柔性自动化车间的最优随机生产计划

研究了由多个柔性制造系统组成的柔性自动化车间的最优随机生产计划问题,首先根据实际需要建立车间生产计划的随机非线性规划模型,为求解方便,将其近似转化成确定非线性规划模型,并通过引进约束进一步转化成线性规划模型。由于这种模型规模较大,很难在微机上用单纯形法在可接受的时间内获得其最优解。为此,分别用卡马卡算法和基于卡马卡算法的关联预测法,求解柔性自动化车间最优生产计划问题,并编制了相应软件。最后通过算例研究,比较了卡马卡算法、基于卡马卡算法的关联预测法和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随机产品需求计划,最优分解成由柔性自动化车间中各柔性制造系统执行的短期随机计划。     

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。     

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.     

Scheduling tasks and vehicles in a flexible manufacturing system

Due to their increasing applicability in modern industry, flexible manufacturing systems (FMSs), their design, and their control have been studied extensively in the recent literature. One of the most important issues that has arisen in this context is the FMS scheduling problem. This article is concerned with a new model of an FMS system, motivated by the practical application that takes into account both machine and vehicle scheduling. For the case of a given machine schedule, a simple polynomial-time algorithm is presented that checks the feasibility of a vehicle schedule and constructs it whenever one exists. Then a dynamic programming approach to construct optimal machine and vehicle schedules is proposed. This technique results in a pseudopolynomialtime algorithm for a fixed number of machines.     

Loading problems with tool management in flexible manufacturing systems: A few integer programming models

In automated production systems like flexible manufacturing systems (FMSs), an important issue is to find an adequate workload for each machine for each time period. Many integer linear programming (ILP) models have been proposed to solve the FMS loading problems, but not all of them take tools into account. Those that do not consider tooling are quite unrealistic, especially when setup times are important with respect to processing times. When tool loading has to be handled by the model, the load assignment may have to be changed completely.In this article we consider FMSs with a tool management of the following type: the system works in time periods whose durations are fixed or not; and tools are loaded on the machines at the beginning of each time period and stay there for the whole time period. Tool changes may occur only at the end of each time period when the system is stopped.We present some integer programming models for handling these situations with several types of objectives. Emphasis is laid on the ILP formulations. Computational complexities are discussed.     

Effectiveness of flexible routing control

Flexibility in part process representation and in highly adaptive routing algorithms are two major sources for improvement in the control of flexible manufacturing systems (FMSs). This article reports the investigation of the impact of these two kinds of flexibilities on the performance of the system. We argue that, when feasible, the choices of operations and sequencing of the part process plans should be deferred until detailed knowledge about the real-time factory state is available.To test our ideas, a flexible routing control simulation system (FRCS) was constructed and a programming language for modeling FMS part process plans, control strategies, and environments of the FMS was designed and implemented. In addition, a scheme for implementing flexible process routing called data flow dispatching rule (DFDR) was derived.The simulation results indicate that flexible processing can reduce mean flow time while increasing system throughput and machine utilization. We observed that this form of flexibility makes automatic load balancing of the machines possible. On the other hand, it also makes the control and scheduling process more complicated and calls for new control algorithms.     

Reliability Optimisation of Flexible Manufacturing Systems with Spare Tooling

Tool reliability plays an important role in the performance and justification of flexible manufacturing systems (FMSs). Failure of a single tool can cause downtimes over the entire system. This would cause due dates to be missed and can result in inferior products. Therefore, in order to justify the large capital investment associated with FMSs, the system must perform in a reliable manner to give an acceptable or required rate of return on the investment. In order to arrive at this objective, FMS reliability must be studied at the planning and design stages, tool failures pose a major obstacle to achieving this objective. In this paper, a mathematical model has been developed to determine the spare tooling requirement for the tooling system in an FMS, so that a desired system reliability is achieved and the cost is minimised. The influence of tool sharing on cost, reliability, spares requirement, and tool magazine capacity of the FMS are analysed. The tools and tool transporter are subject to general failure distributions.     

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.     

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.     

Heuristic solution approaches for combined-job sequencing and machine loading problem in flexible manufacturing systems

Job sequencing and machine loading are two vital and interrelated production planning problems in flexible manufacturing systems (FMSs). In this research, attempts have been made to address the combined job sequencing and machine loading problem using minimization of system unbalance and maximization of throughput as objective functions, while satisfying the constraints related to available machining time and tool slots. This research describes two heuristics to deal with the problems. Heuristic I uses predetermined fixed job sequencing rules as inputs for operation allocation decision on machines, whereas heuristic II uses genetic algorithm based approach for simultaneously addressing job sequences and operation machine allocation issues. Performance of these heuristics has been tested on problems representing three different FMS scenarios. Heuristic II (Genetic algorithm based) has been found more efficient and outperformed heuristic I in terms of solution quality.     

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.     

Holonic Concept Based Methodology for Part Routeing on Flexible Manufacturing Systems

A flexible manufacturing system (FMS) is designed to achieve good productivity and low cost. The success of an FMS depends largely on effective production scheduling and control. However, it has been found that current manufacturing scheduling and control algorithms lack the flexibility to handle interruptions or resource breakdowns; hence, system performance drops dramatically and abruptly when interruptions occur. This research develops a computer-simulation-based framework of FMS scheduling and control system using the holonic concept. This framework can maintain stability and flexibility while accommodating system disturbance, increase throughput, reduce part flow-time and work-in-process inventory, and balance workload among identical workstations. The significance of this research is the investigation of an innovative approach to revolutionary advances of control technologies for advanced manufacturing systems, and to the revitalisation of control and scheduling algorithms used by existing FMSs. A case study has been provided to substantiate the effectiveness of this proposed framework.     

Quality control of an unreliable flexible manufacturing system with scrapping and infinite buffer capacity

Manufacturing multiple part types on a flexible manufacturing system (FMS) is increasingly becoming a rule rather than an exception. In such systems, attention has been drawn to the application of zero-defect technologies. However, in practice, this goal has remained elusive and costly. As a result, even though FMSs may be more reliable, producing fewer defective parts, system complexity and more stringent quality standards are rendering quality control in FMSs potentially useful. The goals of this article are threefold. First, we introduce a procedure for measuring and managing the in-process quality control of an FMS, which is described by an Open Queueing Network (OQN), bridging thereby a gap between queueing theory and quality control. Second, by focusing attention on the potential unreliabilities of FMSs, we provide some managerial insights regarding the role, position, and distribution of the quality control effort in an FMS. Finally, we stress the intricate relations between an FMS's operating characteristics and the manufactured quality and its control. Using numerical analyses, we draw some inferences regarding the design of such FMSs when both quality and quantity issues in the FMSs are considered. These simultaneous considerations of quantity and quality flows in an FMS have not been previously considered in the study of FMSs.     

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.     

XPN-FMS: A CAD tool for FMS modeling, analysis, animation, and simulation using Petri nets and X window

We propose a CAD tool, XPN-FMS, which is primarily based on a unique Petri net (PN) synthesis method, called the knitting technique, developed by the authors. Petri net theory has been applied to specification, validation, performance analysis, control code generation, and simulation for manufacturing systems. The analysis of flexible manufacturing systems (FMSs) based on PNs suffers from the complexity problem of reachability analysis (Peterson, 1981). CAD tools are urgently needed. There is no existing CAD tool for FMSs as comprehensive as XPN-FMS, in the sense that the latter integrates the functions of drawing, analysis, reduction (Chao and Wang, 1992; Murata and Koh, 1980), synthesis, property queries, and animation of FMS operations in one software package. Using the X window graphical interface and animation, XPN-FMS makes the modeling and analysis of an FMS visualizable and easy to understand and manipulate. It lets a user draw the factory layout of an FMS on the screen of a monitor using the supplied tools. A corresponding PN model can also be drawn on the monitor screen. XPN-FMS can animate and simulate the overall operating process of the FMS. It is useful for FMS specification, validation, and exploration of different design alternatives, status monitoring, and control. Using XPN-FMS with various inputs and comparing the resulting outputs, the user can determine how to improve efficiency, reduce cost, and pinpoint bottlenecks. For the PN models of FMSs that are decision free, we extend the theory and algorithm of a unique matrix-based method (Chao and Wang, 1993b) to search for subcritical loops (including types A and B) and to support scheduling and dealing with transition periods. XPN-FMS implements this extended method to find the minimum cycle time, critical loop, subcritical loops, next critical loop, and scheduling ranges to avoid the transient period for static scheduling. This is implemented in XPN-FMS for the input sequence control.This project is partially funded by NJIT's Separately Budgeted Research Program. Portions of this article were presented in Chao, Chen, Wang, and Zhou (1992),Proceedings of the 1992 IEEE International Conference on Systems, Man, and Cybernetics, Chicago, Illinois, October 1992. The former name of the first author, which has appeared in some of his earlier publications, was Yuh Yaw.     

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.     

Deadlock prevention and avoidance in FMS: A Petri net based approach

The use of structure theory of Petri nets to develop efficient deadlock prevention and deadlock avoidance methods for flexible manufacturing systems (FMSs) modelled by S⁴R nets is demonstrated. Major synchronisation patterns, such as generalised parallel and sequential mutual exclusion, frequently observed in FMS contexts can be represented by this class. The liveness property of a given S⁴R net (deadlock-freeness in the context of FMSs) is characterised in terms of structural Petri net elements called siphons. An efficient method for controlling minimal siphons of a given S⁴R net is developed where local control places are added to the net. A sufficient condition for liveness of the augmented net is provided. This constitutes a deadlock prevention approach. When the net liveness condition is not satisfied, an on-line controller, using a dynamic resource allocation policy, is developed for the augmented net. The performance of the proposed approaches is illustrated using several examples.     

A review of some issues and identification of some barriers in the implementation of FMS

Global competition, advancements in technology and ever changing customers’ demand have made the manufacturing companies to realize the importance of flexible manufacturing systems (FMS). These organizations are looking at FMS as a viable alternative to enhance their competitive edge. But, implementation of this universally accepted and challenging technology is not an easy task. A large number of articles have been reviewed and it is found that the existing literature lacks in providing a clear picture about the implementation of FMS. In this paper, work of various researchers has been studied and it is found that it is really a very difficult task for any organization to transform into FMS on the basis of existing research results. A wide gap exists between the proposed approaches/algorithms for the design of different components of FMS and the real-life complexities. Besides describing the gap in various issues related to FMS, some barriers, which inhibit the adaptation and implementation of FMS, have also been identified in this paper.     

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.