汽车装配车间生产计划调度系统的设计与开发

论述了汽车装配车间在企业顺利生产中的重要性,建立了车间生产计划与调度的同时优化模型.基于免疫算法.以概率1收敛的特点,选用免疫算法并将之进行适当组合得到交替式免疫算法来对该模型进行求解,以达到计划和调度同时优化的目的.在进行理论研究的基础上,根据南京某汽车厂的实际需求设计出了生产计划与调度系统方案,并使用组件化技术,开发出了基于.NET平台和B/S模式的汽车装配车间生产计划与调度系统,最终满足实际生产要求,达到了高效信息管理的目标.     

汽车装配车间生产计划与调度的同时优化方法

文中提出三种新方法来解决汽车装配车间生产计划与调度的同时优化问题.首先将汽 车装配线简化为一个Flow shop问题,并建立其混合整数规划模型,以求得使各装配工位的准 备成本和空闲时间尽可能少并尽可能满足产品需求的粗生产计划.然后在粗生产计划的基础上 考虑装配线的细节,用Tabu搜索法与快速调度仿真相结合的三种不同启发式算法使生产计划 与调度同时得到优化,并给出了三种算法的复杂性.大量算例的比较研究表明了这些算法的有 效性和适用性.     

带返工的定点装配车间生产计划与调度集成优化

针对定点装配车间不合格品返工导致生产计划及调度不可行的情况,提出一种基于返工延后处理的定点装配车间生产计划与调度集成优化方法.首先制定返工延后处理的粗生产计划;下达计划生产后,将每周期产生的不合格品放入缓冲区,在下周期初时重新调整生产计划并求解新计划下的最优调度,判断其是否满足装配班组负载率要求,不断交替迭代生产计划与调度直至达到计划与调度的均衡和优化.最后通过算例验证了所提出方法的可行性和有效性.     

炼铸轧集成计划与调度组批模型及算法

为提高热装批量计划的调度可行性,构建一种集成批量计划类型及部分调度约束的批量计划约束满足模型,并采用显性基因的约束遗传算法进行优化求解。在优化过程中,采用一种以提高批量计划的调度可行性的基于邻域连通的快速判定方法,同时利用判定返回的信息构建显性基因指导优化过程。最后利用实际生产数据进行测试,结果表明,所提出的模型和算法能够提高热装率和批量计划调度的可行性,并且算法的执行效率可满足实际应用的要求。     

汽车装配线生产计划与调度的集成优化方法

为提高汽车装配线的生产效率,优化资源配置,研究了汽车装配线生产计划和调度的集成优化问题,给出了该问题的混合整数规划模型.利用分枝定界算法和单纯型法求得问题的粗生产计划.通过将模拟退火算法和快速调度仿真相结合,探讨了一种新的启发式算法.然后基于已求得的粗生产计划,针对三种不同寻优组合论述了该算法的实现.将该算法应用于实际算例,仿真结果表明该算法对求解此类问题有着很好的效果.     

基于遗传分散搜索算法的装配排序优化

航空发动机装配车间调度问题包括部件组装调度和试车台排序。其中试车台排序是一个关键问题,它直接影响生产效率和生产成本。为了提高生产效率、降低生产成本,文中针对航空发动机装配车间调度问题,依据实际情况,对其中关键的试车台排序问题进行深入研究。在分析试车台排序特征的基础上,建立了试车台最优排序的旅行商模型,基于遗传分散搜索算法对该模型进行求解,为装配排序优化问题提供了一种科学的方法。最后通过算例比较表明该算法的适用性和优越性。     

基于遗传分散搜索算法的装配排序优化

航空发动机装配车间调度问题包括部件组装调度和试车台排序。其中试车台排序是一个关键问题,它直接影响生产效率和生产成本。为了提高生产效率、降低生产成本,文中针对航空发动机装配车间调度问题,依据实际情况,对其中关键的试车台排序问题进行深入研究。在分析试车台排序特征的基础上,建立了试车台最优排序的旅行商模型,基于遗传分散搜索算法对该模型进行求解,为装配排序优化问题提供了一种科学的方法。最后通过算例比较表明该算法的适用性和优越性。     

基于粒子群算法的流程工业生产调度研究

以优化流程工业生产为目标,研究了将基于惯性权重的粒子群算法应用到流程工业的生产调度问题。在对流程工业生产调度问题进行分析的基础上,建立了以总加工完成时间最短为优化目标的生产调度模型。调度算法采用动态惯性权重,使惯性权值在粒子群算法搜索过程中线性变化,以提高粒子群算法的优化性能。给出了粒子编码与解码实现方法,以及具体的算法实现过程。以某流程工业企业生产调度实例为例,利用建立的优化调度模型和设计的粒子群算法进行了实验仿真,结果表明,建立的调度模型和设计的算法是可行的,与蚁群系统方法相比较,有较好的调度性能,适用于解决流程工业实际生产调度问题。     

免疫克隆选择算法求解柔性生产调度问题

为减少计算复杂度,将具有解决复杂组合优化问题的免疫克隆选择算法应用于求解柔性生产调度问题.首先设计一种有效的抗原和抗体的数据结构,用抗原表示待调度的生产计划,抗体表示高效的柔性生产调度结果;然后着重设计了用于产生高效的柔性生产调度结果的克隆免疫算子;最后运用该模型对一个实际生产系统进行仿真调度决策,实验评估结果验证了算法的正确性和有效性.     

冶铸轧一体化生产下动态调度策略和方法研究

为了解决冶铸轧一体化生产过程中的动态调度问题,以保证冶铸轧一体化生产稳定顺行。首先,通过分析炼钢生产过程中的扰动,提出了基于扰动处理的冶铸轧一体化生产下动态调度策略。之后,将动态调度策略归结为:计划延迟和LF炉处理策略;钢种改判、钢水回炉以及产品问题处理策略;设备替换处理策略。基于三类处理策略分别介绍了启发式规则和机器冲突消解模型、计划优化模型和智能优化算法以及设备替换算法等处理方法。最后对实际生产中常见的"追加计划"进行了仿真,仿真系统分别对炼钢-连铸计划以及热轧和加热炉计划进行了动态调度,结果表明系统能够依据扰动,动态调整生产计划,保证生产稳定顺行。     

汽车同步装配线生产计划与调度集成优化汽车同步装配线生产计划与调度集成优化

为克服传统的"自顶向下"方式下生产计划与调度不协调的缺陷,针对汽车同步装配线,构造了生产计划与调度集成优化混合整数规划模型,并采用拉格朗日松弛法将其分解为批量计划及调度等子问题.将调度子问题转化为与时间相关的旅行商问题,并采用dynasearch算法求解.对于拉格朗日对偶问题,采用均衡方向策略法求解.仿真实验结果验证了模型及算法的有效性.     

An integrated job shop scheduling and assembly sequence planning approach for discrete manufacturing

This paper proposes an integrated job shop scheduling and assembly sequence planning (IJSSASP) approach for discrete manufacturing, enabling the part processing sequence and assembly sequence to be optimized simultaneously. The optimization objectives are to minimize the total production completion time and the total inventory time of parts during production. The interaction effects between the job shop schedule and the assembly sequence plan in discrete manufacturing are analyzed, and the mathematical models including the objective functions and the constraints are established for IJSSASP. Based on the above, a non-dominated sorting genetic algorithm-II (NSGA-Ⅱ) with a hybrid chromosome coding mechanism is applied to solve the IJSSASP problem. Through the case studies and comparison tests for different scale problems, the proposed IJSSASP approach is verified to be able to improve the production efficiency and save the manufacturing cost of the discrete manufacturing enterprise more effectively.     

Robust design of flexible manufacturing systems using, colored Petri net and genetic algorithm

A method is presented for the robust design of flexible manufacturing systems (FMS) that undergo the forecasted product plan variations. The resource allocation and the operation schedule of a FMS are modeled as a colored Petri net and an associated transition firing sequence. The robust design of the colored Petri net model is formulated as a multi-objective optimization problem that simultaneously minimizes the production costs under multiple production plans (batch sizes for all jobs), and the reconfiguration cost due to production plan changes. A genetic algorithm, coupled with the shortest imminent operation time (SIO) dispatching rule, is used to simultaneously find the near-optimal resource allocation and the event-driven schedule of a colored Petri net. The resulting Petri net is then compared with the Petri nets optimized for a particular production plan in order to address the effectiveness of the robustness optimization. The simulation results suggest that the proposed robustness optimization scheme should be considered when the products are moderately different in their job specifications so that optimizing for a particular production plan creates inevitably bottlenecks in product flow and/or deadlock under other production plans.     

考虑换模时间的冲压车间库存储备定额优化

在市场经济条件下,科学合理地确定物资储备是企业物资管理的重要内容。以某车身厂的冲压车间及生产库房为例,建立了库存储备定额优化模型。该模型考虑了机器加工时的换模具时间,以最小化库存成本为目标,一定的供应下游生产能力和库存平均占用资金为约束。运用遗传算法求得了模型中库存定额的优化值,从而帮助企业制定出更加合理的短周期生产计划。     

基于智慧车间的生产执行系统的研究及应用

为了解决中小型塑料制造企业管理系统在信息采集方式、计划实时性、灵活性等方面的不足,将射频识别Radio Frequency Identification(RFID)技术引入塑料生产车间,构建塑料制造装配车间的物料智能配送体系,形成面向离散制造业的智慧装配车间。对生产执行系统Manufacturing Execution System(MES)的架构、RFID智慧生产车间应用流程、应用可靠性等关键技术进行了研究,并对车间生产组织、制造事件和动态多变市场的响应能力进行了优化。所述内容对提升塑料制造企业核心竞争力具有重要的理论与实际意义。     

Assembly line balancing and group working: A heuristic procedure for workers’ groups operating on the same product and workstation

In this paper, we examine an assembly line balancing problem that differs from the conventional one in the sense that there are multi-manned workstations, where workers’ groups simultaneously perform different assembly works on the same product and workstation. This situation requires that the product is of sufficient size, as for example in the automotive industry, so that the workers do not block each other during the assembly work. The proposed approach here results in shorter physical line length and production space utilization improvement, because the same number of workers can be allocated to fewer workstations. Moreover, the total effectiveness of the assembly line, in terms of idle time and production output rate, remains the same. A heuristic assembly line balancing procedure is thus developed and illustrated. Finally, experimental results of a real-life automobile assembly plant case and well-known problems from the literature indicate the effectiveness and applicability of the proposed approach in practice.     

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...     

A Case Study on Integrated Production Planning and Scheduling in a Three-Stage Manufacturing System

This paper presents an integrated optimization model of production planning and scheduling for a three-stage manufacturing system, which is composed of a forward chain of three kinds of workshops: a job shop, a parallel flow shop consisting of parallel production lines, and a single machine shop. As the products at the second stage are assembled from the parts produced in its upstream workshop, a complicated production process is involved. On the basis of the analysis of the batch production, a dynamic batch splitting and amalgamating algorithm is proposed. Then, a heuristic algorithm based on a genetic algorithm (known as the integrated optimization algorithm) is proposed for solving the problem. Note to Practitioners-This paper presents a method for integrated production planning and scheduling in a three-stage manufacturing system consisting of a forward chain of three kinds of workshops, which is common in such enterprises as producers of automobiles and household electric appliances, as in the case of an autobody plant usually with the stamping workshop, the welding and assembling workshop, and the painting workshop. Herein, the production planning and scheduling problems are simultaneously addressed in the way that a feasible production plan can be obtained and the inventory reduced. A batch splitting and amalgamating algorithm is proposed for balancing the production time of the production lines. And a case study of the integrated planning and scheduling problem in a real autobody plant verifies the effectiveness of our method