State-dependent models of material handling systems in closed queueing networks

A comprehensive algorithmic analysis of finite state-dependent queueing models and exponentially distributed workstations is formulated and presented. The material handling system is modeled with finite state-dependent queueing network M/G/c/c models and the individual workstations are modeled with exponentially distributed single and multi-server M/M/c queueing models. The coupling of these queueing models is unique via the material handling structure. The performance modeling of the systems for series, merge, and split and other complex network topologies are included so as to demonstrate the type of topological network design that is possible with these incorporated material handling systems. Of some importance, it is shown that these integrated M/M/c and M/G/c/c networks have a product form when the population arriving at the M/G/c/c queues is controlled. Numerous experimental results demonstrate the efficacy of our approach for a variety of contexts and situations.     

Performance evaluation and capacity planning in a metallurgical job-shop system using open queueing network models

In this paper, we apply performance evaluation and capacity allocation models to support decisions in the design (or redesign) and planning of a job-shop queueing network of a metallurgical plant. Approximate parametric decomposition methods are used to evaluate system performance measures, such as the expected work-in-process (WIP) and production leadtimes. Based on these methods, optimisation models are then applied for the allocation (or reallocation) of capacity to the stations of the job-shop network. These models are also used to generate approximate trade-off curves between capacity investment and WIP or leadtime, which are valuable for a production manager to estimate how much capacity should be allocated to the stations to reach some targeted performance measures. These curves are also useful for the sensitivity analysis of the solutions to changes in the input parameters, such as the variability of the product demands, the mix of the production and the throughput rate of the network.     

Decomposition without aggregation for performance approximation in queueing network models of semiconductor manufacturing

Accurate and speedy forecasts of production cycle time are key components that support the operation of modern semiconductor wafer fabricators. Estimates of cycle time can be obtained via simulation, but such an approach, though common, requires significant computational investment and model maintenance. Queueing network models and approximations for their performance can provide a viable alternative. As modern semiconductor manufacturing systems exhibit largely reentrant product routing, but contain essential probabilistic routes (for metrology and rework), prior mean cycle time approximation methods are not well suited to the system structure. In this paper, we extend the decomposition without aggregation (DWOA) approach – which is tailored to systems with deterministic routing – to allow for the existence of probabilistic paths. Numerical and simulation studies are conducted with numerous practically inspired datasets to assess the quality of the resulting mean cycle time approximations. The results reveal that our approach outperforms the existing mean cycle time approximations on datasets inspired by the semiconductor industry MIMAC benchmark datasets. For example, in MIMAC dataset 1, our mean cycle time approximations exhibit an average of 10.33% error compared to 18.82% error for existing approaches.     

Effective process times for multi-server flowlines with finite buffers

An Effective Process Time (EPT) approach is proposed for the building of aggregate models to represent multi-server tandem queues with finite buffers. EPT distributions of the workstations in the flow line are measured without identifying the contributing factors. A sample path equation is used to compute the EPT realizations from arrival and departure events of lots at the respective workstations. If the amount of blocking in the line is high, the goodness of fits of the EPT distribution determines the accuracy of the EPT-based aggregate model. Otherwise, an aggregate model based on just the first two moments of the EPT distributions is sufficient to obtain accurate predictions. The approach is illustrated in an industrial case study using both simulation and analytical queueing approximations as aggregate models.     

A discrete-time queueing network approach to performance evaluation of autonomous vehicle storage and retrieval systems

In this paper, we present a method for performance evaluation of autonomous vehicle storage and retrieval systems (AVS/RSs) with tier-captive single-aisle vehicles. A discrete-time open queueing network approach is applied. The data obtained from the evaluation of the lift and vehicle movements can be used directly as input for the general discrete service time distributions of the queueing network. Furthermore, the approach allows for the computation of the retrieval transaction time distribution as well as of the distribution of the number of transactions waiting to be stored. Consequently, not only expected values and variances but also quantiles of the performance measures can be obtained. Comparison to discrete-event simulation quantifies approximation errors resulting from the decomposition approach in the discrete-time domain. Moreover, the errors obtained by the discrete-time approach are compared to the errors obtained using a continuous-time open queueing network approach. Finally, it will be outlined how the model can be used for designing AVS/RSs according to given system requirements, such as storage capacity, throughput, height and length of the system as well as the 95% quantile of the retrieval transaction time.     

Multi-class queueing models for performance analysis of computer systems

Queueing models, networks of queues in particular, have been found especially useful for estimating the performance of computer systems. Networks of queues with multiple customer classes provide a flexible framework for modelling computer systems, where a rich set of analytical results and techniques are available. When because of the complexity of the system being modelled the analytical results cannot be applied directly, they often point to fairly accurate approximation schemes. In this paper, we present a brief survey of some of the important results and techniques from the theory of multi-class queueing networks. We also present a case study to illustrate how these results and techniques are used in a real-life situation where many of the modelling constraints are violated.     

基于RSU辅助的车载机会网络通信能力增强方案

针对传统车载机会网络通信能力的有限性及随机化的问题,提出一种通过部署路边单元(RSU)进行辅助通信来增强车载机会网络通信能力的方案.该方案利用RSU稳定的覆盖、存储和传输优势,有效克服传统车载机会网络通信时间间隔长、传输能力有限等缺点.以北京和上海各自一个月的出租车全球定位系统(GPS)数据为基础,对车辆与RSU的相遇特性进行了分析,发现该方案通过合理部署RSU对车辆信息进行缓存,可以极大地提高车辆间的通信概率.理论分析和仿真实验表明,利用RSU可以完成车与车之间大数据的传输,能极大提升车载机会网络的通信能力.     

Performance modelling of a fault-tolerant real-time multiprocessor using stochastic Petri nets

The fault-tolerant multiprocessor (ftmp) is a bus-based multiprocessor architecture with real-time and fault-tolerance features and is used in critical aerospace applications. A preliminary performance evaluation is of crucial importance in the design of such systems. In this paper, we review stochastic Petri nets (spn) and developspn-based performance models forftmp. These performance models enable efficient computation of important performance measures such as processing power, bus contention, bus utilization, and waiting times.     

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.     

Analysis of one-dimensional stochastic finite elements using neural networks

This paper explores the applicability of neural networks for analyzing the uncertainty spread of structural responses under the presence of one-dimensional random fields. Specifically, the neural network is intended to be a partial surrogate of the structural model needed in a Monte Carlo simulation, due to its associative memory properties. The network is trained with some pairs of input and output data obtained by some Monte Carlo simulations and then used in substitution of the finite element solver. In order to minimize the size of the networks, and hence the number of training pairs, the Karhunen–Loéve decomposition is applied as an optimal feature extraction tool. The Monte Carlo samples for training and validation are also generated using this decomposition. The Nyström technique is employed for the numerical solution of the Fredholm integral equation. The radial basis function (RBF) network was selected as the neural device for learning the input/output relationship due to its high accuracy and fast training speed. The analysis shows that this approach constitutes a promising method for stochastic finite element analysis inasmuch as the error with respect to the Monte Carlo simulation is negligible.     

Batch sizes optimisation by means of queueing network decomposition and genetic algorithm

Batch sizes have a considerable impact on the performance of a manufacturing process. Determining optimal values for batch sizes helps to reduce inventories/costs and lead times. The deterministic nature of the available batch size optimisation models reduces the practical value of the obtained solutions. Other models focus only on critical parts of the system (e.g., the bottleneck). In this paper, we present an approach that overcomes important limitations of such simplified solutions. We describe a combination of queueing network analysis and a genetic algorithm that allows us to take into account the real characteristics of the system when benefiting from an efficient optimisation mechanism. We are able to demonstrate that the application of our approach on a real-sized problem with 49 products allows us to obtain a solution (values for batch sizes) with less than 4% relative deviation of the cycle time from the exact minimal value.     

Approximation of single-class queueing networks with downtime-induced traffic variability

Queuing networks have been used with partial success for analytical modelling of manufacturing systems. In this paper, we consider a tandem system with high traffic variability caused by downtime events in the first queue. We propose improved approximation for departure variability in order to predict the waiting duration at the bottleneck queue located last in the line. We demonstrate that existing methods do not properly approximate such systems and provide some reasons and insights. Thus, a new decomposition method which employs the variability function principles is proposed. We differentiate between two components of the departure variability in multi-class systems: the ‘within-class effect’ – the variability caused by the class’ own inter-arrival and service time distributions – and the ‘between-class effect’ – the variability caused by interactions with other classes. Our analysis shows that the first effect can be approximated by existing multi-class decomposition methods, while the second effect requires a new development. Our proposed approximation for between-class effect is based on simulating a proper sub-system. The method enables modelling different policies of downtimes (e.g. FCFS, Priority). Numerical experiments show relative errors much smaller vs. existing procedures.     

无线中继网络系统容量最大化中继选择机制

分析了基于用户频谱效率的中继选择算法的不足,基于最大流最小割定理,给出了系统容量最优化问题模型,分析了两跳中继网络接入链路和中继链路对系统容量的不同影响.基于链路权重因子,提出一种基于系统容量最大化的中继选择算法.对不同中继选择算法下的系统容量差异的理论与仿真分析结果表明,提出的系统容量最大化中继选择算法可以获得更优的系统容量性能,并对网络拓扑和节点个数具有良好的鲁棒性.     

Fuzzy-based coverage and capacity scheme in LTE heterogeneous networks

Abstract

Coverage and capacity optimization (CCO) is a crucial procedure in Long-Term Evolution (LTE) Self-Organizing Network (SON). In recent studies, fuzzy theory has been widely applied for CCO in centralized SON but not in distributed SON. Distributed SON can be applied in user-deployed small cells such as femtocells. In the present paper, a distributed, autonomous, and low-complexity fuzzy-based coverage and capacity scheme is proposed for LTE heterogeneous networks (HetNet). To accomplish this goal, the proposed scheme manages radio resources to minimize inter-cell interference. A tradeoff exists between cell coverage and capacity due to inter-cell interference. By leveraging three fuzzy memberships, the scheduling decision is adaptively made by a low-complexity intersection function. Different from conventional fuzzy approaches, the proposed approach does not depend on pre-defined fuzzy rules and pre-defined fuzzy membership models. System performance is evaluated in terms of throughput and energy efficiency. The simulation results show that the proposed approach improves system performance by up to about 39% compared with a joint optimization algorithm.     

A multiplicative finite strain finite element framework for the modelling of semicrystalline polymers and polycarbonates

This paper presents a phenomenological model for the simulation and analysis of stress‐induced orientational hardening in semicrystalline polymers and polycarbonates at finite strains. The notion of intermediate (local) stress‐free configuration is used to develop a set of constitutive equations, and its relation to the multiple natural (stress‐free) configurations in the class of materials being considered here is discussed. A hyperelastic stored energy function, written with respect to the intermediate stress‐free configuration is presented to model the finite elastic response. It is then combined with the J₂‐flow theory to model the finite inelastic response. The isochoric constraint during inelastic deformation is treated via an exact multiplicative decomposition of the deformation gradient into volume‐preserving and spherical parts. The numerical solution algorithm is based on the use of operator splitting technique that results in a product formula algorithm with elastic‐predictor/inelastic‐corrector components. Numerical results are presented to show the behaviour of the model. Copyright © 2000 John Wiley & Sons, Ltd.     

两类排队网络的逼近研究

本文给出了两类排队网络。一类是容量有限的队列网络,我们证明了在高负荷下,标准化的队长过程弱收敛于半鞅反射的布朗运动：另一类是带有反馈的多类顾客多服务台队列网络,我们获得了队列网络中负荷过程的扩散逼近。     

Performance modelling of a solar road panel prototype using finite element analysis

Performance prediction is a critical step towards the acceptance of a new pavement structure. This is true for both conventional and innovative designs; however, it is particularly important for innovative designs that attempt to redefine pavement design practices. One such innovative design concept is the solar road panel; a road panel with a transparent surface that generates electricity through embedded solar cells. Despite the work completed by multiple organisations towards the development of this concept, questions exist about the viability of these panels as a structural pavement surface. This paper investigates these questions through a finite element modelling approach that assesses a prototype panel's performance on a variety of structural bases. Overall, this paper finds that it is possible to design a solar road panel to withstand traffic loading and that a concrete structural base allows for substantial optimisation to the analysed prototype design.     

Variability modelling and balancing of stochastic assembly lines

In a production flow line with stochastic environment, variability affects the system performance. These stochastic nature of real-world processes have been classified in three types: arrival, service and departure process variability. So far, only service process – or task time – variation has been considered in assembly line (AL) balancing studies. In this study, both service and flow process variations are modelled along with AL balancing problem. The best task assignment to stations is sought to achieve the maximal production. A novel approach which consists of queueing networks and constraint programming (CP) has been developed. Initially, the theoretical base for the usage of queueing models in the evaluation of AL performance has been established. In this context, a diffusion approximation is utilised to evaluate the performance of the line and to model the variability relations between the work stations. Subsequently, CP approach is employed to obtain the optimal task assignments to the stations. To assess the effectiveness of the proposed procedure, the results are compared to simulation. Results show that, the procedure is an effective solution method to measure the performance of stochastic ALs and achieve the optimal balance.     

Reliability and performance analysis of time – space – time switching networks with multiple separated space switches

Since electronic switching systems usually require very strict reliability requirements as well as good performance objectives, we need to jointly analyse the performance and reliability of switching systems. In this paper, we compare conventional time–space–time switches with single space switches with those with multiple separated space switches, from the viewpoints of reliability and performance. We consider time–space–time switching networks which consist of N incoming time switches, i.e. one NxN space switch, two (N/2)x(N/2) space switches, and four (N/4)x(N/4) space switches. We introduce a Markov reliability model to study the effect of failures and analyse the reliability and performance of three different types of switching networks in terms of average blocking probability and the mean time to unreliable operation, as we vary the offered traffic. As a result, T–S–T switching networks with multiple separated space switches exhibit better performance and reliability than those with single space switches.