柔性制造系统中的运输机械

论述了柔性制造系统中使用的有轨和无轨自动输送车的特点、结构、功能及控制系统。     

Dispatching, routing, and scheduling of two automated guided vehicles in a flexible manufacturing system

This article presents a new approach for planning the dispatching, conflict-free routing, and scheduling of automated guided vehicles in a flexible manufacturing system. The problem is solved optimally in an integrated manner, contrary to the traditional approach in which the problem is decomposed in three steps that are solved sequentially. The algorithm is based on dynamic programming and is solved on a rolling time horizon. Three dominance criteria are used to limit the size of the state space. The method finds the transportation plan minimizing the makespan (the completion time for all the tasks). Various results are discussed. A heuristic version of the algorithm is also proposed for an extension of the method to many vehicles.     

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

A decision-making approach to the operation of flexible manufacturing systems

This paper introduces a generic decision-making framework for assigning resources of a manufacturing system to production tasks. Resources are broadly defined production units, such as machines, human operators, or material handling vehicles; and tasks are activities performed by resources. In the specific context of FMS, resources correspond to individual machines; tasks correspond to operations to be performed on parts. The framework assumes a hierarchical structure of the system and calls for the execution of four consecutive steps to make a decision for the assignment of a resource to a task. These steps are 1) establishment of decision-making criteria, 2) formation of alternative assignments, 3) estimation of the consequences of the assignments, and 4) selection of the best alternative assignment. This framework has been applied to an existing FMS as an operational policy that decides what task will be executed on which resource of this FMS. Simulation runs provide some initial results of the application of this policy. It is shown that the policy provides flexibility in terms of system performance and computational effort.     

Analysis of the number of automated guided vehicles required in flexible manufacturing systems

In this paper we examine some of the general principles and analysis methods that are used to design an automated material handling system. The paper focuses on one type of automated handling system that seems especially suitable for automation in discrete-product manufacturing. These types of automated handling systems are called automated guided vehicle systems. These systems are most applicable for the automation of low-and medium-volume handling situations, where the routeing of materials is more individualised. For guided vehicles, a new quantitative method for analysing these systems is developed in the paper. Examples are presented to demonstrate the method.     

Developing a computer control system for a flexible manufacturing cell

This article focuses on the development of a computer control system for a flexible manufacturing cell. The paper outlines the various modules that are required for a computer control system and elaborates on the development of some of these modules. This is part of an ongoing research project at the University of the Witwatersrand. The aim of the project is to demonstrate the viability of flexible manufacturing systems to South African industry. Thus the main constraints of the project were cost, ease of implementation, and ease of maintainability. This necessitated the use of existing machinery and of computer systems and software that were readily available and already familiar to industry.     

基于 Petri网的柔性制造系统动态优化模型

为解决柔性制造系统的动态优化调度问题,在基于扩展高级全局决策Petri网的柔性制造系统优化模型的基础上,提出了实时一优化切换控制Petri网模型。该模型在柔性制造系统发生加工设备故障、急件插入等异常情况时,自动切换并运行全局优化调度算法,并在系统允许的时间范围内,再切换返回到原有系统状态,按照新的优化结果运行。最后,以实时一优化切换控制Petri网模型与基于遗传的最小平衡算法结合为例,证实了该模型是有效的。     

Scheduling algorithms for a two-machine flexible manufacturing system

The flexible manufacturing system (FMS) considered in this paper is composed of two CNC machines working in series—a punching machine and a bending machine connected through rollers acting as a buffer system of finite capacity. The main difference between the present problem and the standard two-machine flow shop problem with finite intermediate capacity is precisely the buffer system, which in our problem consists of two stacks of parts supported by rollers: the first stack contains the output of the punching machine, while the second stack contains the input for the bending machine. When the second stack is empty, the first stack may be moved over. Furthermore, the capacity of each stack depends on the particular part type being processed.The FMS can manufacture a wide range of parts of different types. Processing times on the two machines are usually different so that an unbalance results in their total workload. Furthermore, whenever there is a change of the part type in production, the machines must be properly reset—that is, some tools need to be changed or repositioned.A second important difference between the present problem and the usual two-machine flow shop problem is the objective. Given a list ofp part types to be produced in known quantities, the problem considered here is how to sequence or alternate the production of the required part types so as to achieve various hierarchical targets: minimize the makespan (the total time needed to complete production) and, for instance, compress the idle periods of the machine with less workload into a few long enough intervals that could be utilized for maintenance or other reasons.Although Johnson's rule is optimal in some particular cases, the problem addressed in the paper isNP-hard in general: heuristic procedures are therefore provided.     

Rule-based production planning in flexible manufacturing systems

Production planning in flexible manufacturing may require the solution of a large-scale discrete-event dynamic stochastic optimization problem, due to the complexity of the system to be optimized, and to the occurrence of discrete events (new orders and hard failures). The production planning problem is here approached for a multistage multipart-type manufacturing shop, where each work cell can share its processing time among the different types of parts. The solution of this problem is obtained by an open-loop-feedback control strategy, updated each time a new event occurs. At each event time, two coupled problems are solved: 1) a product-order scheduling problem, conditioned on estimated values of the production capacities of all component work cells; and 2) a production-capacity planning problem, conditioned on predefined sequences of the product orders to be processed. In particular, the article aims at defining a production planning procedure that integrates both analytical tools, derived from mathematical programming, and knowledge-based rules, coming from experience. The objective is to formulate a hybrid (knowledge-based/analytical) planning architecture, and to analyze its use for multicell multipart-type manufacturing systems.     

Batch sizes and lead-time performance in flexible manufacturing systems

Production lead-time performance in flexible manufacturing systems is influenced by several factors which include: machine groupings, demand rates, machine processing rates, product batching, material handling system capacity, and so on. Hence, control of lead-time performance can be affected through the manipulation of one or more of these variables. In this article, we investigate the potential of batch sizing as a control variable for lead-time performance through the use of a queueing network model. We establish a functional relationship between the two variables, and incorporate the relationship in an optimization model to determine the optimal batch size(s) which minimizes the sum of annual work-in-process inventory and final inventory costs. The nonlinear batch sizing problem which results is solved by discrete optimization via marginal analysis. Results show that batch sizing can be a cheap and effective variable for controlling flexible manufacturing system throughput.     

Evaluating the design of flexible manufacturing systems

Evaluating the design of flexible manufacturing systems is complex. Developing a measure of performance useful for evaluating alternate designs continues to be interesting. Here, total productivity of the system is proposed as an appropriate measure. Specification of parameters based upon strategic considerations for this measure are discussed. Finally, the usefulness of the measure is demonstrated through an example.     

The Effects of Scheduling Rules and Routing Flexibility on the Performance of a Random Flexible Manufacturing System

The increased use of flexible manufacturing systems to efficiently provide customers with diversified products has created a significant set of operational challenges for managers. Many issues concerning procedures and policies for the day-to-day operation of these systems still are unresolved. Previous studies in this area have concentrated on various problems by isolating or simplifying the systems under study. The primary objective of this study is to extend previous research by examining the effects of scheduling rules and routing flexibility on the performance of a constrained, random flexible manufacturing system (FMS). Other experimental factors considered are shop load, shop configuration, and system breakdowns. Within the bounds of this experiment, the results indicate that, in the presence of total routing flexibility, the effects of shop load, system breakdowns, and scheduling rules are significantly dampened. In particular, when total routing flexibility exists, the choice of scheduling rules is not critical. We also show that the behavior of scheduling rules in a more constrained FMS environment (i.e., where system breakdowns occur and material handling capability is limited) is consistent with the findings of previous research conducted under less constrained environments. Finally, results indicate that the shop configuration factor has little or no impact on a system's flow-time performance.     

Real-time scheduling with deadlock avoidance in flexible manufacturing systems

The dynamic nature of manufacturing makes rescheduling essential in today's complex production environment, particularly in flexible and re-configurable systems. Research on optimising schedules, which includes deadlock avoidance, is rather limited. Furthermore, the deadlock problem is mostly ignored in research on rescheduling. A rescheduling algorithm, that uses time petri-nets and the minimal siphons concept, was developed to deal with sources of disturbance such as machine breakdowns in real-time. The algorithm guarantees a deadlock-free new schedule. The existence of alternative routes, availability of material handling facilities and the limitation of buffer capacities were taken into consideration. The developed algorithm modifies only the affected portion of the original schedule, rather than rescheduling all jobs, in order to limit changes to the original schedule and reduce the impact on the response time.The effect of flexible routing, machine breakdowns, machine downtime, routing criterion and the use of the dispatching rule on the performance of manufacturing systems was studied. The systems performance was measured by the average flow time, the makespan and the average machine utilisation. The results indicate that utilising the system routing flexibility in real-time rescheduling, while avoiding deadlocks, improves system performance. Moreover, routing the interrupted operation to an alternative machine, based on the minimum expected completion time rather than the least utilised machine criterion, resulted in better performance.     

模糊柔性制造系统的混杂Petri网建模与调度

对模糊柔性制造系统的建模和调度进行了研究.定义了一种具有模糊区间速率的混杂Petri网模型,提出了模型的迁移使能和迁移引发语义,定义了弱使能迁移的模糊使能规则,给出了模型动态演变算法.建立了模糊柔性制造系统调度的模糊线性规划模型,并对典型的工业实例进行了分析.研究结果表明,基于所定义的混杂Petri模型能够有效地描述和分析模糊柔性制造系统.     

柔性装配制造系统中生产优化的Petri网方法

本文在基本Ｐｅｔｒｉ网的基础上,给出了一种进行周期性生产的柔性装配制造系统的模型;同时,针对该系统,给出了一个求稳定需求下最佳生产指量的启发式调度方法。     

Multiple-Objective Scheduling for the Hierarchical Control of Flexible Manufacturing Systems

This paper presents a hierarchical approach to scheduling flexible manufacturing systems (FMSs) that pursues multiple performance objectives and considers the process flexibility of incorporating alternative process plans and resources for the required operations. The scheduling problem is solved at two levels: the shop level and the manufacturing system level. The shop level controller employs a combined priority index developed in this research to rank shop production orders in meeting multiple scheduling objectives. To overcome dimensional complexity and keep a low level of work-in-process inventory, the shop controller first selects up to three production orders with the highest ranking as candidates and generates all possible release sequences for them, with or without multitasking. These sequences are conveyed to the manufacturing system controller, who then performs detailed scheduling of the machines in the FMS using a fixed priority heuristic for routing parts of multiple types while considering alternative process plans and resources for the operations. The FMS controller provides feedback to the shop controller with a set of suggested detailed schedules and projected order completion times. On receiving these results, the shop controller further evaluates each candidate schedule using a multiple-objective function and selects the best schedule for execution. This allows multiple performance objectives of an FMS to be achieved by the integrated hierarchical scheduling approach.     

现代桑性制造技术及其发展

通过分析柔性制造系统的关键技术和发展研究方向，展望了现代柔性制造系统的发展趋势，进而阐述了柔性制造系统在先进制造业中的重要作用及其发展的深远意义。     

仿真优化在制造系统生产调度中的研究进展

在阐述了生产调度概念、分类和仿真优化基本原理、方法的基础上,介绍了国内外仿真优化技术在制造系统生产调度中的应用概况、研究成果,并分别进行分析,指出目前制造系统仿真优化研究中存在的问题以及主要发展趋势。     

Tool addition strategies for flexible manufacturing systems

The allocation of tools to machines determines potential part routes in flexible manufacturing systems. Given production requirements and a minimum feasible set of tools, the decision of how to fill vacant slots in tool magazines to maximize routing flexibility is shown to be a minimum cost network flow problem for the cases when routing flexibility is a function of the average workload per tool aggregated over tool types, or of the number of possible routes through the system. A linear programming model is then used to plan a set of routes for each part type so as to minimize either the material handling requirement or the maximum workload on any machine. The impact of these tool addition strategies on the material handling and workload equalization is investigated and computational results presented. The advantage of the overall approach is computational simplicity at each step and the ability to react to dynamic changes.This article is based upon work supported by the National Science Foundation under Grants No. DMC 85–44993 and DDM 92–15432.This work was done by the author while visiting the SIE Department of the University of Arizona.     

柔性制造系统状态监测与故障诊断系统设计

从柔性制造系统（FMS）的故障机理入手,分析研究了FMS状态监测与故障诊断总体框架。建立了监测与故障诊断子系统通用集成化设备与过程状态监控系统,给出了系统体系结构与硬软件组成．提出了该集成系统的一种实现方法。对FMS体系下的故障咨询、知识库管理、外部扩展接口等子系统模块的实现做了剖析。