Performance Analysis of an FMS Operating Under Different Failure Rates and Maintenance Policies

Flexible manufacturing Systems (FMSs) typically operate at 70–80% utilization, which is much higher than the utilization of traditional machines that can operate with as low as 20% utilization. A result is that an FMS may incur four times more wear and tear than a traditional system. This requests the execution of effective maintenance plans on FMSs. While maintenance actions can reduce the effects of breakdowns due to wear-outs, random failures are still unavoidable. It is important to understand the implications of a given maintenance plan on an FMS before its implementation. This paper discusses a procedure that combines simulation and analytical models to analyze the effects of corrective, preventive, and opportunistic maintenance policies on the performance of an FMS. The FMS performance is measured by its operational availability index, which is determined using the production output rate of the FMS under a variety of time between failure distributions and different operational conditions. The effects of various maintenance policies on FMS performance are simulated and the results are compared to determine the best policy for a given system.     

A fuzzy integrated decision-making support system for scheduling of FMS using simulation

In the complex environment of an automated manufacturing system, decision-making is one of the most important and difficult tasks of a manager in general or a scheduler in particular. Flexible Manufacturing Systems (FMSs) are highly automated and expensive systems. The high investment cost of a FMS justifies the use of computer simulation support. This paper investigates the operational problems of FMSs through simulation, and different combinations of scheduling rules are evaluated by a fuzzy integrated decision-making support system.     

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.     

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.     

The Applications of Flexible Manufacturing Technologies in Business Process Reengineering

Through radical redesign of business processes and systems, policies, and organizational structures, the business process reengineering (BPR) effort was initiated in the manufacturing industry to seek performance breakthroughs. This paper describes a novel approach to the BPR, which applies flexible manufacturing systems (FMSs) design and analysis technologies, such as simulation, multicriteria decision support, and artificial intelligence (AI). These technologies are integrated to design and analyze specific FMS models related to the proposed technical and managerial changes in an industrial case. First, the literature is reviewed to obtain an understanding of the BPR concept and the role of FMS design and analysis in BPR. Second, a decision-making support system is developed to illustrate how the FMS design and analysis would affect BPR. Finally, a summary of the integrated approach practice in industry and conclusions are presented. The paper shows that the key to a successful BPR approach is the identification and analysis of specific proposed models. It also demonstrates that the integrated approach enables engineers to improve the efficiency of BPR.     

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.     

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.     

Experimental investigation of an FMS due-date scheduling problem: Evaluation of machine and AGV scheduling rules

Although extensive research has been conducted to solve design and operational problems of automated manufacturing systems, many of the problems still remain unsolved. This article investigates the scheduling problems of flexible manufacturing systems (FMSs). Specifically, the relative performances of machine and automated guided vehicle (AGV) scheduling rules are analyzed against various due-date criteria. First, the relevant literature is briefly reviewed, and then the rules are tested under different experimental conditions by using a simulation model of an FMS. The sensitivity to AGV workload, buffer capacity, and processing-time distribution is also investigated to assess the robustness of the scheduling rules.     

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.     

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.     

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.     

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.     

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.     

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。     

An Intelligent Decision Support System for Part Launching in a Flexible Manufacturing System

The effective control of flexible manufacturing systems (FMS) poses a major challenge to designers and the research community. In this paper, the framework of a unique decision support system to assist in the control of a FMS through intelligent part-launching is introduced. The proposed system makes usr of a new heuristic method based on the pull concept, and a neural network trained with data from a system simulation model, which in turn provides a desision about choosing a part to be launched into the FMS. The performance of the proposed heuristic method was tested against another popular heuristic method normally used in existing FMS via discrete event simulation models. Data sets from the simulation program of the proposed system were used to train the neural network, which can be used on the shop floor for realtime decision support. The output from the trained neural network is based on the same principle as the proposed heuristic method used in the simulation program. Therefore, the descision support provided by the neural network can be used for improved shop floor control.     

Evaluation of the impact of information delays on flexible manufacturing systems performance in dynamic scheduling environments

The significance of the adverse effects of information delays (IDs) on flexible manufacturing system (FMS) performance is getting increasing attention from manufacturing systems managers, planners, schedulers, Enterprise Resource Planning software developers, and researchers because of their potential to disrupt production schedules. In this paper, we examine the extent of the adverse impact that IDs have on FMS performance. The FMSs are assumed to operate in a “review period” mode; i.e., the control decisions (e.g., sequencing and dispatching) are taken based on information monitored at predetermined intervals of time called “review periods”. The performance deterioration occurs due to the obsolescence of system status information. Key empirical findings based on extensive simulation experiments are: (1) IDs significantly degrade FMS performance for due date-based measures (mean tardiness and percent of jobs tardy); (2) IDs also degrade FMS performance for non-due date-based measures (mean flowtime and average machine utilization), albeit to a less severe degree; (3) routing flexibility, often regarded as a significant factor to influence FMS performance, is superseded by status review information delay.     

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.     

Development and evaluation of feature-focused dynamic routing policy

This paper reports on a development of feature-focused dynamic routing policy and its evaluation in a flexible manufacturing systems (FMS) simulation framework. The dynamic policy is based on an integrative methodology in which process planning system IMPlanner is integrated with FMS simulation module. IMPlanner’s rule-based system process selection system performs knowledge-intensive task of generating alternative processing options for each feature for parts in production plan. Generated alternative routings (process plan network) for each part are utilized in the FMS simulation module such that routing decision in FMS are made on periodic intervals by considering alternative processes for each feature and making decision based on the current system status and performance. The proposed framework has been evaluated in an experimental FMS simulation module, implemented in Arena, in which two performance criteria, machine utilization and WIP, were used to make routing decisions. The feature-focused approach is compared with traditional static decision-making, and its improved performance is demonstrated.     

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.