Equivalent and Efficient Optimization Models for an Industrial Discrete Event System with Alternative Structural Configurations

In this paper a hybrid approach is proposed for supervisory control of discrete event systems (DES) subject to forbidden states. Assuming that an uncontrolled bounded Petri net (PN) model of a (plant) DES and a set of forbidden state specifications are given, the proposed approach computes a maximally permissive and nonblocking closed-loop hybrid model. The first step is to simplify the given PN model by means of PN reduction rules. The simplified model and the specifications are then represented as buffers, and supervisory control theory (SCT) is applied to obtain a Ramadge–Wonham (RW) supervisor in the form of an automaton. After reduction of the latter’s state size by a ‘control congruence’, the simplified RW supervisor is represented by a so-called auto-net and coupled to the given uncontrolled PN plant model by means of inhibitor arcs to represent the disabling actions. The plant model and supervisor auto-net run concurrently, synchronizing on shared events. This procedure provides a maximally permissive and nonblocking ‘hybrid’ (mixed PN/automaton) closed-loop controlled system. The method is straightforward logically, graphically, and technologically. Its applicability is shown by two examples, one of them a workcell from the PN control literature.

This paper presents an approach to perform Activity Based Costing (ABC) with Petri nets. ABC is a powerful methodology to calculate various of discrete event systems (e.g. production systems). Petri net models of discrete event systems are easy to create, comprehend, and to perform analysis, the mathematics behind Petri nets is also easy to grasp. This paper shows how ABC can be performed with Petri nets, so that various involved in a discrete event system can be easily measured with the help of the Petri net model. After a short introduction to ABC and Petri nets, this paper shows the approach which basically embeds various cost drivers as firing costs and firing times of transitions in a Petri net model. This work also presents a case study that is done with GPenSIM, a toolbox realized with this approach.

Individuals, populations and fluid approximations: A Petri net based perspective

Manufacturing systems are highly parallel and distributed processes which require a high level of guarantee in operation and safety. Its concurrent and non-deterministic nature makes its analysis and design very complex. These systems can develop through different states and as a consequence of its magnitude is possible that the system has states unconsidered during the design phases that lead it to an undesirable performance. According to the above in this paper we have made several contributions aimed in to developing a procedure for modeling and analyzing discrete event systems that integrate wireless sensor and actuator networks (WSAN) by using Colored Petri Nets (CPN) models, in order of to establish a method for designing plans to minimize the time sequence of tasks execution and to fulfil with safety requirements ensuring absence of locks, process overflows, and unwanted presence of mutual exclusion conditions on the use of shared resources. Additionally a minimum set of components is presented in CPN that can be used to analyze the behavior of these kinds of systems and verify their structural and behavioral properties.

Petri net models are used to detect and isolate faults in case of discrete event systems as manufacturing, robotic, communication and transportation systems. This chapter addresses two problems. The first one is the structure designs and parameters identification of the Petri net models according to the observation and analysis of the sequences of events that are collected. Deterministic and stochastic time Petri nets are concerned. The proposed method is based on a statistical analysis of data and has a practical interest as long as sequences of events are already saved by supervision systems. The second problem concerns the use of the resulting Petri net models to detect, isolate and characterize faults in discrete event systems. This contribution includes the characterization of intermittent faults. This issue is important because faults are often progressive from intermittent to definitive and early faults detection and isolation improve productivity and save money and resources.

This paper presents a modular liveness-enforcing supervisory control design for scalable discrete event systems. A maximally permissive monitor-based supervisory control policy is suggested using divide and conquer paradigm. A vector-covering approach is used to minimize essential set of legal markings and first-met bad markings. Providing that modules of system interact by Enable operator, it will be proved that monitor-based supervisory control methods can be applied modularly. Then, Enable operator of Petri nets (PNs) can be used to synthesize subsystems. This algorithm is implemented by extending a graphical PN drawing and analysis tool with supervisory control analysis modules as Java codes. The experimental results show that this approach constitutes a primary step towards a hierarchical procedure that overcomes whole reachability graph computation, which is a bottleneck in deadlock preventing supervisory control policies.

Educative institutions consist of systems that can be considered as discrete event systems and show a complex behavior. The management of this kind of institutions may be very demanding, particularly if the planning and scheduling of educative activities are complemented by environmental and financial issues, such as programs of energy consumption efficiency, waste reduction and control, or rationalizing the use of the center resources. In order to cope with some of these issues, it is proposed a methodology that combines mathematical modeling, optimization based on genetic algorithms for searching the best solution in the solution space, and discrete event systems simulation. In order to carry out with all these tasks, a modeling paradigm has been considered to describe the educative institution. The institution is modelled using Petri nets following a top-bottom approach. This process is performed by the development of a low-detailed Petri net model of the global system and, in an additional step, the subsystems can be detailed by expanding their models. The Petri net model will present some parameters, representing the decision variables, which act as freedom degrees of the system and constitute the focus of the management board of the educative center.

This article presents a Petri net‐based approach to modeling and evaluating four different deadlock avoidance schemes for a distributed robotic system, i.e., a five‐robot‐five‐assembly‐line system. Among these four schemes are the conventional, full synchronization, global semaphore, and partial synchronization schemes. To explore such issues as the system performance and control structure complexity, this article conducts detailed Petri net modeling for this system and evaluates performance of the deadlock avoidance schemes using stochastic Petri nets. The interesting results presented include that: (1) any possible system deadlock can seriously degrade the system performance even if effective deadlock resolution techniques are available; (2) conservative use of resources is likely to be the best policy; and (3) higher resource utilization may not necessarily imply higher system production rate in a resource‐sharing environment. The related results need to be further explored for the larger resource‐sharing discrete event systems. ©1995 John Wiley & Sons, Inc.

Material handling systems are usually modeled as discrete event systems. However, when the size of these systems grows, the overall system performances depend also on continuous time phenomena. We present a hybrid model based on a new Petri net formalism that merges the concepts of Hybrid Petri Nets and Colored Petri Nets to obtain compact models for these systems. An example is discussed in detail to motivate the introduction of a new formalism.

Scheduling a manufacturing system is usually an NP-hard problem. This means that only heuristic algorithms can be used to provide near-optimal schedules. In this paper, we show that a manufacturing system can be modelled using a particular type of Petri nets, called controllable-output nets (CO nets). These Petri net models are then used to introduce a two-stage scheduling algorithm for large horizon problems. The first stage consists of distributing the workload among the resources. The second stage derives a schedule from the resource workload. The deterministic case is considered. Numerical results are proposed.

Modelling Basic Discrete Event Systems - A Key Factor in Supporting the Representation and Analysis of Complex Production Systems

Many technological, industrial or economical systems are described by discrete event system (DES) models. The decision making processes that arise in the design and operation of this kind of systems can be afforded by means of algorithmic methodologies. A large range of approaches based on the simulation of the behavior of the system have been reported to answer this problem. Their main advantage consists of being applicable to most of the systems. An important drawback is the significant computational resources required to perform an exhaustive exploration of the state space due to the combinatorial explosion. A manual choice of a reduced set of configurations to be simulated can be improved by the use of parametric Petri nets and a metaheuristic search of the most promising ones. In this paper, a review of some definitions of parametric Petri net found in the literature is presented, as well as a definition for the general framework of stating optimization problems of both, the operation and the design of the model of the DES. Moreover, a methodology to obtain such a parametric Petri net, called compound Petri net, from an easier-to-obtain set of alternative Petri nets is proposed and an application example is given.

This paper is about the incremental computation of control sequences for discrete event systems in uncertain environments where uncontrollable events may occur. Timed Petri nets are used for this purpose. The aim is to drive the marking of the net from an initial value to a reference one, in minimal or near-minimal time, by avoiding forbidden markings, deadlocks, and dead branches. The approach is similar to model predictive control with a finite set of control actions. At each step only a small area of the reachability graph is explored: this leads to a reasonable computational complexity. The robustness of the resulting trajectory is also evaluated according to a risk probability. A sufficient condition is provided to compute robust trajectories. The proposed results are applicable to a large class of discrete event systems, in particular in the domains of flexible manufacturing. However, they are also applicable to other domains as communication, computer science, transportation, and traffic as long as the considered systems admit Petri Nets (PNs) models. They are suitable for dynamical deadlock-free scheduling and reconfiguration problems in uncertain environments.

The author proposes an approach to represent assembly by Petri nets and presents an algorithm of automatic robot assembly planning based on the Petri-net model. The Petri-net model of assembly is configured by the goal structures and initial constraints, both in the Petri-net formalism. Due to the Petri-net representation of assembly, the plan generation is quite straightforward and the planning algorithm can be easily and efficiently implemented with simple matrix manipulation. An example of how to plan an assembly by the Petri net model is presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Residuals-based fault diagnosis of industrial automation systems using timed and untimed Interpreted Petri nets