现代制造系统中的供应链管理功能模型

总结现代制造系统发展趋势的基础上,提出供应链及其管理理论是实现企业协同的重要途径;给出了供应链管理概念模型的描述方法,该模型能寒带地表示出供应链中的过程实体活动及其相互关系。并表示出实现供应链管理的基础设施是信息流、物流和资金流在各供应链过程实休主时协调;地面向产品的供应链管理多级／多层功能功模型结构及功能模块的分解描述;该模型过程包括计划过程、资源过程、制造过程和销售过程;用ＩＤＥＦＯ图描述了各     

基于本体与多Agent的可靠供应链网络设计模型

针对供应链环境下的分布性、不确定性和动态性特征,基于本体与多Agent技术,构建了一种集成多种智能算法的可靠供应链网络设计模型。通过服务本体实现成员企业服务发布与发现,通过工作流本体实现订单任务动态分解,综合采用投招标策略和可靠性优化策略,实现可靠供应链网络的最优设计。其中,优化Agent由投标企业可靠性评估机制、目标可靠性预测机制以及基于可靠性的任务分配机制构成。通过一个应用实例验证了系统的可行性与有效性。     

分散决策供应链生产计划协同研究

为解决多级、多产品、分散供应链系统生产计划协同问题,提出了一种基于拉格朗日松弛算法的生产计划协同模型.在该模型中,建立每个企业独立的生产计划模型,使用拉格朗日松弛算法,松弛掉企业之间的物流平衡约束,将需要集中决策的供应链生产计划协同问题,分解为企业间分散的独立决策问题;运用次梯度算法对拉格朗日因子进行更新,通过反复迭代的优化过程实现生产计划协同.仿真实验表明,基于拉格朗日松弛算法的供应链协同对复杂供应链系统能够较好地逼近最优解,协同效果和收敛速度优于遗传算法.     

面向供应链管理的产品设计方法研究

为了提高产品对应的供应链的性能,在设计过程中需要针对供应链进行优化。介绍了面向供应链管理的产品设计的4个主要策略,提出了企业在整个产品开发过程中实施面向供应链管理的设计的基本流程,并建立出了一个实现框架。     

利用拉格朗日松弛算法协调多厂供应链生产计划

为了解决多厂供应链生产计划的协调问题,提出了一种基于拉格朗日松弛算法的内部价格协调优化策略。该策略通过松弛工厂之间的物料耦合约束,将整个供应链的生产计划问题分解为多个单厂的生产计划问题。每个工厂只需利用本地信息制定各自的生产计划。为了获取问题的可行解,又提出了一种前溯式可行化方法,通过协调中心对产品内部价格（拉格朗日算子）的迭代更新,实现整个供应链生产计划的协调优化。仿真实验表明,该策略能够较好地协调多厂供应链计划,结果明显优于已有的协调方法。     

供应链管理中工程数据库集成技术

信息技术的发展为制造系统供应链管理提供了有效支持,供应链上的节点均是 独立自主的过程实体。物理上分散,逻辑上也分散的分布式数据库管理系统存在数 据库构建困难及系统复用性、过程实体自治性差等缺点。本文提出物理上分散,逻辑 上集中的分布式数据库管理系统结构模型,并设计过程实体数据库与供应链全局工 程数据库集成的应用程序接口实现方案,解决了分布式供应链管理中工程数据库集 成的问题。     

基于动态设计结构矩阵的复杂产品配置过程规划技术

为降低复杂产品配置任务间的耦合程度,减少配置过程的迭代次数,优化产品配置设计过程,以动态设计结构矩阵(Design structure matrix,DSM)为工具研究了产品配置过程的规划技术。研究基于数据流图的产品配置过程任务建模,在此基础上通过映射得到配置过程DSM,并将其拓展为三视图结构,通过视图间的双重映射获得配置过程动态DSM,使客户需求和最新配置知识在产品配置过程中得以动态反映。用矩阵的分解和撕裂算法对配置过程进行规划,重组配置任务,优化任务执行次序,为协同配置设计任务分配提供基础。以大型电除尘装备为例子分析配置设计过程规划技术的具体实现。     

基于PDM协同设计任务建模与调度方法研究

从产品数据管理系统中协同设计过程任务建模的角度出发,提出基于产品结构分解的协同设计过程人员-任务分配模型,建立任务结构的约束映射和基于可扩展着色Petri网的任务过程建模方法,实现Multi-agent协同设计过程任务调度集成框架,最后进行了系统实现.     

基于Pareto最优的多目标集成协作计划与调度

针对现有制造系统中协作计划、生产计划和调度方案不能同步制定的问题,考虑在供应链环境下有协作的计划与调度,构建了一种多目标集成协作计划与调度优化模型。提出一种基于Pareto最优的多目标优化算法,设计了包含协作染色体的基于作业的集成编码方案,通过惩罚操作实现协作计划与生产计划的同步协调。考虑供应链协调中常见的完工时问、总成本、总拖期时间、平均流经时间四个性能指标对模型进行整体优化。通过仿真实验验证了模型及其算法的有效性。     

复杂产品开发过程中资源优化使用技术研究

为实现复杂产品开发过程中制造资源的优化选择和使用,提出一种基于分层的多目标优化决策方法。面向过程的任务分层分解技术,将影响资源选择的约束因素和评价标准与特定的产品开发任务相结合,保证所选择资源的实用性。并行协同产品开发环境的建立以及基于Agent技术的资源调度过程实现,为制造资源共享和优化使用准备了条件。通过改进的多目标优化决策方法结合增益目标、损益目标准则下两个效用评价函数,详细地描述了服务响应时间、服务质量、成本、安全性等约束目标下资源优化选择的原理和过程,实现了资源调度的“排序选优”。结合工程实例,验证了该算法的可行性。     

The optimization of attribute selection in decision tree-based production control systems

This study develops a learning-based production control system (PCS) to support a manufacturing system to make on-line decisions that are robust in the face of various production requirements. Selecting essential system attributes (or features) based on various production requirements to construct PCS knowledge bases is a critical issue because of the existence of a large amount of shop floor information in a manufacturing system. However, a classical decision tree (DT) learning approach to construct dynamic dispatching knowledge bases does not consider the optimal subset of system attributes in the problem domain. To resolve this problem, this study develops a hybrid genetic algorithm/decision tree (GA/DT) approach for DT-based PCS. The hybrid GA/DT approach is used to simultaneously evolve an optimal subset of system attributes and determine learning parameters of the DT from a large set of candidate manufacturing system attributes according to various performance measures. For a given feature subset and learning parameters of a DT decoded by a GA, a DT was applied to evaluate the fitness in the GA process and to generate the PCS knowledge base. The results demonstrate that the proposed GA/DT-based PCS has, according to various performance criteria, a better long term system performance than those obtained with classical DT-based PCS and the heuristic individual dispatching rules, according to various performance criteria.     

A simulated annealing algorithm for integration of shop floor control strategies in semiconductor wafer fabrication

The semiconductor manufacturing industry is one of the most important industries in Taiwan. Wafer fabrication is an essential process in semiconductor manufacturing. However, controlling the production system on the shop floor is extremely difficult owing to the complicated manufacturing process and reentrant characteristics. In this paper, the shop floor control (SFC) integration strategies (order review/release, dispatching, and rework strategies) in wafer fabrication are considered with using several performances. We reviewed the literature on SFC strategies in wafer fabrication. The proposed combination simulation and simulated annealing (SA) algorithm is presented for SFC strategies in wafer fabrication. The objective was to seek the near global optimum solution for the combination of SFC strategies for a specific performance indicator. From the results, the proposed methodology was found to perform well for combinations of SFC strategies using different performance indicators in wafer fabrication. However, no single combination of SFC strategies could satisfy all performance indicators. Hence, considering the trade-off among these production control strategies, a suitable strategy should be chosen based on the system control tactics. Considerable computational time was saved in this research.     

A mixed dispatching rule approach in FMS scheduling

Short-term scheduling in flexible manufacturing systems (FMSs) is a difficult problem because of the complexities and dynamic behavior of FMSs. To solve this problem, a dispatching rule approach is widely used. In this approach, however, a single dispatching rule is usually assigned for all machines in a system during a given scheduling interval. In this paper, a mixed dispatching rule which can assign a different dispatching rule for each machine is proposed. A search algorithm which selects an appropriate mixed dispatching rule using predictions based on discrete event simulation is developed for this approach. The search algorithm for the mixed dispatching rule is described in detail. The effectiveness (in meeting performance criteria) of the mixed dispatching rule and the efficiency of the search algorithm relative to exhaustive search (complete enumeration) is demonstrated on an FMS model. The mixed dispatching rule approach performs up to 15.9% better than the conventional approach, and is 4% better on average. The statistical significance of the results is dicussed.     

Dispatching of overhead hoist vehicles in a fab intrabay using a multimission-oriented controller

The semiconductor manufacturing system has become one of the most important manufacturing systems in recent years. Intrabay automation for wafer transport is in high demand in a 300 mm foundry fab. The control of the transport system plays an important roles in manufacturing efficiency and the satisfaction of production strategy. In general, efficiency is the most important issue that has appeared in most research of automated transport systems. However, how to dynamically adjust the transport policy to meet the production strategy and to increase the transport efficiency as well seems to be more crucial to modern semiconductor manufacturing systems. In this paper, a fuzzy-logic-based multimission-oriented overhead vehicle dispatcher is developed. The vehicle dispatching rule is assigned in real-time according to the statistics of the manufacturing performance. In this manner, the dispatching rules can be adjusted according to possible high-risk lots so that most of the production strategies can be satisfied. If all of the lots meet the prescribed production strategies, then the nearest-job-first rule can be used to offer higher transport efficiency. In addition, the proposed vehicle dispatcher is also capable of deadlock-free operation, collision avoidance, and blockage prevention. Finally, this paper uses AutoMod simulation software to construct and evaluate the manufacturing models. By evaluating the simulation results, the proposed intelligent multimission-oriented vehicle dispatcher performs better performance than the others, and all of the production strategies are satisfied .     

Dynamic dispatching for a flexible manufacturing system based on fuzzy logic

Variables in the production environment inevitably result in deviations from the generated schedules. These variables affecting the system performance should be considered when dealing with dynamic dispatching problems. In addition, determination of the dispatching rules based on a single performance criterion cannot satisfy the requirements of different production performances. In this research, a dynamic dispatching strategy for multiple performance measures based on fuzzy inference is proposed. First, the variables affecting the system performance are identified. Then, the fuzzy membership functions and the fuzzy inference rules are established based on the simulation data. According to the statuses of environment variables, the fuzzy inference is performed to find an appropriate dispatching rule at each decision point to meet the best multiple performance measures. An example of the application is presented. The simulation results indicate that the proposed fuzzy-based dynamic dispatching strategy has a very good and robust performance.     

Multicriteria dynamic scheduling by swapping of dispatching rules

For most shop floors, consideration of more than one criterion would be likely to provide more realistic scheduling of a given set of jobs. The present paper considers this aspect of scheduling and uses an algorithm proposed by the authors in their previous work for implementing several criteria simultaneously in a shop of dynamic nature. The algorithm considers several dispatching rules simultaneously for selecting a job for processing and continuously monitors the attained values of performance measures. The selection of dispatching rules is made by identifying the worst performing criterion. A rule that can improve system performance for the worst-performing criterion is selected to dispatch the part under consideration. In this paper, several case studies have been attempted to evaluate the efficiency of the algorithm. The results of the taken case studies indicate that in a dynamic system the system performance improves by changing the dispatching rules corresponding to the worst-performance criterion at the appropriate deterioration in the performance measures.     

电网调度专业语料库构建方法研究及应用

针对调控领域缺乏调度专业语料库导致语音识别准确率较低的问题,提出一种基于自然语言处理和人工智能技术的电网调度专业语料库构建方法。面对结构形式多样的调控语料,提出不同方法建立调度专业语料识别模型;基于规则蒙版识别数据库和文档表格中调度专业实体,采用实体识别和关系抽取技术识别调控文本中调度专业实体和事件;通过梳理调度员操作意图生成调度指令实体,将上述方式获得实体和事件汇集形成调度专业语料库。通过某调控中心语料验证,所建立调度专业语料库能够提升语音识别准确率,具有较强实用性。     

基于仿真的生产线控制规则性能评估技术研究

综合考虑了工件的加工时间、到达率和交货期等随机因素，仿真分析了不同故障率下调度规则和路径选择规则组合的性能，并给出了每种性能评价指标下最优的规则组合。另外，在动态生产环境中，为了支持快速仿真分析，提出了基于建模模板的仿真建模方法。该方法以建模元素和仿真控制逻辑分离的原则为指导，采用面向对象仿真建模技术，构建面向生产线的过程控制模型，实现控制模型的模块化，提高了模型的可重用性和可扩展性。     

Information-Based Dynamic Manufacturing System Scheduling

Information about the state of the system is of paramount importance in determining the dynamics underlying manufacturing systems. In this paper, we present an adaptive scheduling policy for dynamic manufacturing system scheduling using information obtained from snapshots of the system at various points in time. Specifically, the framework presented allows for information-based dynamic scheduling where information collected about the system is used to (1) adjust appropriate parameters in the system and (2) search or optimize using genetic algorithms. The main feature of this policy is that it tailors the dispatching rule to be used at a given point in time to the prevailing state of the system. Experimental studies indicate the superiority of the suggested approach over the alternative approach involving the repeated application of a single dispatching rule for randomly generated test problems as well as a real system. In pa ticular, its relative performance improves further when there are frequent disruptions and when disruptions are caused by the introduction of tight due date jobs and machine breakdown—two of the most common sources of disruption in most manufacturing systems. From an operational perspective, the most important characteristics of the pattern-directed scheduling approach are its ability to incorporate the idiosyncratic characteristics of the given system into the dispatching rule selection process and its ability to refine itself incrementally on a continual basis by taking new system parameters into account.     

协作制造环境下的多Agent生产控制框架

构建了一个基于多Agent的协作生产控制框架，框架通过应用自治Agent和分布式决策的权重函数，在协作制造环境中制造实体间或实体内进行生产调度与控制，同时Agent之间应用简单指标值而不是详细数据进行信息交换，框架通过动态分配／调整子装配的优先权来适应系统的突发事件，从而降低了订单的提前／延期惩罚。