Fault detection and location in DES using Petri Nets

Building reduced petri net models of discrete manufacturing systems

This paper is concerned with the diagnosability property of discrete event systems (DES) modeled by live and safe Interpreted Petri nets (IPN). The IPN are used to model both, the normal and faulty behavior of the system. Based on this model, the notion of input-output diagnosability is introduced and a polynomial algorithm to characterize diagnosable IPN is proposed. The novel features of the approach herein presented are: a) the notion of relative distance between any pair of transitions; b) the use of the net siphons and T-semiflows to determine the relative distance between any pair of transitions; c) a characterization of diagnosable IPN based on the relative distance concept. Moreover, the approach herein presented characterizes a broader class of IPN exhibiting the diagnosability property and presents a better deepening of the structures needed to characterize diagnosable IPN.

State-Stability Analysis of Discrete Event Systems using Petri-net Branching Processes

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.

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.

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.

A new method based on discrete event system is proposed for fault diagnosis of a certain kind of circuit, such as a relay control circuit. The original algorithm to obtain a minimal test set is improved. By using the improved algorithm the finest testable partition can be obtained and the complex testability analysis is avoided. The basic model of the proposed method and the general rule for fault diagnosis are described in detail. At first, the relay control circuit is described with corresponding combinational logic circuit model. Then, the fault diagnosis model of the circuit-under-test is constructed based on the given DES model. This method is applied to diagnose a relay control circuit. The results indicate that this method can diagnose this kind of circuit effectively and the new algorithm has a much lower computational complexity than the original algorithm. The fault elements can be localized exactly and this method has high practical value.

The use of shared resources is a major problem occurring in discrete event (DE) systems, including manufacturing systems, computer systems, communication systems, highway/vehicle systems, and others. The issues involve problems of assignment of resources when the same resources are simultaneously requested by more than one job. Failure to suitably assign, or dispatch, resources in such situations can have serious deleterious effects on system performance, resulting in extreme cases in system deadlock [7]. Computer operating systems engineers and industrial engineers have used the concepts of circular wait (CW) and circular blocking in analysis of such phenomena [41, 24]. Various concepts in Petri nets (PN) are extremely useful for dealing with deadlock and a great deal of research has been done from the PN point of view (see references, especially [11, 14, 19]). The PN approaches are often based on the notion of the siphon, which indeed is called a “deadlock” in some works [26]. Unfortunately, it is known that many problems in scheduling, dispatching, and deadlock analysis are NP-hard [12], so that significant increases in computing power do not significantly improve computational ability. Neither PN nor CW approaches have addressed this issue.

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

This paper aims to introduce a facility operation modeling and simulation mainly based on a discrete event system modeling scheme. Facilities have become so much complex that its operational status cannot be estimated by simple calculations. A facility can consist of a lot of unit process and a lot of transportation between consecutive processes, which may be modelled as a time driven system or an event driven system. However, the transportation between processes can usually be considered as a discrete event system and not a continuous system. Therefore, in macro-scale, a facility operation can be simulated on the basis of a discrete event system modeling if we do not consider how an individual process behaves. This study introduces the current status of the studies on an operation modeling and simulation regarding typical nuclear facilities along with some instances. Also, this paper provides insights about how a discrete event system can be applied to a nuclear facility. These kinds of modeling and simulation are very important because they can contribute to a facility design in terms of an optimal process and an equipment layout, a generic understanding for regulators, stakeholders and operators, a system diagnosis through by comparing measurement data with simulation results and furthermore it can contribute to an efficient operation scheduling.

In order to make it possible to effectively represent deterministic uncertainties and vagueness as well as the human subjective observation and judgement inherent to many real-world problems, especially those in biomedicine, we introduce, in this paper, fuzzy states and fuzzy events and generalize (crisp) discrete event systems (DES) to fuzzy DES. The largely graph-based current framework of the crisp DES is unsuitable for the expansion, and we have thus reformulated it using state vectors and event transition matrices which can be extended to fuzzy vectors and matrices by allowing their elements to take values between 0 and 1. To measure information related to fuzzy DES, we generalize the crisp DES observability. The new observability allows one to determine whether or not the system output observed is sufficient for decision making. Finally, we extend the optimal control of DES to fuzzy DES. The new fuzzy DES theory is consistent with the existing theory, both at the conceptual and the computation levels, in that the former contains the latter as a special case when the memberships must be either 0 or 1. Numerical examples are provided to illustrate the theoretical development.

Petrinets are the suitable tool for modeling and analysis of discrete event systems. The effective methods of analyzing the discrete event systems (DES) are exhibited by Petri nets. The entire structure of the system is mathematically expressed using Petrinets and also all the properties are analysed by different methods. The properties of Petrinets are different in various systems, a Flexible Manufacturing System (FMS) requires production activities in which raw materials, energy, labour, and equipment are combined together in the modification process for the production of good quality goods.” The word “flexible” explains the capability of the system to relate productively to make changes in the system. These changes can be internal failure of the system or classification problems such as a sample or external changes in the structure of the model as well as demand for the process. The inherent limitations such as undecidable properties, complexity in checking, automatic verification of the modeled system are existing in FMS. This paper explains a study on FMS using Petri net reduction. A PN underlies event structures with casuality and compatibility relations. Partial order methods and reduction methods reduce the complexity of constructing the reachability graph. The determination of PN system through reduction methods in recent years focused by many researchers. The significance of reduction methods are highlighted to execute the faster analysis of a system. Instead of coverability trees and the graphical representation the incidence matrix of the PNs are used for the reduction methods. Reduction methods are used to simplify large scale PNs into “equivalent” smaller nets. Boundedness, liveness, simplification of implicit places, shared resources and elimination of self-loops are checked though equivalent smaller nets. The structure of FMS is preserved.

In this paper we deal with the observability problem in discrete event systems modeled with interpreted Petri nets (IPN) under partial state observations with both silent and indistinguishable transitions. In particular, we study the sequence-detectability property which is a necessary condition for observability. We provide a characterization of sequence-detectability. This characterization takes into account both structural and dynamic aspects of the IPN model.

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 is concerned with multiagent system (MAS). In particular, the design of a function that generates beliefs in an agent using the belief-desire-intention (BDI) architecture is presented. This work is developed in the discrete event systems (DES) context, since they include a broad class of systems like flexible manufacturing systems that can be modeled as interpreted Petri net (IPN). The mathematical analysis used in this paper allows to determine, using linear algebra concepts, when the belief will tend to a fact as new information is perceived by the agent.