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。     

Near optimal manufacturing flow controller design

Flow control of flexible manufacturing systems (FMSs) addresses an important real-time scheduling requirement of modern manufacturing facilities, which are prone to failures and other controllable or stochastic discrete events affecting production capacity, such as change of setup and maintenance scheduling. Flow controllers are useful both in the coordination of interconnected flexible manufacturing cells through distributed scheduling policies and in the hierarchical decomposition of the planning and scheduling problem of complex manufacturing systems. Optimal flow-control policies are hedging-point policies characterized by a generally intractable system of stochastic partial differential equations. This article proposes a near optimal controller whose design is computationally feasible for realistic-size systems. The design exploits a decomposition of the multiple-part-type problem to many analytically tractable one-part-type problems. The decomposition is achieved by replacing the polyhedra production capacity sets with inscribed hypercubes. Stationary marginal densities of state variables are computed iteratively for successive trial controller designs until the best inscribed hypercubes and the associated optimal hedging points are determined. Computational results are presented for an illustrative example of a failureprone FMS.     

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.     

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。     

Object-oriented approach of MCTPN for modelling Flexible manufacturing systems

Manufacturing industry is facing a stricter challenge than ever before owing to the rapid change in market requirements. Flexible manufacturing systems (FMSs) have a much greater capability than traditional fixed-type production systems for coping with the rapid change. In this paper, a modified coloured-timed Petri net (MCTPN) is developed to model the dynamic activities in an FMS. The MCTPN provides an object-oriented and modular method of modelling manufacturing activities. It includes colour, time, modular and communication attributes. The features of object-oriented modelling allow the FMS to be modelled with the properties of classes, objects, and container trees. Since the system activities can be encapsulated and modularised by the proposed MCTPN, the manufacturing systems can be easily constructed and investigated by the system developers. It makes the concept of software IC possible for modelling complex FMSs. Once all of the MCTPN objects are well defined, the developers need to consider only the interfaces and operations relating to the MCTPN objects. In order to demonstrate the capability of the proposed MCTPN, the FMS in the Manufacturing Automation Technology Research Center (MATRC) of the National Taiwan University will be stimulated and justified by using the proposed MCTPN along with the G2 expert system.     

Object-oriented graphical modeling of FMSs

Presented in the article is a method for constructing a graphical model of an FMS by using a new modeling tool called JR-net (Job Resource relation-net). JR-net is an object-oriented graphical tool for modeling automated manufacturing systems (AMSs), such as FMSs, FASs, and AS/RSs. As with the object-oriented modeling paradigm of Rumbaugh et al. (1991), the JR-net modeling framework supports the three stages of models: static layout model (object model); job flow model (functional model); and supervisory control model (dynamic model). In this article, the existing JR-net structure (Park 1992, Han et al., 1995) is extended further to make it a graphical tool for FMS modeling. Using the extended JR-net, a step-by-step procedure for constructing a graphical model of FMSs is presented. Also addressed are issues of classifying FMSs in terms of their generic functions and of utilizing the JR-net model of FMSs.     

The control of a flexible manufacturing system by short-term goal identification

The control of manufacturing systems is characterised by the need to make a compromise between conflicting goals. Traditional research concentrates on steady-state optimisation of single objectives that are not necessarily relevant to decision making in a production environment. The advent of flexible manufacturing systems (FMSs) with automated material handling and limited buffer space highlights the need to provide computationally-efficient solutions to work out scheduling and dispatch problems for real-time applications. The authors have adopted a knowledge-based approach to achieve effective real-time FMS control. In the context of the current system status and planned system activities, short-term goals are identified which lead to appropriate jobdispatch decisions. This approach has been implemented in a prototype control system written in Prolog. To obtain knowledge in this area of scarce expertise, a “define-build-learn” cycle was adopted. First, functional concepts are defined and built into the control system, then the corresponding system characteristics are studied and the results used for further cycles of concept definition and building. This paper describes the development of this operational system.     

A case study in FMS production planning and dispatching

The speedy development and extensive application of computers have helped play a significant role in a new technological revolution. The importance of FMS flexibility in producing a variety of products and adapting rapidly to customer requirements makes FMSs attractive. Further, FMSs are most appropriate for largevariety and medium- to high-volume production environments. However, the module of the FMS production planning system is not perfect. This paper focuses on a new scheme for FMS production planning and dispatching under the realistic assumptions promoted by a particular flexible manufacturing factory. Some practical constraints such as fixture uniqueness, limited tool magazine capacity, and a given number of pallets are considered. The simulation results indicate that the scheme provides a good production plan, according to the short-term plans from the MIS Department. Some conclusions are drawn and a discussion is presented.     

A pattern-directed approach to flexible manufacturing: A framework for intelligent scheduling, learning, and control

The planning, scheduling, and control of manufacturing systems can all be viewed as problem-solving activities. In flexible manufacturing systems (FMSs), the computer program carrying out these problem-solving activities must additionally be able to handle the shorter lead time, the flexibility of job routing, the multiprocessing environment, the dynamic changing states, and the versatility of machines. This article presents an artificial intelligence (AI) method to perform manufacturing problem solving. Since the method is driven by manufacturing scenarios represented by symbolic patterns, it is referred to as pattern-directed. The method is based on three AI techniques. The first is the pattern-directed inference technique to capture the dynamic nature of FMSs. The second is the nonlinear planning technique to construct schedules and assign resources. The third is the inductive learning method to generate the pattern-directed heuristics. This article focuses on solving the FMS scheduling problem.In addition, this article reports the computation results to evaluate the utility of various heuristic functions, to identify important design parameters, and to analyze the resulting computational performance in using the pattern-directed approach for manufacturing problem-solving tasks such as scheduling.     

Design Guidelines for Deadlock-Handling Strategies in Flexible Manufacturing Systems

Deadlock-free operation of flexible manufacturing systems (FMSs) is an important goal of manufacturing systems control research. In this work, we develop the criteria that real-time FMS deadlock-handling strategies must satisfy. These criteria are based on a digraph representation of the FMS state space. Control policies for deadlock-free operation are characterized as partitioning cuts on this digraph. We call these structural control policies (SCPs) because, to avoid deadlock, they must guarantee certain structural properties of the subdigraph containing the empty state; namely, that it is strongly connected. A policy providing this guarantee is referred to as correct. Furthermore, an SCP must be configurable and scalable; that is, its correctness must not depend on configuration-specific system characteristics and it must remain computationally tractable as the FMS grows in size. Finally, an SCP must be efficient; that is, it must not overly constrain FMS operation. We formally develop and define these criteria, formulate guidelines for developing policies satisfying these criteria, and then provide an example SCP development using these guidelines. Finally, we present an SCP that guarantees deadlock-free buffer space allocation for FMSs with no route restrictions.     

RDCAPP: A real-time dynamic CAPP system for an FMS

Computer-aided process planning (CAPP) systems need to consider the uncertain nature of the shop-floor prior to the identification of job routes and processing sequences. This paper describes the design and development of a prototype, real-time dynamic CAPP (RDCAPP) system for a multimachining-centre flexible manufacturing system (FMS). Concepts relevant to this research include CAPP, profile input using group technology (GT), artificial-intelligence-based expert systems, and FMSs.RDCAPP considers facility characteristics, machine capacity and the current shop-floor conditions prior to developing a process plan Input to the system is through a GT code and additional auxiliary interactive inputs. RDCAPP uses uncertainty management techniques to keep track of and adapt to changes in shop-floor status. The paper discusses the architecture of RDCAPP in detail. The system was tested rigorously and its outputs validated. Ideas for future research are presented.     

A Decentralized Approach to Estimate Activity-Based Costs and Near-Optimal Resource Allocation in Flexible Manufacturing Systems

Flexible manufacturing systems (FMSs) can apply the efficiencies of large-scale production to small batch production. The coordination of FMS activities is a complex task; this paper presents a decentralized pricing mechanism that can be used to estimate the activity–based costs and manage the activities of the FMS efficiently. The pricing mechanism described in this paper does not require systemwide information to compute prices; instead, the pricing mechanism samples and uses the demand information at each CNC machine to compute rental prices at that machine. We derive the theoretical formula for rental prices supporting the optimal performance and propose simulation studies to estimate the rental prices for real-time price changes in a decentralized manner. Results from a preliminary simulation study indicate that stable rental prices can be estimated and significant improvements can be realized by using the pricing mechanism.     

Reliability analysis of flexible manufacturing systems

High productivity is the primary goal of flexible manufacturing systems (FMSs) in which semi-independent workstations are integrated using automated material-transport systems and hierarchical local networks. Availability of various subsystems and of the system as a whole is a prerequisite for achieving functional integration as well as high throughput. An FMS also has inherent routing and operation flexibilities that provide it with a certain degree of fault tolerance. A certain volume of production can thus be maintained in the face of subsystem (i.e., machines, robots, material handling system, etc.) failures. In this article, we propose two reliability measures, namely, part reliability (PR) and FMS reliability (FMSR) for manufacturing systems and present algorithms to evaluate them. We also consider the dynamic or time-dependent reliability analysis as a natural generalization of the static analysis. The methods outlined use an algorithm that generates process-spanning graphs (PSGs), which are used to evaluate the reliability measures.     

一种基于Petri网的顺序共享资源AMS＊s

Ｐｅｔｒｉ网控制器自动设计及控制程序自动生成方法的研究是自动制造系统ＡＭＳｓ和柔性制造系统ＦＭＳｓ领域研究的热点问题之一〔２～６〕。本文以ＡＭＳｓ计划和调度产生的生产序列ＰＳ和资源需求序列ＲＲＳ为基础，为顺序共资源ＡＭＳｓ设计了一种规格说明语言，以自动生成ＡＭＳｓＰｅｔｒｉ网模型的矩阵形式，并给出了转换步骤。由于引入了资源状态反馈，故生成的Ｐｅｔｒｉ网模型是无死锁的。最后，用一个实例说明了设计过程。     

A distributed knowledge-based approach to flexible automation: The contract net framework

This article applied distributed artificial intelligence to the real-time planning and control of flexible manufacturing systems (FMS) consisting of asynchronous manufacturing cells. A knowledge-based approach is used to determine the course of action, resource sharing, and processor assignments. Within each cell there is an embedded automatic planning system that executes dynamic scheduling and supervises manufacturing operations. Because of the decentralized control, real-time task assignments are carried out by a negotiation process among cell hosts. The negotiation process is modeled by augmented Petri nets —the combination of production rules and Petri nets—and is excuted by a distributed, rule-based algorithm.     

The State of the Art in Simulation Study on FMS Scheduling: A Comprehensive Survey

Scheduling of flexible manufacturing systems (FMSs) has been one of the most attractive areas for both researchers and practitioners. A considerable body of literature has accumulated in this area since the late 1970s when the first batch of papers was published. A number of approaches have been adopted to schedule FMSs, including simulation techniques and analytical methods. Numerous articles can be found on each of these approaches. This paper reviews scheduling studies of FMSs which employ simulation techniques as an analysis tool, since simulation is the most widely used tool for modelling FMSs. Scheduling methodologies are categorised into simulation of general scheduling studies, multi-criteria scheduling approaches, and artificial intelligence (AI) approaches in FMSs. Comments on the publications, and suggestions for further research and development are given.     

Simulation for maintenance of an FMS: an integrated system of maintenance and decision-making

Flexible manufacturing systems (FMSs) are designed to produce a variety of different part types with high machine utilisation, so the maintenance technique is necessary and very important in an FMS. This paper discusses the maintenance problem in an FMS and its simulation, analyses the maintainability of a real FMS shop, and presents the architecture of an integrated system of maintenance and decision-making/scheduling for manufacturing shop control. The modelling and simulation of the maintenance activities in the shop are shown. The simulation program is written in SLAM II and the special subroutines are realised in Fortran. The interest is directed towards the use of the method of simulation for maintenance and decision-making in FMSs.     

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。     

An Analytical Queueing Network Model for Flexible Manufacturing Systems with a Discrete Handling Device and Transfer Blockings

In this paper, we study job shop-like flexible manufacturing systems (FMSs) with a discrete material handling system (MHS). In such FMSs, the MHS is a critical device, the unavailability of which may induce transfer blockings of the machines. The FMS devices therefore are hierarchically structured into primary and secondary devices to manage such blocking and avoid deadlocks in these FMSs.For evaluating the quantitative steady-state performance of such FMSs, we propose an analytical queueing network model that relies on an approximate method proposed for analyzing computer systems with simultaneous possessions of resources. Such a model is obtained using the concept of passive resources and by aggregating the FMS workload data so that models are much more tractable.The analytical results are validated against discrete event simulation and shown to be very encouraging. We also show how to increase their robustness, especially under light workload conditions, by modifying an assumption of the method concerning service time distributions.     

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.