面向定制生产系统的缓冲区优化配置方法

针对定制型装备制造企业中具有有限缓冲区的开排队网制造单元,其车间负荷界限即缓冲设置难以确定的问题（buffer allocation problem,BAP）,文章对每阶段具有有限缓冲区且含有多台加工设备的三阶段柔性流水车间(flexible flow shop,FFS)进行排队网建模,应用状态空间分解法对该模型进行分析求解,获得系统的一系列性能指标值。为了对该方法的有效性进行验证,对该模型设计仿真实验,并利用扩展法对模型进行求解,将数值结果进行比较分析,验证了利用该方法对FFS缓冲区进行优化配置的合理性,这对较大规模的多节点每阶段具有多台设备的流水车间负荷界限的有效设定及其规划具有参考和指导意义。     

带分段环形路径AGV的制造系统排队网建模与分析

针对含物料自动运输环节(automated material handling unit,AMHU)的个性化定制生产系统性能分析问题,文章着重考虑其随机批量运输的特点,提出了该系统的开排队网建模方法。对含AMHU的生产系统进行了描述,并建立其排队网模型;采用改良状态空间分解法,建立了节点状态空间模型,求解并计算出生产系统的性能指标值;与生产系统仿真模型的实验结果进行对比,验证了所提方法的精确性和有效性,为进一步优化配置该类生产系统的资源奠定了基础。     

带检测环节的制造单元布局优化

针对带检测环节的智能制造单元，考虑其具有随机性因素的特点，本文对其机器布局问题进行研究。首先对该智能制造单元的生产过程及特点进行分析，建立其机器布局优化问题的随机非线性整数规划的数学模型；然后建立该智能制造单元对应的仿真模型，对该优化问题进行求解；最后分析抽检率的变化对最优解造成的影响，并对该智能制造单元的性能指标进行方差分析，研究不同的布局方案和抽检率对系统性能的影响程度。研究成果为企业进行智能制造单元的机器布局提供决策依据。     

基于Petri网的包装物流系统建模仿真与优化

采用离散事件动态系统理论和Petri网建模技术,研究包装物流系统建模、仿真与优化,描述和分析系统要素及逻辑序列.以纸箱包装物流系统为例进行建模、仿真,优化分析,获得了该系统的优化模型.结果表明,这种研究方法可行有效.     

晶圆制造双闭环Interbay物料运输系统性能分析模型

双闭环Interbay物料运输系统是300 mm晶圆制造系统至关重要的组成部分。为在设计阶段快速有效分析其运行性能，本文提出了一种扩展马尔可夫模型。该模型充分考虑了运输小车在外环、内环和捷径导轨关键节点的运行、堵塞、装卸晶圆卡等系统状态，抑制了多运输小车运行环境下的模型状态空间规模爆炸，提高了性能分析模型的准确性与运算效率。采用某晶圆制造企业实际生产数据，将扩展马尔可夫模型与仿真模型进行比较。结果表明：两者在空载运输小车到达时间间隔、系统搬运能力和运输小车利用率等关键指标方面相对误差值较小；扩展马尔可夫模型明显具有更高的分析效率。由此验证了提出的扩展马尔可夫模型用于双闭环Interbay系统性能分析是有效的。     

Petri网在包装印刷生产中的应用

首先对包装印刷生产进行了分析,针对包装印刷生产的离散事件特性,本文运用广义随机Petri网(GPN)和基于活动扫描的调度方法对包装印刷生产线进行了建模仿真,分析仿真结果得到系统的多项性能指标数据,从而对系统进行优化,并进行了实例分析.     

滑板托盘集装单元货载搬运稳定性研究

目的为了规避托盘单元货载在叉车装卸搬运过程中因散垛、塌垛导致的货物事故。文中基于ADAMS仿真定量分析叉车装卸搬运过程中托盘单元货载稳定性。方法瓦楞纸箱货物分别采用重叠堆码和交错堆码,在牛卡纸滑板托盘上堆码达到2200mm的极限高度,形成滑板托盘集装单元货载,不施加裹膜、捆扎等固定措施。以这2种堆码方式形成的滑板托盘集装单元货载为研究对象,建立叉车搬运作业ADAMS动力学仿真模型,并进行货载稳定性分析。结果从仿真结果中可以得到,当货物质量为14 kg时,货物偏移和振动加速度最大,此时对比叉车车身速度曲线和实验要求曲线,验证了仿真数据设置的合理性;提取货物与托盘间位置偏移曲线,得到重叠堆码时,货物沿着叉尖方向的偏移量达到了最大值123.4 mm;提取货物振动加速度曲线,对货物脆值进行评价,得到货物若脆值需在60以上才不会因振动损坏。结论在不施加裹膜、捆扎等固定措施的情况下,采用这2种堆码方式形成的滑板托盘集装单元货载在叉车装卸搬运过程中虽未出现塌垛现象,但堆码在高层的货物发生了较大位置偏移和颠簸振动而存在散垛及损伤货物的危险。建议施加外部约束如裹膜、捆扎等必要措施。     

医疗转诊建模评估及医保政策应用分析

基于马尔可夫理论对同一医联体内部上层医院和下层医院之间合作转诊的问题进行了排队网络的建模分析和优化决策。首先利用平均场理论对系统进行了分析,而后进一步设计了以矩阵几何为基础,以相关性迭代为算法,从而获得了系统的各类性能指标的解析结果。根据数值实验探讨了上层医院向下层医院的转诊率对系统性能的影响,并进一步指出该模型对保险共付比政策优化的潜在应用。该模型对于评估我国双向转诊系统的性能和相应的政策研究具有指导意义。     

滚珠丝杠进给系统动力学建模与动态特性分析

考虑滚珠丝杠进给系统中各结合面接触刚度的影响,提出一种有限元建模方法,用于研究滚珠丝杠进给系统的动态特性。将丝杠螺母、导轨滑块和滚动轴承简化为弹簧-质量模型。基于Hertz接触理论推导出其接触刚度的计算公式,采用多单元混合的方法划分网格,建立整个进给系统的有限元模型,仿真得到承载台的前五阶模态振型和固有频率;采用锤击激励法对滚珠丝杠进给系统进行模态试验,试验结果表明仿真和试验得到的模态振型基本一致,固有频率的最大误差为8.9%;基于该有限元模型分析了主轴质量、滚动导轨副预紧力以及滑块间距对进给系统振型分布和固有频率的影响。所提出的动力学建模方法和研究结果对滚珠丝杠进给系统的动态特性分析和结构优化具有参考价值。     

未知非线性系统的神经网络建模与控制仿真研究

针对一类未知非线性系统的建模与控制问题，采用基于神经网络的多步预测控制算法进行了仿真研究，仿真对象选取控制工程界常用的单摆试验装置．该算法的实现步骤为：获取系统开环试验数据；辨识神经网络正向动态模型；设计非线性优化控制律．仿真研究结果表明，所提出的建模与控制方法是有效的．     

Two-level manufacturing system performance analyser

Open queuing network is a commonly used analytical tool for modelling manufacturing systems. Parametric decomposition is a proven solution method for analysing open queuing networks and can estimate key performance measures such as work-in-process inventory, cycle time, and machine utilisation, fairly accurately. This paper presents a two-level hierarchical open queuing network model, which considers numerous features seen in a real manufacturing system including, machine set-up, material handling device setup (for example, loading and unloading operations), process as well as transfer batching, empty travel of the material handling device and machine or material handling device failures. The model first analyses a higher level open queuing network whose nodes are aggregations of a set of machines. The higher level network is solved via the parametric decomposition method and the results are then disaggregated to get lower level, e.g. machine specific, results. The motivation, algorithm and its relationship with the one-level model are discussed. Experimental results are provided to show that the two-level model provides comparable results with the one-level model in addition to its computational and managerial advantages. In addition, both are shown to provide better results than a recent method available in the literature that is based on the well-known queuing network analyser.     

Fuzzy-based system reliability of a labour-intensive manufacturing network with repair

This paper presents a fuzzy-based assessment model to evaluate system reliability of a labour-intensive manufacturing system with repair actions. Due to the uncertainty in human performance, labour-intensive manufacturing systems must determine the capacity of each labourer in order to accurately characterise the performance of the systems. Therefore, we model such a manufacturing system as a fuzzy multi-state network in order to characterise the labourers’ influence on workstation performance. First, the workstation reliability is defined according to the loading state by three fuzzy membership functions, namely ‘under loading’, ‘normal loading’ and ‘over loading’, respectively. The system reliability is subsequently evaluated with fuzzy intersection operations in terms of these workstation reliabilities. Thus, the system reliability is defined as a fuzzy membership function to assess whether the manufacturing system performance is sufficient to satisfy the demand reliably. A case study of a footwear manufacturing system is illustrated to explain the proposed model. Furthermore, we apply the proposed model to a non-labour-intensive manufacturing network in order to validate the applicability to this class of systems.     

智能制造系统AGV小车及缓冲区容量仿真优化

具有MHS(material handling system)的智能制造系统AGV(automated guided vehicle)小车及缓冲区最大容量配置优化,属于典型的非线性整数规划问题。由于约束无法用封闭形式表达,因此较难获得问题的精确解。为此,本文提出了仿真优化的方法以获得问题的近似解。首先,对AGV小车及缓冲区最大容量配置优化问题进行了描述;其次,基于Em plant平台建立了具有MHS的智能制造系统仿真模型;然后,基于不同的优化目标,提出了3种仿真优化方法;最后,通过仿真试验对上述3种方法进行了分析与比较。分析表明,本文提出的方法及优化结果,可为企业配置AGV小车及缓冲区最大容量提供决策支持。     

Performance analysis of open general queuing networks with blocking and feedback

Queuing network models have been extensively used for performance evaluation in many modern manufacturing and communication systems. The phenomenon of feedback reflects many practical situations, e.g. reworking in the production systems. However, existing research on open queuing network with feedback mainly concentrates on the models with infinite buffers or the models with finite buffers but exponentially distributed inter-arrival and service times. Research on open queuing networks with finite buffers, feedback and general inter-arrival and service times has not been reported. In this paper, a Rate Iterative Method embedded with the Generalised Expansion Method, is proposed for modelling this type of queuing network. System performance measures include the mean throughput, work-in-process and sojourn time all calculated by the proposed method. The accuracy and the efficiency of the proposed method are tested by comparing the results with other methods or simulation results from the experiments. Finally, a case study of a practical production system used in the manufacturing industry is studied and illustrates the applications of the proposed method. The results in this paper can be used as a basis for system design analysis and resource planning.     

Dealing with design options in the optimization of manufacturing systems: An evolutionary approach

When designing a manufacturing system, several features have often to be determined to optimize a performance criterion. We propose an optimization simulation method that can be applied to optimize problems taking into account design options and any type of parameters. This method is based on the association of an evolutionary algorithm using a specific data structure and a simulation model. New mutation and recombination operators are proposed, which are adapted to this specific data structure. This approach is implemented on a network of Sun workstations, each station being responsible for running its own simulation model and its own evolutionary algorithm. This method is illustrated through the problem of designing a manufacturing system.     

A genetic algorithm and queuing theory based methodology for facilities layout problem

Facilities layout, being a significant contributor to manufacturing performance, has been studied many times over the past few decades. Existing studies are mainly based on material handling cost and have neglected several critical variations inherent in a manufacturing system. The static nature of available models has reduced the quality of the estimates of performance and led to not achieving an optimal layout. Using a queuing network model, an established tool to quantify the variations of a system and operational performance factors including work-in-process (WIP) and utilisation, can significantly help decision makers in solving a facilities layout problem. The queuing model utilised in this paper is our extension to the existing models through incorporating concurrently several operational features: availability of raw material, alternate routing of parts, effectiveness of a maintenance facility, quality of products, availability of processing tools and material handling equipment. On the other hand, a queuing model is not an optimisation tool in itself. A genetic algorithm, an effective search process for exploring a large search space, has been selected and implemented to solve the layout problem modelled with queuing theory. This combination provides a unique opportunity to consider the stochastic variations while achieving a good layout. A layout problem with unequal area facilities is considered in this paper. A good layout solution is the one which minimises the following four parameters: WIP cost, material handling cost, deviation cost, and relocation cost. Observations from experimental analysis are also reported in this paper. Our proposed methodology demonstrates that it has a potential to integrate several related decision-making problems in a unified framework.     

System performance analysis of flexible flow shop with match processing constraint

Blocking makes the analytical modelling of open queuing networks with finite buffers intractable because the product-form solutions are unavailable. In this paper, about mould manufacturing, a four-stage flexible flow shop with match processing constraint is first modelled as an open queuing network with finite buffers. According to the characteristics of the matching node, the inter-arrival time distributions of parts arriving at the nodes are assumed to be exponential or general. Next, based on approximation of queuing theory, the Decomposition of State Space Method and the Generalized Expansion Method are developed for system performance evaluation. Then, experiments to assess the accuracy of the proposed methods are reported by comparing the analytical results with simulations. Finally, a case of a real-life production system of mould manufacturing is studied to show the application of the proposed methods. The results of experiments reveal that the proposed methods are feasible and effective for system performance evaluation and they can even solve large-size practical problems in a reasonable time. The results in this paper can provide a basis for system design or resource planning, to solve buffer allocation problems and capacity configuration problems.     

An analysis of the ceiling height requirement for a large-scale semiconductor fab

This paper proposes the proposition that the fab ceiling height may become a bottleneck for throughput in a large-scale semiconductor fab. To justify the proposition, we propose a systematic approach for the design of the fab ceiling height. In this approach, we develop a queuing network model to evaluate the cycle time performance of a fab design under a target throughput. This queuing network model is adapted from Connor et al. [1996. A queueing network model for semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing, 9 (3), 412–427] by additionally treating the transportation facilities as finite-capacity resources. Numerical experiments were carried out. The results indicate that a large-scale fab with an inappropriate ceiling height may limit the installation of transportation capacity, which, in turn, limits the utilisation of tool capacity, and thus lowers the fab throughput that can be achieved.     

Performance evaluation of a multi-product system under CONWIP control

Analytical models of multi-product manufacturing systems operating under CONWIP control are composed of closed queuing networks with synchronization stations. Under general assumptions, these queuing networks are hard to analyze exactly and therefore approximation methods must be used for performance evaluation. This research proposes a new approach based on parametric decomposition. Two-moment approximations are used to estimate the performance measures at individual stations. Subsequently, the traffic process parameters at the different stations are linked using stochastic transformation equations. The resulting set of non-linear equations is solved using an iterative algorithm to obtain estimates of key performance measures such as throughput, and mean queue lengths. Numerical studies indicate that the proposed method is computationally efficient and yields fairly accurate results when compared to simulation.