On the Consequences of Information Delays in the Scheduling of Semi-Automated Flexible Machines

Manufacturing systems with varying levels and types of flexibility employ alternative scheduling strategies to exploit flexibility for performance enhancement. Scheduling decisions in manufacturing systems are influenced by time delays due to information handling activities such as information collection, transfer, and processing. More specifically, scheduling strategies implicitly involve information intensive activities that may entail significant time delays for implementation, depending on the extant shop floor automation and integration within a flexible system. These are information delays and we believe that most contemporary flexible systems must inherently cope with some level of information delay when implementing on-line scheduling strategies. This paper conceptualizes the manifestation of information delays in the context of scheduling decisions within flexible systems through the definition of three key delay modes: (i) Mode 1 information-transfer delay; (ii) Mode 2 decision-implementation delay; and (iii) Mode 3 status-review delay. We then stress the need and importance of devising suitable on-line scheduling strategies for countering the effect of information delays by demonstrating the efficacy of a novel scheduling strategy on a single machine. While opening a new scheduling dimension with potential research ramifications, this paper highlights the fact that the concept of information delay can effectively capture the synergism issues related with flexibility, integration, and automation in the context of scheduling decisions within semi-automated flexible systems.     

工艺设计对生产调度结果的影响

提出了集成环境下工艺设计和生产调度的并行实现方法 ,讨论了备选工艺计划对调度结果的影响规律 ,给出了可实现多工艺备选的调度算法。仿真试验表明 ,增加工艺路线可以使零件的流通时间大大减少 ,资源利用率显著提高 ,是提高整个生产系统效率的有效途径     

Intelligent scheduling of automated machining systems

An automated machining system involves concurrent use of manufacturing resources, alternative process plans and flexible routings. High investment in the installation of automated facilities requires an efficient scheduling system that is able to allocate the resources specified for operations over a scheduling horizon. The primary emphasis of this paper is to generate schedules that accurately reflect details of the automated environment and the objectives stated for the system. In this paper, a rule for dispatching operations, named the Most Dissimilar Resources (MDR) dispatching rule, is introduced. A scheduling algorithm for automated machining is presented. Using the previous simulation research for this topic, a rule-based scheduling system is constructed. An architecture for an intelligent scheduling system is proposed, and the system has a high potential to provide efficient schedules based on the task-specific knowledge for the dynamic scheduling environment.     

Job shop scheduling using fuzzy logic

In a flexible manufacturing system (FMS) scheduling problems become extremely complex, even for simple breakdowns, when dynamic uncertainties such as machine breakdowns and the uncertain arrival of jobs are taken into consideration. In the first stage of this study, a fuzzy logic-based algorithm for assigning priorities to part types that are to be machined is proposed. In the second stage, an operation-machine allocation and scheduling algorithm is presented. A criteria contribution equalizer is used in decision-making. The proposed algorithm can re-generate the schedule in case of a machine breakdown, and therefore can be used as an on-line controller. The system architecture and linguistic variables are presented and results showed that the proposed algorithm improves the system efficiency.     

TTCAN网络调度平台的设计优化

TTCAN是近几年发展起来并广泛应用于汽车以及其它一般工业控制系统的实时传输协议~([1]).分析了TTCAN网络平台对于周期性消息及非周期性消息的调度策略,分别对其进行改进,并通过遗传算法对系统矩阵周期调度表进行优化,之后利用Simulink中的Stateflow工具针对一般工业控制系统建立了TTCAN网络调度仿真平台,并对仿真平台进行优化,优化后的仿真平台较好地提高了网络系统带宽利用率,增大了总线通信量,降低了各传感器节点周期性消息的响应时间和非周期性消息的延时时间,从而改善了网络平台的通信实时性能.     

基于多代理的敏捷制造单元调度研究

在分析敏捷环境下敏捷制造单元调度特点的基础上 ,提出了基于多代理协作的敏捷制造单元模型 ,并根据该模型设计了一种混合遗传模拟退火 (SAGA)单元调度算法。并给出SAGA和GA两种方法的比较结果。应用实例表明 ,该方法调度性能良好 ,调度过程快 ,支持任务的随机加入 ,为制造企业快速有效的响应市场 ,提高敏捷性提供了强有力的理论与技术支持。     

基于改进的两阶段控制策略的AGV路径优化调度研究

提出了一种基于改进后的两阶段控制策略和多目标的带约束遗传算法的控制策略,并用通过速度调节的冲突解决模式,实施对AGV系统的优化调度。首先利用遗传算法离线生成k条最优路径,再采用速度调节的冲突解决模式对其进行在线动态路径规划;若k条路径均不能满足条件,则用带约束多目标遗传算法计算最优路径。仿真证明:本文提出的调度策略,大大增加了AGV调度系统的柔性、效率和鲁棒性,提高了系统效率,为实际应用提供了技术依据。     

多目标批量生产柔性作业车间优化调度

研究批量生产中以生产周期、最大提前/最大拖后时间、生产成本以及设备利用率指标(机床总负荷和机床最大负荷)为调度目标的柔性作业车间优化调度问题。提出批量生产优化调度策略,建立多目标优化调度模型,结合多种群粒子群搜索与遗传算法的优点提出具有倾向性粒子群搜索的多种群混合算法,以提高搜索效率和搜索质量。仿真结果表明,该模型及算法较目前国内外现有方法更为有效和合理。最后,从现实生产实际出发给出多目标批量生产柔性调度算例,结果可行,可对生产实践起到一定的指导作用。     

Simulation study of an AGV system in an FMS environment

A simulation program written in ECSL to simulate an AGV system serving an FMS is presented. It incorporates a special algorithm to enable ‘intelligent’ routing of the AGVs with minimum control requirements. The program was used to examine several parameters and scheduling/control disciplines affecting the AGV system's performance for a specific FMS. Results show that selection of an appropriate combination of parameter values can have a beneficial effect on the FMS.     

Workflow balancing in parallel machines through genetic algorithm

Workflow balancing helps to remove the bottlenecks present in a manufacturing system. A genetic algorithm (GA) is used to solve the parallel machine scheduling problem of the manufacturing system with the objective of workflow balancing. The performance of GA is compared with three workflow balancing strategies namely random (RANDOM), shortest processing time (SPT) and longest processing time (LPT). The relative percentage of imbalance (RPI) is adopted among parallel machines for evaluating the performance of these heuristics. The GA shows better performance for the combination of various job sizes and machines. A computer program has been coded on an IBM/PC compatible system in the C++ language for experimentation to a standard manufacturing system environment in operation.     

基于GASA优化算法的不确定条件下Job-Shop调度问题研究

针对不确定因素和动态干扰事件下Job-Shop调度问题,基于模糊数理论和动态调度策略,综合考虑完工时间、机器加工成本和机器负荷,建立了作业车间多目标不确定性调度模型;为了求解该调度模型,结合遗传算法和模拟退火算法的特点,设计了遗传模拟退火混合算法,并针对作业车间的复杂性要求,对算法的编码解码、交叉变异算子以及保优策略等方面进行了改进;通过仿真,得到了初始调度方案,然后在此基础上,采用动态调度策略对紧急插单、机器故障、工件取消和交货期变更等不确定干扰事件进行了研究.通过对某电动产品生产公司车间进行的实证研究结果表明,根据上述研究得到的较好的调度方案,可以有效地提高机器利用率和客户满意度.该模型和算法能够较好地应用到企业实际生产中.     

车间作业计划问题的全局动态模型

对车间作业计划问题进行简要回顾，分析设计作业计划算法时,由于不合理的简化假设可能造成的一些问题，针对这些问题提出了主要由综合优先级、资源利用率平衡和问题预测机制3部分组成的全局动态模型，给出了基于该模型的具体实施办法。经实际数据仿真检验，该模型能较好的满足生产需要。     

面向大批量定制的可重构动态调度

动态可重构制造系统是实现大批量定制的关键需求之一。将强化学习方法应用于可重构动态调度系统．给出了一类典型的可重构多机并行调度决策的问题描述。针对该问题建立了基于分布耦合控制的强化学习决策方法。所给方法利用状态分解将原问题转化为一组设备控制器的耦合决策问题，以简化单个控制器的求解空间。在局部决策中进一步采用递阶的分层强化学习控制方法，使得设备排序调度决策与重构决策分离。重构控制器通过排序调度决策信息及外部设备控制器反馈信息调整设备加工模式。达到负荷平衡及优化调度的目的。     

工序集中型设备的作业排序系统开发

通过对制造业作业分配问题的分析,设计了作业排序系统的信息框架,并确定了系统的总体方案和功能模块。继而进行了系统数据库和前台程序的设计与开发。在作业排序方面,采用了Johnson-Bellman算法,实现总加工流程时间最短。同时设计了工件能按先到先服务或按交货期自动确定合适加工时间段的程序。从系统运行的效果可知,所开发的系统性能良好。     

Simultaneous scheduling of machines and vehicles in an FMS environment with alternative routing

Scheduling of flexible manufacturing systems is a well-known NP-hard problem which is very complex, due to additional considerations like material handling, alternative routing, and alternative machines. Improvement in the performance of a flexible manufacturing system can be expected by efficient utilization of its resources, by proper integration and synchronization of their scheduling. Differential evolution is a powerful tool which proved itself as a better alternative for solving optimization problems like scheduling. In this paper, the authors addressed simultaneous scheduling of both machines and material handling system with alternative machines for the makespan minimization objective. The authors proposed a machine selection heuristic and a vehicle assignment heuristic which are incorporated in the differential evolution approach to assign the tasks, to appropriate machine and vehicle, and to minimize cycle time.     

基于零件虚拟工序队列的FMS动态调度研究

提出虚拟工序队列的概念,并在此基础上提出一种基于静态零件分批（静态调度）的ＦＭＳ动态生产调度方法,该算法充分考虑到ＦＭＳ的系统资源限制及零件运输等环节,能较好地解决生产调度中的设备负荷平衡,系统紧急事件发生（如机床故障,新零件加工等）,可替代加工工序等问题,且易于实现,具有较广泛的适应性。     

基于时间窗口的网络控制系统调度算法

由于网络控制系统中各个控制设备共享物理传输介质,造成了控制设备争用总线的问题,从而引起了控制数据传输的延时,而反馈控制系统的稳定性能由环延时决定,需要研究一种调度算法对网络中消息的传输进行调度,使消息可以满足其实时性要求。该调度算法从控制系统稳定性能角度出发,利用控制环的最大允许环延时确定控制环的采样周期,同时基于时间窗口得出控制环中各个节点的起始传输时刻,最终确定了系统静态调度表的结构。最后分析了该调度算法在CAN总线应用中需解决的问题以及未来的研究工作。     

Real-Time Manipulation of Alternative Routeings in Flexible Manufacturing Systems: A Simulation Study

This paper presents the results of a simulation study of a typical flexible manufacturing system (FMS) that has routeing flexibility. The objective is this study is to test the effectiveness of the dissimilarity maximisation method (DMM) for real-time FMS scheduling. DMM is an alternative process plan selection method developed for routeing selection in off-line FMS sched-uling. An integrated framework that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to evaluate the effects of various operational control rules on the system performance. The hypothetical FMS employed in this study consists of seven machining centres, a loading and an unloading area, and six different part types. Owing to the existence of identical machining centres in the system, the part types have alternative routeings. For selecting an incoming part and later routeing it to a machining centre for its next operation, three control rules, namely, first-in first-out/first available (FIFO/FA), equal probability loading (EPL), and dissimilarity maximisation method/first-in first-out (DMM/ FIFO) are used. In this study, DMM is 1. Used as a real-time decision-making tool to select routeings for the parts that are in the system. 2. Tested and benchmarked against FIFO/FA and EPL. The results show that DMM/FIFO outperforms FIFO/FA and EPL on system throughput. Other measures such as average waiting time, average transportation time, and percentage utilisation rates are also investigated to provide insights for the effectiveness of the DMM rule for real-time FMS control applications.     

基于遗传算法的装配车间调度问题的研究

研究了装配车间调度问题,提出了一种基于遗传算法的车间作业调度方法。根据车间调度系统的特点,通过Delmia/QUEST软件建立了制造系统仿真模型进行仿真分析。结合仿真系统,分析了QUEST软件的设计原理及应用方法。最后通过计算机仿真模型实例验证了算法的有效性。     

Dissimilarity Maximization Method for Real-time Routing of Parts in Random Flexible Manufacturing Systems

This paper presents a dissimilarity maximization method (DMM) for real-time routing selection and compares it via simulation with typical priority rules commonly used in scheduling and control of flexible manufacturing systems (FMSs). DMM aims to reduce the congestion in the system by selecting a routing for each part among its alternative routings such that the overall dissimilarity among the selected routings is maximized. In order to evaluate the performance of DMM, a random FMS, where the product mix is not known prior to production and off-line scheduling is not possible, is selected for the simulation study. A software environment that consists of a computer simulation model, which mimics a physical system, a C++ module, and a linear program solver is used to implement the DMM concept. In addition to DMM, the simulation study uses two priority rules for routing (i.e., machine) selection and seven priority rules for selecting parts awaiting service at machine buffers. The results show (1) DMM outperforms the other two routing selection rules on production rate regardless of the part selection rule used, and (2) its performance is highly dependent on the part selection rules it is combined with.