满足产品需求条件下的车间最优随机生产计划与控制

根据实际需要建立关联方程有延迟且以正好满足产品需求为约束条件的车间生产计划与控制的随机非线性规划模型，即一种求解动态优化问题的静态优化模型，为求解方便将其转化成线性规划模型。提出分别用卡马卡算法和基于卡马卡算法的关联预测法来求解柔性自动化车间（FAM）最优随机生产计划与控制问题，并编制了相应软件。通过算例研究，比较了上述2种方法和Matlab中的线性规划法，结果表明所提方法非常适合将不确定性环境中的FAW产品需求计划最优分解成由FAW中各柔性制造系统（FMS）执行的短期随机计划，尤其适合FMS之间工件传输需经出入库并有1个生产周期延迟的情况。     

敏捷制造环境中车间的随机生产计划方法

研究了敏感制造环境下柔性自动化车间的髹机生产计划方法。     

机械加工车间动态生产计划与控制系统设计

介绍了制造型企业机械加工车间动态生产计划与控制系统开发的主要任务,分析了整个系统在结构设计、数据库集成以及机械加工过程中的功能控制,结果表明运用该系统能够有效地减少机械加工车间调度的任务量,提高车间管理者对工时定额的有效控制。     

JIT柔性混合流水车间生产调度问题研究

针对混合柔性流水车间多种工艺路线的生产调度问题,分析了生产工艺计划与车问调度系统的集成原理,建立目标模型,通过将简单遗传算法加以改进,在建立集成模型的基础上,对算法进行研究,把进化后的遗传算法（SGA）和改进的模拟退火算法（SA）有机结合,使算法优化机制融合和优化结构互补,形成较为高效的混合优化算法,并对问题进行求解。最后给出了一个具体算例,验证算法的有效性和先进性。     

基于产能柔性的装饰布企业生产计划模型构建

针对装饰布企业生产特点及存在的问题，探讨了提高装饰布企业产能柔性方法，建立了面向产能柔性的装饰布企业生产计划模型，并给出了遗传算法的具体求解步骤。     

基于产能柔性的装饰布企业生产计划模型构建

针对装饰布企业生产特点及存在的问题,探讨了提高装饰布企业产能柔性方法,建立了面向产能柔性的装饰布企业生产计划模型,并给出了遗传算法的具体求解步骤。     

柔性流水车间设备利用率排产优化问题研究

针对具有工序约束信息的柔性流水车间的设备利用率优化问题,提出利用PSODE混合算法来解决该问题,全局优化过程采用群体优化算法,在局部优化过程中通过上下道关联工序约束信息来控制工件的分配,将并行工位总设备利用率作为适应度函数,构建了具有关联工序约束的柔性流水车间生产调度模型,确定生产工件的加工路径、加工顺序、开工时间和完工时间。通过多组方案数值计算结果对比分析,验证了PSODE算法解决柔性流水车间设备利用率优化问题的有效性。     

灵活的模具车间自动化生产

Rexam公司生产的新型MegaCell产品旨在最大限度地以它的全自动模式实现无人值守的模具镶件和电极生产,并且能够很容易地转换成手动模式以适应“自定义”工作。     

基于现场总线的柔性自动化液压车间

通过构建现场总线控制系统——柔性自动化液压车间实例,显示采用PROFIBUS现场总线技术,具有信息一体化和控制经济化的特点.通过从底层现场设备层控制到高层工厂管理自动化系统的构建实例,无论总体设计、硬件配置、软件设计,现场总线控制系统相对传统的中央控制网络系统和集散控制系统,都显示出全面性能和高度可靠.     

面向产能柔性的综合生产计划模型研究

在阐述产能柔性概念的基础上,分析了影响产能柔性的因素及其能力构成,进而以生产成本、库存成本以及非柔性成本最小化建立了综合生产计划优化模型,最后采用遗传算法予以求解,并通过实例仿真证明了模型和算法的有效性和可行性。     

Production Capacity of Flexible Manufacturing Systems with Fixed Production Ratios

Determining the production capacity of flexible manufacturing systems is a very important issue in the design of such systems. We propose an approach for determining the production capacity (i.e., the maximum production rate) of a flexible manufacturing system with several part types, dedicated pallets, and fixed production ratios among the different part types. We show that the problem reduces to the determination of a single parameter for which we propose an iterative procedure. Simulation or approximate analytical techniques can be used as the building block performance evaluation technique in the iterative procedure.     

Hierarchical Production Planning in Flexible Automated Workshops with Delay Interaction

This paper addresses the hierarchical production planning (HPP) problem for flexible automated workshops (FAWs) with delay interaction, each with a number of flexible manufacturing systems (FMSs). The delay interaction aspect arises from taking into consideration the transfer of parts between FMSs. Any job which requires processing on more than one FMS cannot be transferred directly from one FMS to the next. Instead a semi-finished-product completed in one period must be put into shop storage until the next period at which it can be transferred to the next FMS for further processing. The objective is to decompose medium-term plans (assigned to an FAW by ERP/MRP II) into short-term plans (to be executed by FMSs in the FAW) so as to obtain the lowest production cost. The HPP problem is formulated in this paper by a nonlinear programming model whose constraints are linear but whose objective function is piecewise linear. For the convenience of solving the nonlinear programming model, it is transformed into a linear programming model. Because the model for a general workshop is too large to be solved by the simplex method on a personal computer within acceptable time, Karmarkar’s algorithm and an interaction/prediction algorithm, respectively, are used to solve the model, the former for medium- or small-scale problems and the latter for large-scale problems. With the implementations of these algorithms and with many HPP examples, Karmarkar’s algorithm, the interaction/prediction algorithm and the linear programming method in Matlab 5.0 are compared, showing that the proposed approaches are very effective.     

Towards an Integration of Process Planning and Production Planning and Control for Flexible Manufacturing Systems

This introduction article attempts to present some major issues relating to the integration of process planning and production planning and control (PPC) for flexible manufacturing systems (FMSs). It shows that the performance of an FMS can be significantly improved and FMS capabilities more effectively utilized by integrating process planning and PPC functions. The various types of flexibility to be planned and provided for in process planning and manufacturing are summarized in the article, as well as emerging conceptual frameworks for integration, along with their implementation requirements and problems. Distinctive elements that differentiate these frameworks, such as the extent of integration of process planning and PPC activities, number of alternative process plans, and the time at which numerical control programs are generated, are discussed, followed by a brief summary of the articles compiled for this special issue.     

Optimal Method of Capacitated Lot-Sizing Planning in Manufacturing Systems

This paper analyzes the capacitated lot-sizing problem considering an individual machine’s production capacity using a two-layer hierarchical method to minimize the sum of the dynamic inventory cost and the overtime penalty cost. The genetic algorithm, the parameter linear programming method, and a heuristic method were used in the developed method. The method uses the genetic operator to define the lot-sizing matrix (the first layer), linear programming to determine each machine's schedule (the second layer) according to the lot-sizing matrix, and the heuristic method to verify the feasibility of the solutions by adjusting them to meet the constraint requirements. The scheduling of machines in a press shop demonstrates the effectiveness of the algorithm. The result shows that the algorithm is convergent. Translated from J. Tsinghua Univ. (Sci. Tech.), 2004, 44(5)     

A Generic Model to Solve Tactical Planning Problems in Flexible Manufacturing Systems

This paper is an attempt to develop a generic modeling framework that addresses tactical planning problems of flexible manufacturing systems in a coherent manner. We propose a generic 0-1 mixed integer programming formulation, that integrates batching, loading, and routing problems with their critical aspects related to a system's performance. For this purpose, a thorough analysis is made to determine and relate system components, their attributes, and alternatives together with performance measures specific to tactical planning. This provided the justification to support our argument about generality of the model. A linear programming formulation is provided to approximate the mixed integer formulation proposed so as to overcome the problem's combinatorial complexity. The potential capability of the linear approximation proposed also is demonstrated via a small set of test problems.     

面向半导体生产线生产计划的混合智能算法研究

针对传统半导体企业生产计划优化方法不能体现市场和生产环境中不确定性的不足,将模糊机会约束规划应用于半导体生产计划优化模型的建立,通过结合了模糊模拟和遗传算法的混合智能算法对半导体企业生产计划进行求解并通过实例及验证来说明该方法的可行性和有效性。     

Integrating Flexible Process Plans with Scheduling in Flexible Manufacturing Systems

This paper highlights the importance of integration between process planning and scheduling in flexible manufacturing systems (FMS). An effective integration increases the potential for enhanced system performance and enhanced decision making A framework that integrates flexible process plans with off-line (predictive) scheduling in FMS is presented. The flexibility in process planning, including process flexibility, sequence flexibility, and alternative machine tools, is discussed. The proposed framework consists of four integrated stages with the objective of reducing the completion time. The integrated stages include: 1. Machine tool selection. 2. Process plan selection. 3. Scheduling. 4. Re-scheduling modules. In addition, the paper proposes a new approach, namely the Dissimilarity Maximisation Method (DMM), for selecting the appropriate process plans for a part mix where parts have alternative process plans. The recursive structure of the framework provides a different approach, namely overlapping schedules, which considers a longer scheduling period as comprising several short scheduling periods. Knowing that neither the process plans nor the planned (predicted) schedules are truly followed on the shop floor, the related literature and the corresponding approaches are compared in order to envisage new approaches for closing the gap between process planning and scheduling.     

A Dynamic Tool Requirement Planning Model for Flexible Manufacturing Systems

Despite their strategic potential, tool management issues in flexible manufacturing systems (FMSs) have received little attention in the literature. Nonavailability of tools in FMSs cuts at the very root of the strategic goals for which such systems are designed. Specifically, the capability of FMSs to economically produce customized products (flexibility of scope) in varying batch sizes (flexibility of volume) and delivering them on an accelerated schedule (market response time) is seriously hampered when required tools are not available at the time needed. On the other hand, excess inventory of tools in such systems represents a significant cost due to the expensive nature of FMS tool inventory. This article constructs a dynamic tool requirement planning (DTRP) model for an FMS tool planning operation that allows dynamic determination of the optimal tool replenishments at the beginning of each arbitrary, managerially convenient, discrete time period. The analysis presented in the article consists of two distinct phases: In the first phase, tool demand distributions are obtained using information from manufacturing production plans (such as master production schedule (MPS) and material requirement plans (MRP)) and general tool life distributions fitted on actual time-to-failure data. Significant computational reductions are obtained if the tool failure data follow a Weibull or Gamma distribution. In the second phase, results from classical dynamic inventory models are modified to obtain optimal tool replenishment policies that permit compliance with such FMS-specific constraints as limited tool storage capacity and part/tool service levels. An implementation plan is included.