbay物料自动搬运系统的运行效率对于晶圆制造系统影响较大,研究Interbay物料自动搬运系统的绩效具有较大的意义[1]。该文以带有捷径的单闭环背脊式布局的物料自动搬运系统为研究对象,通过问题描述,简化、假设将实际问题抽象为导引运输模型。然后,建立数学模型,采用Dijkstra算法确定工件搬运的最短路径。最后,利用Arena仿真软件建立含有导引运输设备的模型,采用控制变量法探究小车数量小车占用轨道的方式、调度规则等因素对于产出的影响,发现对于本文中的模型,其它条件相同时,搬运系统采用Release-at-end的控制方式,系统最大搬运量越大。     

Developing cost-optimization production control model via simulation

This research is a further development of our recent papers 2, 3. A production system produces a given target amount by a given due date and has several possible speeds which are subject to random disturbances. The system's output can be measured only at present inspection (control) points. The average manufacturing costs per time unit for each production speed and the average cost of performing a single inspection at the control point to observe the actual output at that point, are given. The least permissible probability of meeting the target on time, i.e. the system's chance constraint, is pre-given too. The problem is to determine both, control points and speeds to be introduced at those points, in order to minimize the system's expenses within the planning horizon. A stochastic optimization problem is formulated, followed by a heuristic solution via simulation. A numerical example is given. Extensive experimentation has been undertaken to illustrate the efficiency of the presented algorithm. The algorithm has been used in practice on a real man–machine plant.     

Simulation-based methodology for machine cell design

This paper presents a simulation-based methodology which uses both design and manufacturing attributes to form manufacturing cells. The methodology is implemented in three phases. In phase I, parts are grouped into part families based on their design and manufacturing dissimilarities. In phase II, machines are grouped into manufacturing cells based on relevant operational costs and various cells are assigned part families using an optimization technique. Phases I and II are based on integer and mixed-integer mathematical models. Finally, in phase III, a simulation model of the proposed system is built and verified, and the model is run so that data on the proposed system may be gathered and evaluated. The mathematical and simulation models are used to solve a sample production problem. The results from these models are compared, and can be used to justify the final design. By the use of these modeling tools, cellular manufacturing systems can be designed, analyzed, optimized, and finally justified.     

团购模式下云制造服务资源组合优化模型与算法

在云制造服务环境中,为了进一步降低需求者的服务成本,提出了一种团购模式下云制造服务资源组合优化模型与算法。在云制造平台发展的初期阶段,以服务需求者的视角分析云制造服务资源组合优化管理问题,通过团购模式研究了资源组合优化模型与算法,模型中考虑团购定价、团购信任度等关键影响因素,对云制造资源组合优化进行综合决策;设计改进的遗传算法进行模型求解,进一步对团购模式下云制造服务资源组合模型进行仿真分析。通过不同规模问题的仿真实验验证了模型与算法的有效性和可行性,仿真结果表明,在团购规模逐渐增大的情况下,团购模式比个体模式更具有成本优势。     

Proposal for a flexible discrete event simulation model for assessing the daily operation decisions in a Ro–Ro terminal

Roll-on/roll-off (Ro–Ro) terminals are important logistic hubs dedicated to vessels and transporters and their loading, unloading and temporary storage. This study aims at assessing the impact of managers’ decisions on planning and operational efficiency with a particular focus on vehicle handling. To this end, the terminal operations are described, the operation decisions are analyzed and the costs involved in terminal processes are formalized. The high complexity of the managerial problem, mostly caused by the stochastic nature of the related variables, is resolved with a discrete event simulation model (developed in Arena Rockwell). It supports day-by-day terminal managers’ decisions, enabling the evaluation of the economic impact of different operational alternatives on logistic costs and pollutant emissions. The verification and validation of the model were carried out in a real environment. Finally, an illustrative example of the tool usage is presented in a case study.     

Application of ant colony optimization algorithm in process planning optimization

One objective of process planning optimization is to cut down the total cost for machining process, and the ant colony optimization (ACO) algorithm is used for the optimization in this paper. Firstly, the process planning problem, considering the selection of machining resources, operations sequence optimization and the manufacturing constraints, is mapped to a weighted graph and is converted to a constraint-based traveling salesman problem. The operation sets for each manufacturing features are mapped to city groups, the costs for machining processes (including machine cost and tool cost) are converted to the weights of the cities; the costs for preparing processes (including machine changing, tool changing and set-up changing) are converted to the ‘distance’ between cities. Then, the mathematical model for process planning problem is constructed by considering the machining constraints and goal of optimization. The ACO algorithm has been employed to solve the proposed mathematical model. In order to ensure the feasibility of the process plans, the Constraint Matrix and State Matrix are used in this algorithm to show the state of the operations and the searching range of the candidate operations. Two prismatic parts are used to compare the ACO algorithm with tabu search, simulated annealing and genetic algorithm. The computing results show that the ACO algorithm performs well in process planning optimization than other three algorithms.     

基于遗传算法的网格制造资源优化选择

制造资源的选择和优化是制造网格应用过程中的关键问题.本文通过对已有制造资源搜索方法进行分析,指出其存在的局限性;在对资源选择问题进行数学描述的基础上,提出了一个基于遗传算法的制造资源组合优化模型,并对该模型的算法进行了设计;最后,给出了一个典型算例,以说明该模型和算法的有效性.     

基于Arena的港口泊位三维仿真系统的实现

本文在三维仿真软件Arena3DPlayer平台上实现了港口泊位作业系统的三维动画仿真。首先分析了港口泊位作业系统并利用Arena对该系统进行了二维仿真模拟,然后给出该系统在Arena3DPlayer平台上三维仿真动画的实现过程,最后总结了其中的关键技术。     

An online robot trajectory planning and programming support system for industrial use

The manufacturing industry today is still looking for enhancement of their production. Programming of articulated production robots is a major area for improvement. Today, offline simulation modified by manual programming is widely used to reduce production downtimes but requires financial investments in terms of additional personnel and equipment costs. The requirements have been evaluated considering modern manufacturing aspects and a new online robot trajectory planning and programming support system is presented for industrial use. The proposed methodology is executed solely online, rendering offline simulation obsolete and thereby reduces costs. To enable this system, a new cell-based Voronoi generation algorithm, together with a trajectory planner, is introduced. The robot trajectories so achieved are comparable to manually programmed robot programs. The results for a Mitsubishi RV-2AJ five axis industrial robot are presented.     

改进的SAGA算法在变电站巡检作业调度中的应用

针对多资源约束条件下变电站巡检作业调度问题,根据巡检成员的位置、当前任务、任务详情、待执行任务、巡检设备、设备历史巡检记录等因素,构建数学模型,并在此模型基础上提出一种改进的遗传算法。该算法解决了传统遗传算法陷入局部最优解的问题,且具有收敛速度快的特点。实验结果表明,SAGA算法在解决变电站巡检作业调度问题方面要优于GA算法,且具有更高的求解效率。 