Showing papers on "Petri net published in 2016"

Understanding Petri Nets: Modeling Techniques, Analysis Methods, Case Studies

Abstract: With their intuitive graphical approach and expressive analysis techniques, Petri nets are suitable for a wide range of applications and teaching scenarios, and they have gained wide acceptance as a modeling technique in areas such as software design and control engineering. The core theoretical principles have been studied for many decades and there is now a comprehensive research literature that complements the extensive implementation experience. In this book the author presents a clear, thorough introduction to the essentials of Petri nets. He explains the core modeling techniques and analysis methods and he illustrates their usefulness with examples and case studies. Part I describes how to use Petri nets for modeling; all concepts are explained with the help of examples, starting with a generic, powerful model which is also intuitive and realistic. Part II covers the essential analysis methods that are specific to Petri nets, introducing techniques used to formulate key properties of system nets and algorithms for proving their validity. Part III presents case studies, each introducing new concepts, properties and analysis techniques required for very different modeling tasks. The author offers different paths among the chapters and sections: the elementary strand for readers who wish to study only elementary nets; the modeling strand for those who wish to study the modeling but not the analysis of systems; and finally the elementary models of the modeling strand for those interested in technically simple, but challenging examples and case studies. The author achieves an excellent balance between consistency, comprehensibility and correctness in a book of distinctive design. Among its characteristics, formal arguments are reduced to a minimum in the main text with many of the theoretical formalisms moved to an appendix, the explanations are supported throughout with fully integrated graphical illustrations, and each chapter ends with exercises and recommendations for further reading. The book is suitable for students of computer science and related subjects such as engineering, and for a broad range of researchers and practitioners.

Comprehensible predictive models for business processes

Abstract: Predictive modeling approaches in business process management provide a way to streamline operational business processes. For instance, they can warn decision makers about undesirable events that are likely to happen in the future, giving the decision maker an opportunity to intervene. The topic is gaining momentum in process mining, a field of research that has traditionally developed tools to discover business process models from data sets of past process behavior. Predictive modeling techniques are built on top of process-discovery algorithms. As these algorithms describe business process behavior using models of formal languages (e.g., Petri nets), strong language biases are necessary in order to generate models with the limited amounts of data included in the data set. Naturally, corresponding predictive modeling techniques reflect these biases. Based on theory from grammatical inference, a field of research that is concerned with inducing language models, we design a new predictive modeling technique based on weaker biases. Fitting a probabilistic model to a data set of past behavior makes it possible to predict how currently running process instances will behave in the future. To clarify how this technique works and to facilitate its adoption, we also design a way to visualize the probabilistic models. We assess the effectiveness of the technique in an experimental evaluation with synthetic and real-world data.

Optimal One-Wafer Cyclic Scheduling and Buffer Space Configuration for Single-Arm Multicluster Tools With Linear Topology

Abstract: This work studies the scheduling problem of a single-arm multicluster tool with a linear topology and process-bound bottleneck individual tool. The objective is to find a one-wafer cyclic schedule such that the lower bound of cycle time is reached by optimally configuring spaces in buffering modules that link individual cluster tools. A Petri net (PN) model is developed to describe the dynamic behavior of the system by extending resource-oriented PNs such that a schedule can be parameterized by robots’ waiting time. Based on this model, conditions are presented under which a one-wafer cyclic schedule with the lower bound of cycle time can be found. With the derived conditions, an algorithm is developed to find such a schedule and optimally configure buffer spaces. The algorithm requires only simple calculation to set the robots’ waiting time and buffer size. Illustrative examples are presented to demonstrate the proposed method.

IoT-Enabled Real-Time Production Performance Analysis and Exception Diagnosis Model

Abstract: The recent developments of technologies in Internet of Things (IoT) provide the opportunities for smart manufacturing with real-time traceability, visibility, and interoperability in production planning, execution, and control. To fulfill this target, this work presents a real-time production performance analysis and exception diagnosis model (PAEDM). By this model, hierarchical-timed-colored Petri net (HTCPN) with smart tokens that change just like smart objects in practice is used to analyze the sensor data such that the critical performance information can be perceived. Decision Tree is used to diagnose exceptions from the critical production performance, so that persuasive qualitative and quantitative exception information can be extracted accurately. The presented method is demonstrated by a case study and simulation results show that PAEDM can be used to effectively analyze production performance and exceptions in real-time for dynamic and stochastic manufacturing processes.

A divide-and-conquer-method for the synthesis of liveness enforcing supervisors for flexible manufacturing systems

Abstract: In this paper a divide-and-conquer-method for the synthesis of liveness enforcing supervisors (LES) for flexible manufacturing systems (FMS) is proposed. Given the Petri net model (PNM) of an FMS prone to deadlocks, it aims to synthesize a live controlled Petri net system. For complex systems, the use of reachability graph (RG) based deadlock prevention methods is a challenging problem, as the RG of a PNM easily becomes unmanageable. To obtain the LESs from a large PNM is usually intractable. In this paper, to ease this problem the PNM of a system is divided into small connected subnets. Each connected subnet prone to deadlocks is then used to compute the LES for the original PNM. Starting from the simplest subnet prone to deadlocks to make the subnet live, monitors (control places) are computed. The RG of each subnet is considered and split into a dead-zone (DZ) and a live-zone. All states in the DZ are prevented from being reached by means of a well-established invariant-based control method. Next, the computation of monitors is followed for bigger subnets. Previously computed monitors are included within the bigger subnets based on a criterion. This process keeps the DZ of the bigger subnets smaller compared with the original uncontrolled subnets. When all subnets are live we obtain a set of monitors that are included within the PNM to obtain a partially controlled PNM (pCPNM). A new set of monitors is also computed for the pCPNM. Finally, a live controlled Petri net system is obtained. The proposed method is generally applicable, easy to use, effective and straightforward although its off-line computation is of exponential complexity in theory. Its use for FMS control guarantees deadlock-free operation and high performance in terms of resource utilization and system throughput. Two FMS deadlock problems from the literature are used to illustrate the applicability and the effectiveness of the proposed method.

Hybrid Petri nets for modeling and analysis of microgrid systems

Abstract: Hybrid Petri nets U+0028 HPNs U+0029 are widely used to describe and analyze various industrial hybrid systems that have both discrete-event and continuous discrete-time behaviors. Recently, many researchers attempt to utilize them to characterize power and energy systems. This work proposes to adopt an HPN to model and analyze a microgrid that consists of green energy sources. A reachability graph for such a model is generated and used to analyze the system properties.

On the Equivalence of Observation Structures for Petri Net Generators

Abstract: Observation structures considered for Petri net generators usually assume that the firing of transitions may be observed through a static mask and that the marking of some places may be measurable. These observation structures, however, are rather limited, namely they do not cover all cases of practical interest where complex observations are possible. We consider in this paper more general ones, by correspondingly defining two new classes of Petri net generators: labeled Petri nets with outputs (LPNOs) and adaptive labeled Petri nets (ALPNs). To compare the modeling power of different Petri net generators, the notion of observation equivalence is proposed. ALPNs are shown to be the class of bounded generators possessing the highest modeling power. Looking for bridges between the different formalisms, we first present a general procedure to convert a bounded LPNO into an equivalent ALPN or even into an equivalent labeled Petri net (if any exists). Finally, we discuss the possibility of converting an unbounded LPNO into an equivalent ALPN.

Discovery of Multi-perspective Declarative Process Models

Abstract: Process discovery is one of the main branches of process mining that allows the user to build a process model representing the process behavior as recorded in the logs. Standard process discovery techniques produce as output a procedural process model (e.g., a Petri net). Recently, several approaches have been developed to derive declarative process models from logs and have been proven to be more suitable to analyze processes working in environments that are less stable and predictable. However, a large part of these techniques are focused on the analysis of the control flow perspective of a business process. Therefore, one of the challenges still open in this field is the development of techniques for the analysis of business processes also from other perspectives, like data, time, and resources. In this paper, we present a full-fledged approach for the discovery of multi-perspective declarative process models from event logs that allows the user to discover declarative models taking into consideration all the information an event log can provide. The approach has been implemented and experimented in real-life case studies.

An overview of model checking practices on verification of PLC software

Abstract: Programmable logic controllers (PLCs) are heavily used in industrial control systems, because of their high capacity of simultaneous input/output processing capabilities. Characteristically, PLC systems are used in mission critical systems, and PLC software needs to conform real-time constraints in order to work properly. Since PLC programming requires mastering low-level instructions or assembly like languages, an important step in PLC software production is modelling using a formal approach like Petri nets or automata. Afterward, PLC software is produced semiautomatically from the model and refined iteratively. Model checking, on the other hand, is a well-known software verification approach, where typically a set of timed properties are verified by exploring the transition system produced from the software model at hand. Naturally, model checking is applied in a variety of ways to verify the correctness of PLC-based software. In this paper, we provide a broad view about the difficulties that are encountered during the model checking process applied at the verification phase of PLC software production. We classify the approaches from two different perspectives: first, the model checking approach/tool used in the verification process, and second, the software model/source code and its transformation to model checker's specification language. In a nutshell, we have mainly examined SPIN, SMV, and UPPAAL-based model checking activities and model construction using Instruction Lists (and alike), Function Block Diagrams, and Petri nets/automata-based model construction activities. As a result of our studies, we provide a comparison among the studies in the literature regarding various aspects like their application areas, performance considerations, and model checking processes. Our survey can be used to provide guidance for the scholars and practitioners planning to integrate model checking to PLC-based software verification activities.

Modeling Self-Adaptive Software Systems With Learning Petri Nets

Abstract: Traditional models unable to model adaptive software systems since they deal with fixed requirements only, but cannot handle the behaviors that change at runtime in response to environmental changes. In this paper, an adaptive Petri net (APN) is proposed to model a self-adaptive software system. It is an extension of hybrid Petri nets by embedding a neural network algorithm into them at some special transitions. The proposed net has the following advantages: 1) it can model a runtime environment; 2) the components in the model can collaborate to make adaption decisions while the system is running; and 3) the computation is done at the local component, while the adaption is for the whole system. We illustrate the proposed APN by modeling a manufacturing system.

A coloured Petri net-based hybrid heuristic search approach to simultaneous scheduling of machines and automated guided vehicles

Abstract: To achieve a significant improvement in the overall performance of a flexible manufacturing system, the scheduling process must consider the interdependencies that exist between the machining and transport systems. However, most works have addressed the scheduling problem as two independent decision making problems, assuming sufficient capacity in the transport system. In this paper, we study the simultaneous scheduling (SS) problem of machines and automated guided vehicles using a timed coloured Petri net (TCPN) approach under two performance objectives; makespan and exit time of the last job. The modelling approach allows the evaluation of all the feasible vehicle assignments as opposed to the traditional dispatching rules and demonstrates the benefits of vehicle-controlled assignments over machine-controlled for certain production scenarios. In contrast with the hierarchical decomposition technique of existing approaches, TCPN is capable of describing the dynamics and evaluating the performance of the ...

Parameterized verification through view abstraction

Abstract: We present a simple and efficient framework for automatic verification of systems with a parametric number of communicating processes. The processes may be organized in various topologies such as words, multisets, rings, or trees. Our method needs to inspect only a small number of processes in order to show correctness of the whole system. It relies on an abstraction function that views the system from the perspective of a fixed number of processes. The abstraction is used during the verification procedure in order to dynamically detect cut-off points beyond which the search of the state space need not continue. We show that the method is complete for a large class of well quasi-ordered systems including Petri nets. Our experimentation on a variety of benchmarks demonstrate that the method is highly efficient and that it works well even for classes of systems with undecidable verification problems. In particular, the method handles the fine-grained and full version of Szymanski's mutual exclusion protocol, whose correctness, to the best of our knowledge, has not been proven automatically by any other existing methods.

Availability analysis of safety critical systems using advanced fault tree and stochastic Petri net formalisms

Abstract: Failure scenarios analysis constitutes one of the cornerstones of risk assessment and availability analysis. After a detailed review of available methods, this paper identified two distinct formalisms to analyze failure scenarios and systems' availability: generalized stochastic Petri nets (GSPN) and Fault tree driven Markov processes (FTDMP). The FTDMP formalism is a combination of the Markov process and the fault tree. This aims to overcome fault tree limitations while maintaining the use of deductive logic. The GSPN is a Petri net with probabilistic analysis using Monte Carlo simulation. The effectiveness of both methods is studied through an emergency flare system including a knockout drum. It is observed that GSPN provides a robust and reliable mechanism for accident scenario analysis. It provides additional information such as events' frequencies at operating and failing modes and expected occurrence timing and durations resulting from different complex sequences. Even for multi-state variables which could be used to design a safety management system. Although FTDMP is a powerful formalism, it provides limited information.

Polynomially Complex Synthesis of Distributed Supervisors for Large-Scale AMSs Using Petri Nets

Abstract: Due to the competition for limited resources by many concurrent processes in large-scale automated manufacturing systems (AMSs), one has to resolve any deadlock issue in order to reach their production goals without disruption and downtime. Monolithic resolution is a conventional approach for optimal or acceptable solutions, but may suffer from computational difficulty. Some decentralized methods are more efficient in finding approximate solutions, but most are application dependent. By modeling AMSs as Petri nets, we develop an innovative distributed approach, which can create a trajectory leading to a desired goal and is adaptable to different kinds of applications. Control strategies are applied to processes locally such that they can proceed concurrently and efficiently. Global goals are always reachable through the local observation, control, and execution of processes without knowing external and extra information. Polynomially complex are designed to find distributed controllers.

30 Years of GreatSPN

Abstract: GreatSPN is a tool for the stochastic analysis of systems modeled as (stochastic) Petri nets. This chapter describes the evolution of the GreatSPN framework over its life span of 30 years, from the first stochastic Petri net analyzer implemented in Pascal, to the current, fancy, graphical interface that supports a number of different model analyzers. This chapter reviews, with the help of a manufacturing system example, how GreatSPN is currently used for an integrated qualitative and quantitative analysis of Petri net systems, ranging from symbolic model checking techniques to a stochastic analysis whose efficiency is boosted by lumpability.

Fuzzy Petri nets Using Intuitionistic Fuzzy Sets and Ordered Weighted Averaging Operators

Abstract: Fuzzy Petri nets (FPNs) are an important modeling tool for knowledge representation and reasoning, which have been extensively used in a lot of fields. However, the conventional FPN models have been criticized as having many shortcomings in the literature. Many different models have been suggested to enhance the performance of FPNs, but deficiencies still exist in these models. First, various types of uncertain knowledge information provided by domain experts are very hard to be modeled by the existing FPN models. Second, the traditional FPNs determine the results of knowledge reasoning using the min, max, and product operators, which may not work well in many practical applications. In this paper, we propose a new type of FPN model based on intuitionistic fuzzy sets and ordered weighted averaging operators to deal with the problems and improve the effectiveness of the conventional FPNs. Moreover, a max-algebra-based reasoning algorithm is developed in order to implement the intuitionistic fuzzy reasoning formally and automatically. Finally, a case study concerning fault diagnosis of aircraft generator is presented to demonstrate the proposed intuitionistic FPN model. Numerical experiments show that the new FPN model is feasible and quite effective for knowledge representation and reasoning of intuitionistic fuzzy expert systems.

A Deterministic and Stochastic Petri Net Model for Traffic-Responsive Signaling Control in Urban Areas

Abstract: The problem of reducing congestion within urban areas by means of a traffic-responsive control strategy is addressed in this paper. The model of an urban traffic network is microscopically represented by means of deterministic and stochastic Petri nets, which allow a compact representation of the dynamic traffic network. To properly model traffic congestion, intersections are divided into crossing sections, and roads have limited capacity. Each intersection includes a multiphase traffic signal, whose sequence of phases is given and represented by a timed Petri net. The control strategy proposed in this paper aims at minimizing queue lengths by optimizing the duration of each signal phase. This is accomplished by heuristically solving a stochastic optimization problem within a receding-horizon scheme, to take into account the actual traffic flow entering the network, thus making the proposed approach traffic-responsive. In this framework, the Petri nets play a key role, as the cost function to be minimized is a function of the marking, and the constraints include the marking state evolution. The proposed strategy is applicable to both undersaturated and oversaturated traffic conditions.

Symbolic computation of differential equivalences

Abstract: Ordinary differential equations (ODEs) are widespread in many natural sciences including chemistry, ecology, and systems biology, and in disciplines such as control theory and electrical engineering. Building on the celebrated molecules-as-processes paradigm, they have become increasingly popular in computer science, with high-level languages and formal methods such as Petri nets, process algebra, and rule-based systems that are interpreted as ODEs. We consider the problem of comparing and minimizing ODEs automatically. Influenced by traditional approaches in the theory of programming, we propose differential equivalence relations. We study them for a basic intermediate language, for which we have decidability results, that can be targeted by a class of high-level specifications. An ODE implicitly represents an uncountable state space, hence reasoning techniques cannot be borrowed from established domains such as probabilistic programs with finite-state Markov chain semantics. We provide novel symbolic procedures to check an equivalence and compute the largest one via partition refinement algorithms that use satisfiability modulo theories. We illustrate the generality of our framework by showing that differential equivalences include (i) well-known notions for the minimization of continuous-time Markov chains (lumpability), (ii)~bisimulations for chemical reaction networks recently proposed by Cardelli et al., and (iii) behavioral relations for process algebra with ODE semantics. With a prototype implementation we are able to detect equivalences in biochemical models from the literature that cannot be reduced using competing automatic techniques.

Control Design Strategy for Flying Capacitor Multilevel Converters Based on Petri Nets

Abstract: Multilevel power converters belong to a class of hybrid systems, where continuous and discrete variables coexist, representing a challenge for their control design. Flying capacitor multilevel converters require controlling the flying capacitor voltages and the output current. In this regard, several works have studied this problem. However, the discrete nature of the converter has not been directly included in the control design. In this paper, a hybrid representation of the converter is considered, and using Petri net (PN) methodology, a control scheme is proposed to regulate the flying capacitor voltages and the output current. An analysis of stability, using Lyapunov method, is presented, and sufficient stability conditions are obtained. From these conditions, the commutation rules are defined and used to define the transition rules for the PNs. Experimental results validate the performance of the proposed scheme.

Use of Petri nets to model the maintenance of wind turbines

Abstract: With large expansion plans for the offshore wind turbine industry there has never been a greater need for effective operations and maintenance. The two main problems with the current operations and maintenance of an offshore wind turbine are the cost and availability. In this work a simulation model has been produced of the maintenance process for a wind turbine with the aim of developing a procedure that can be used to optimise the process. This initial model considers three types of maintenance; periodic, conditional and corrective and also considers the weather in order to determine the accessibility of the turbine. Petri nets have been designed to simulate each type of maintenance and weather conditions. It has been found that Petri nets are a very good method to model the maintenance process due to their dynamic modelling and adaptability and their ability to test optimisation techniques. Due to their versatility Petri net models are developed for both system hardware and the maintenance processes and these are combined in an efficient and concise manner.

Fundamental Conceptual Modeling Languages in OMiLAB

Abstract: Regardless of the application domain, both the analysis of existing systems and the creation of new systems benefit extensively from having the system modeled from a conceptual point of view in order to capture its behavioral, structural or semantic characteristics, while abstracting away irrelevant details. Depending on which relevant details are assimilated in the modeling language, modeling tools may support different degrees of domain-specificity. The boundaries of what domain-specific means are as ambiguous as the definition of a domain—it may be a business sector, a paradigm, or a narrow application area. However, some patterns and invariants are recurring across domains and this has led to the emergence of commonly used modeling languages that incorporate such fundamental concepts. This chapter focuses on the metamodeling approach for the hybridization of BPMN, ER, EPC, UML and Petri Nets within a single modeling method identified as FCML, with a proof of concept named Bee-Up implemented in OMiLAB.

A Timed Petri Nets Model for Performance Evaluation of Intermodal Freight Transport Terminals

Abstract: This paper presents a general modeling framework for Intermodal Freight Transport Terminals (IFTTs). The model allows simulating and evaluating the performance of such key elements of the intermodal transportation chain. Hence, it may be used by the decision maker to identify the IFTT bottlenecks, as well as to test different solutions to improve the IFTT dynamics. The proposed modeling framework is modular and based on timed Petri Nets (PNs), where places represent resources and capacities or conditions, transitions model inputs, flows, and activities into the terminal and tokens are intermodal transport units or the means on which they are transported. The model is able to represent the different types of existing IFTTs. Its effectiveness is tested first on an example from the literature and then on a real case study, the railroad inland terminal of a leading Italian intermodal logistics company, showing its ease of application. In the real case study, using the proposed formalism we test the as-is IFTT performance and evaluate alternative possible to-be improvements in order to identify and eliminate emerging criticalities in the terminal dynamics.

Rescheduling Trains Using Petri Nets and Heuristic Search

Abstract: Railway systems may be interrupted by unforeseen events that require quick replanning to a feasible new schedule. This paper deals with the train rescheduling problem on double-track lines. The rescheduling problem is regarded as a conflict detection and resolution procedure. Timed Colored Petri nets are adopted to model the railway system: places represent rail resources, and tokens represent trains. A conflict detection rule is established in accordance with the safety principles of railway operations to predict potential conflicts. A Petri-net-based conflict resolution algorithm adapted from the $A^{\ast}$ algorithm is designed to search for an optimal or a near-optimal feasible schedule. The algorithm takes into account the railway operational principles when generating new markings, so that the new schedule has less train delays and respects the safety principles. The approach is applied in a case study to a double-track corridor from the Dutch railway network. For small delays, the algorithm can make delayed trains recover to their scheduled timetable within seconds. For large perturbations, the solutions generated by the algorithm can effectively reduce train delays while ensuring traffic safety.

Supervisor Simplification in FMSs: Comparative Studies and New Results Using Petri Nets

Abstract: Modern complex systems require intensive application of sophisticated supervisors Structural simplification techniques are one of the fundamental researches in the context of flexible manufacturing systems (FMSs) They can reduce implementation cost, mitigate fabrication complexity, and improve reliability Several typical methods have been developed along this direction In order to thoroughly explore their effectiveness and performance, we not only conduct a comparison investigation but also develop some new theoretical results Several analytical results and performance measures are proposed for their qualitative and quantitative comparison Our approach can assist researchers and practitioners to better comprehend the inherent mechanisms and relative merits of these simplification methodologies as well as their applicability in FMSs This paper is motivated by FMSs’ control; however, it is also applicable to other systems with discrete event controllers