A generic tool management system architecture for flexible manufacturing systems (FMS)

This paper describes the use of an ARIMA (autoregressive-integrated-moving-average) model and its equivalent state space models to produce rule-based knowledge for flexible manufacturing systems (FMS) that can be used to investigate a wide variety of problems including machine breakdown, material shortage, and changes of scheduling rules. One great advantage of using the proposed models is the ease with which the simulation results can be summarised, analysed and captured, as well as the availability of the mathematical representation of the knowledge that can be kept in a knowledge database for evaluation and selection of alternative FMS strategies in a real-time environment. Various case studies are used to illustrate the methodology and the development of ARIMA and state space models, the analysis includes the system cost and stability of changes or interventions, the relationships among the simulation inputs and outputs, and the formulation of the production rule-base for the FMS scheduler. Management can use this integrated approach to describe and predict the dynamic behaviour of a complex FMS.

A dynamic scheduling system for flexible manufacturing systems (FMSs) is developed. The system consists of an artificial intelligence scheduler (AIS), a simulation model, a database, and a user interface. The AIS is used to generate candidate schedules according to specified dispatching rules and to control the search depth based on the status of an FMS. The simulation model is utilized to evaluate candidate schedules. The user interface is used to manually generate candidate schedules and to facilitate communication between different modules so as to realize automatic scheduling. Schedule related data are stored in the database. A dispatching-rule-based approximation search method is employed, which can quickly converge on good areas of the solution space, and the search method is suitable for dynamic scheduling in FMSs. A hypothetic FMS is designed and an sample scheduling problem is used to demonstrate the mechanism of the scheduling system.

Although the demand for Flexible Manufacturing Systems (FMS) is still growing, only a few companies are reported to have operational experience with these systems over a long period. Consequently, the supposed benefits of this new technology have yet to be widely proved in practice. The research reported was carried out to evaluate the experiences of a sample of early adopters of FMS in the United Kingdom, the Netherlands and Belgium, by means of longitudinal case studies. The extent to which the companies managed to achieve their FMS implementation goals is described, and the influence of technical problems, market changes and organisational pressures on goal achievement is demonstrated. It is concluded that in order to introduce and operate FMS successfully, adopters should approach FMS implementation management in a more integrated manner.

This paper aims to compute the number of reachable (forbidden, live and deadlock) states for flexible manufacturing systems (FMS) without the construction of reachability graph. The problem is nontrivial and takes, in general, an exponential amount of time to solve. Hence, this paper focusses on a simple version of Systems of Simple Sequential Processes with Resources (S3PR), called kth-order system, where each resource place holds one token to be shared between two processes. The exact number of reachable (forbidden, live and deadlock) states can be computed recursively.

Design of a maximally permissive liveness-enforcing supervisor with a compressed supervisory structure for flexible manufacturing systems

This chapter describes a framework for computer-aided process planning, scheduling and control for flexible manufacturing systems (FMS) producing One-of-a-Kind Products (OKP). This constitutes a form of mass customisation (MC) using one-piece flow (mass production) to produce variations on a number of different kinds of products (customisation). The basic concept is to produce customised forms of a standard product in the same time and for the same cost as the standard product. There is a need to capture customer requirements that specify the variation of the standard product easily, quickly and accurately. Also, there is a need to be able to respond to changing demands in the market for new variations and options for standard products. This chapter includes a case study of a company that produces a significant number of products daily that require the use of computer-aided engineering software systems and CNC (computer numerical control) equipment. The planning and control of these FMS are complicated because of the non-standard nature of the products.

Combined Petri net modelling and AI based heuristic hybrid search for flexible manufacturing systems—part 1. Petri net modelling and heuristic search

Production scheduling classically regards the processing units as the only constraining factor. However, scheduling for flexible manufacturing systems (FMS) involves a set of other allocation decisions like allocating jobs to transportation units. Ignoring the relevant allocation decisions has led to widening the gap between theory and practice. In this paper, an agent-based approach for a comprehensive scheduling for FMS is presented. This approach allows for generating a production schedule under consideration of the affecting resources. This is made possible by representing resources as agents. The generation of a schedule results from the goal-oriented interaction among the concerned agents. Based on the illustration of application scenarios, it is shown that this approach results in enhancing the overall performance.

This paper presents a step-by-step procedure for the design of the production control for flexible manufacturing systems (FMSs). Previous research has showed that there is a definite need to improve the production control for many FMSs in practice. The proposed procedure consists of three main steps: (I) an analysis of the FMS situation and a specification of the problems to be dealt with, (II) the design of the production control hierarchy, and (III) the design of the decision support tools and an information system. Feedback loops complete the procedure.<br> The design procedure can be seen as a synthesis of theory and practice. The procedure is illustrated by a case study.

This paper proposes a fuzzy inference-based scheduling decision for flexible manufacturing systems (FMS) with multiple objectives. The objectives have different and dynamic preference levels. It is inferred that the changes in the production environment may be sensed by environmental variables. The detected changes are input in a fuzzy inference mechanism, which outputs the current preference levels of all objectives. A multiple criteria scheduling decision is then made, using the partitioned combination of the preference levels. An example of application is presented. Simulation results show very good performance for the proposed system.

Petri nets are used to design deadlock control strategies for flexible manufacturing systems (FMS), which typically involve the addition of monitors and the associated arcs to the FMS. The addition of several monitors and associated arcs to first constructed Petri net model significantly complicates the Petri net controller. This paper develops a two-step method for preventing deadlocks based on a colored Petri net and a structurally minimal approach that significantly reduces the number of monitors. In the first step, a vector covering technique is applied to generate a minimal covered sets of first-met bad markings (FBMs) and legal markings that are respectively smaller than the sets of FBMs and legal markings. At one iteration, place invariants (PIs) corresponding to monitors are constructed by solving an integer linear programming problem (ILPP) to prohibit the maximum number of FBMs, while allowing all legal markings in the minimal covering set. The purpose of the ILPP is to maximize the number of FBMs forbidden by the PIs. Then, based on a colored Petri net, all generated monitors are combined into a global control place. Therefore, a supervisor with minimal structural complexity can be constructed. The obtained net model is controlled after the addition of the designed supervisor. Two instances from the literature are considered to illustrate the proposed approach.

Petri nets are a popular mathematical tool to investigate the deadlock problems in resource allocation systems. As an important problem solution paradigm in computer science, the divide-and-conquer strategy is used in this paper to investigate the deadlock prevention for flexible manufacturing systems (FMSs) that are modeled with Petri nets. Based on the concept of resource circuits, a plant net model is divided into an idle subnet, an autonomous subnet, and a number of small but independent subnets, called toparchies, from the viewpoint of deadlock control. A liveness-enforcing supervisor, called toparch, is designed for each toparchy. If a particular separation condition holds in a plant net model, the computational complexity of toparches is significantly reduced. This research shows that the resultant net, called monarch, by composing the toparches derived for the toparchies can serve as a liveness-enforcing Petri net supervisor for the whole plant model. FMS examples are given to illustrate the proposed method.

In this paper we discuss a new matrix-based modeling technique for flexible manufacturing systems (FMS). Four Task Plan Matrices can completely describe the job sequencing and resource assignment details of an FMS. The matrices come directly from plans generated by machine planners, or from the bill of materials and resource requirements matrix. Given the matrices, a rule-based supervisory controller operates in real-time to sequence jobs and assign resources depending on dynamic situational information about parts available, resources idle, and jobs completed. The function of the FMS can be quickly changed when new products are needed simply by changing the four matrices. By deriving explicit mathematical formulas for p-invariants and the resource requirement matrix for generalized reentrant flow lines, NP-complexity problems are avoided, which is often an issue in other modeling techniques.KeywordsManufacturingdiscrete event systemsflexible manufacturing systems.

To solve the problem of deadlock prevention for flexible manufacturing systems (FMS), an effective approach based on the State Class Graph (SCG) is proposed in a framework of time Petri nets (TPN). The first step determines the SCG of TPN. In the second step, since the SCG and discrete state graph (DSG) of a TPN have the same markings and obey the same linear temporal logic (LTL) properties, deadlock-freedom can be obtained by performing the required marking/transition separations. The theory of regions is used to design control places added to the original TPN model to realize the desired behavior. A parameterized example is used to show the performance of the proposed approach.

The objective of this paper is a study of minimizing the maximum completion time min F max, or cycle time of the last job of a given family of jobs using flow shop heuristic scheduling techniques. Three methods are presented: minimize idle time (MIT); Campbell, Dudek and Smith (CDS); and Palmer. An example problem with ten jobs and five machines is used to compare results of these methods. A deterministic t-timed colored Petri net model has been developed for scheduling problem. An execution of the deterministic timed Petri net allows to compute performance measures by applying graph traversing algorithms starting from initial global state and going into a desirable final state(s) of the production system. The objective of the job scheduling policy is minimizing the cycle time of the last job scheduled in the pipeline of a given family of jobs. Three heuristic scheduling methods have been implemented. First, a sub-optimal sequence of jobs to be scheduled is generated. Second, a Petri net-based simulator with graphical user interface to monitor execution of the sequence of tasks on machines is dynamically designed. A deterministic t-timed colored Petri net model has been developed and implemented for flexible manufacturing systems (FMS). An execution of the deterministic timed Petri net into a reachability graph allows to compute performance measures by applying graph traversing algorithms starting from initial global state to a desirable final state(s) of the production system.