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针对装配生产线的优化问题,首先阐述生产线仿真基本步骤及ECRS分析和操作分析等两种最常用的优化技术作为全文的理论基础。随后以某装配生产线为研究对象,基于FlexSim仿真软件进行了装配线建模并分析指出瓶颈在于铁框的装夹工序。由此结合作业流程优化和增加工位两个角度,提出了一套针对性的优化方案,最后再次应用FlexSim仿真加以有效性和可行性验证。仿真实验结果表明,该优化方案的实施可大幅提升目标装配线的生产效率,对于类似制造系统或物流系统的建模和优化,也具备良好的借鉴意义。 相似文献
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为解决城市轨道车辆生产线存在的生产效率不高与稳定性差等问题,提出了一种基于有向加权网络的城市轨道车辆工艺路线优化方法。该方法首先利用有向加权网络理论构建车辆生产线的生产网络模型,然后以生产线可靠性与制造成本为目标,建立轨道车辆工艺路线的多目标优化模型,并基于粒子群算法得到最优工艺路线生成算法,最后以某轨道列车生产线为例进行了验证,结果表明,该方法能显著降低生产线的生产成本,提高生产线的生产效率与稳定性。 相似文献
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基于生产线连续和离散并存的混杂特征,提出了混杂系统的建模及其优化控制方法。研究了加工单元的混杂自动机模型(混杂基本结构),面向生产线的混杂系统可看作若干混杂基本结构的合成,有效地避免了系统规模增长给模型造成的组合爆炸问题。在此基础上,对满足一定产量情况下最大化机器利用率的混杂优化控制方法进行了研究,提出了基于蒙特卡洛法的性能优化仿真计算方法。最后,对某有限缓冲容量串行生产线进行了数值仿真计算,仿真结果验证了该研究方法的可行性和有效性。 相似文献
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链段是啤酒生产线设计中需要考虑的重要因素,它直接与影响啤酒生产线性能指标的缓冲容量和缓冲时间参数紧密相关。链段设计本质上是一种组合优化问题,但由于生产线动静特性的影响,不能建立精确的生产线数学分析模型,传统设计方法只能给出留有较大冗余的解。本文研究应用仿真优化方法设计啤酒生产线并开发出基于虚拟仿真环境的制造系统仿真优化系统S imOpt,在实际应用中具有非常好的效果。 相似文献
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基于离散事件仿真技术(DES),对某装配生产线开展了基于仿真的布局设计及优化研究工作,建立该仿真系统的目的是在现有制造模式的基础上,进行不同类型的生产线布局仿真设计试验,提出了一个装配生产线布局解决方案,减少生产线劳动力需求,解决生产瓶颈问题。在分析典型制造零件的制造工艺和生产线现有设备的基础上,提出了直线型布局、U型布局和平行U型布局装配生产线3种布局设计方案。在Witness软件平台上,利用装配生产线数据及经验数据,构建了基于DES的仿真系统。随后,在仿真系统中对这3种布局方式均进行了测试,通过结果对比对3种布局方案在生产线节拍平衡、制造成本和生产效率方面的仿真结果进行分析。结果表明,平行U型布局装配生产线方案是该装配生产线最佳的布局模式。 相似文献
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针对STEP-NC制造特征的加工工艺路线生成与优化问题,提出了一种以机床、夹具及刀具更换率最低为目标函数的禁忌制造特征动态更新的工艺路线蚁群优化方法。首先,根据加工工艺对制造特征进行分解,将工艺路线优化问题转化为对制造特征的排序;然后根据制造特征在加工过程中存在的加工遮挡关系以及刚性工艺性约束,提出禁忌制造特征动态更新的工艺路线生成方法;最后将禁忌制造特征动态更新方法与Ant-Cycle模型的蚁群算法相结合,求解制造特征工艺路线的优化问题。实例应用表明,提出的方法能较好解决加工工艺路线优化过程中的刚性约束处理问题。 相似文献
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Frontiers of Mechanical Engineering - The scheduling of parallel machines and the optimization of multi-line systems are two hotspots in the field of complex manufacturing systems. When the two... 相似文献
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Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufac~ring center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method. 相似文献
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GAO Shiwen LIAO Wenhe GUO Yu LIU Jinshan SU Yan 《机械工程学报(英文版)》2009,22(2):177-183
Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making. 相似文献
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For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem. 相似文献
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面向制造的连续体结构拓扑优化设计方法研究 总被引:2,自引:0,他引:2
为了更好地解决结构拓扑优化的工程实用化问题,研究了一种面向制造的连续体结构拓扑优化设计的方法,即面向制造的分级拓扑优化方法。该方法可使优化结果同时满足设计性能和制造性能的要求。为消除数值不稳定,研究了密度和敏度混合高斯函数过滤算法,该算法能有效解决棋盘格式及网格依赖等数值不稳定问题,并能获得良好的优化结果。利用研究的分级拓扑优化方法和有关算法,对经典算例进行计算,所得结果验证了该方法的可行性和有效性。 相似文献
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针对多品种、变批量需求的可重构制造问题,综合考虑工艺路线与生产批量约束,以设备负荷均衡、跨单元加工次数最少为目标,提出了两阶段求解的虚拟制造单元构建方法。第一阶段,采用图聚类法对工艺路线的相似性和零件的生产批量进行预处理,生成基于订单的多工艺路线最大支撑树,确定基本可行制造单元集;第二阶段,以设备负荷均衡、跨单元加工次数最少的综合目标函数设计为基础,采用基于类电磁机制寻优原理的求解算法,确定最优制造单元解。某泵阀制造企业生产数据的实例应用验证了算法的可行性与有效性。 相似文献
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程曙 《计算机集成制造系统》2008,14(5):937-943
混杂系统理论及其应用是近年来的研究热点和难点。较为全面系统地阐述了混杂系统在建模、分析、控制和优化等几个方面的理论研究现状,对主要内容及其方法的优点和局限性进行了总结和评价。作为混杂系统的一个重要代表,分析与综述了制造系统中的主要应用成果,指出了具体应用中的难点问题。最后展望了进一步的研究内容。 相似文献
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针对云制造环境下加工任务执行过程中机床装备资源易受紧急插单、加工质量异常、设备运行故障等高频随机扰动影响,致使产品加工服务质量(QoS)不能满足客户个性化需求的问题,提出一种基于离散Markov跳变系统的机床装备资源动态优化选择方法.首先,结合云制造服务运行特点,构建了云制造环境下面向加工任务执行过程的服务质量动态演化... 相似文献