Petri Net-based Approach Research Articles

A Petri net-based approach to robust deadlock prevention in automated manufacturing systems with unreliable resources

This paper studies the robust deadlock control issues in automated manufacturing systems (AMSs) with unreliable resources. The purpose of this paper is to synthesize a robust prevention supervisor to guarantee that the controlled system can operate smoothly when unreliable resources work well, and to ensure that parts that do not require any failed resources in their remaining routes can continue to be processed even if unreliable resources malfunction. In this paper, Petri nets (PNs) are employed to model the considered AMSs, which allow multi-quantity and multi-type of resource acquisitions. First, to avoid the resource’s underflow, a set of resource constraints denoted as a set of inequalities are developed based on the nominal capacity of shared resources and the minimal resource requirements of processes. Control places (monitors) are derived along with their control variables so as to resolve the blocking states caused by resource failures. Second, to guarantee the system’s liveness, a monitor is designed for each considered siphon in the different subnets derived from a system net. As a result, a robust prevention supervisor is synthesized for AMSs with unreliable resources. The effectiveness and superiority of our method are elucidated by some analyses and discussions.

Formal Modeling and Analysis of User Activity Sequence in Online Social Networks: A Stochastic Petri Net-Based Approach

Formal Modeling and Analysis of User Activity Sequence in Online Social Networks: A Stochastic Petri Net-Based Approach

Government's public panic emergency capacity assessment and response strategies under sudden epidemics: A fuzzy Petri net-based approach

In the post-epidemic era, public panic has emerged as a highly significant secondary disaster, necessitating an urgent enhancement of emergency management capabilities by governments at all levels. In order to ensure a robust assessment of the government's ability to manage public panic, it is crucial to effectively address the influence of uncertain and ambiguous factors associated with such scenarios. This paper proposes a governmental public panic emergency management capability assessment method based on fuzzy Petri nets. By analyzing the factors influencing public panic across the four evolutionary stages, namely gestation, outbreak, diffusion, and fading, we establish a hierarchical evaluation index system for assessing emergency management capabilities. Additionally, we develop a range of multi-scenario emergency management strategies. To address the challenges posed by uncertainty, randomness, fuzziness, and insufficient statistical data within the assessment index system, we introduce fuzzy Petri nets and fuzzy reasoning rules to evaluate the emergency management capability of the assessment system and derive the optimal emergency management strategy. According to example simulations, the effectiveness and practicality of models and rules constructed using fuzzy Petri nets are demonstrated, highlighting their superiority over traditional assessment methods. This comprehensive approach equips the government with a versatile toolkit for effectively managing public panic emergencies.

A Coloured Petri Net-based approach and Genetic Algorithms for improving services in the Emergency Department

A Coloured Petri Net-based approach and Genetic Algorithms for improving services in the Emergency Department

Public bicycle sharing systems control and performance evaluation: A Petri net-based approach

Public bicycle sharing systems (PBSS) allow citizens to move between two points within a region using bicycles, being composed of stations where users can either pick up or return bicycles after using them. Depending on the demand for bicycles, stations may either become empty or full of bicycles. This problem is usually solved by means of a vehicle that exchanges bicycles among the stations following some balancing strategy. In this paper, we propose a model for PBSSs using generalized stochastic Petri nets with external control, a Petri net with an external agent that decides how to execute the balancing strategy. The main advantage of our model is that it allows different balancing strategies to be implemented without changing the Petri net structure. In addition, since the model is a Petri net, we can easily implement it by making a Petri net simulator built with the incidence matrix associated with the Petri net model. We also propose two balancing strategies and validate both the simulation algorithm and the balancing strategies by applying them to the performance evaluations of the model of a real system, named Integra UFRJ PBSS. The performance evaluation of the system under the balacing strategies have shown that both strategies considerably reduce the times, in average, that stations remain full or empty throughout the system operation, solving problems related to stations being empty of full; in particular, the first strategy reduced those times in such a way that no more than five percent of the users of each station had trouble returning their bicycles due to stations being full, whereas the second strategy reduced the percentage of lost users due to stations being empty to no more than five percent for each station.

Ensuring sufficient cabin hospital beds for curbing the spread of COVID-19 – Findings from petri net analysis

Due to the complexity of the virus and its rapid rate of spread, many countries face the same challenges of providing adequate medical resources. This paper provides an analytical approach for evaluating the possibility of the regional construction industry constructing a large number of cabin hospitals within a short time. The key idea is to compare the demand and supply of patient beds using a Petri net-based approach that incorporates a neural network for the prediction of demand, fuzzy logic for decision-making, and a linear model for predicting supply. The data reported in the Shanghai Omicron battle is used to validate the developed model. Our results show that the fastest conversion speed and the least manpower requirement are obtained from high-rise buildings. Then, preparing some high-rises for easy conversion into cabin hospitals seems a possible solution for future citywide preparedness toward pandemic resilience.

PEPN-GRN: A Petri net-based approach for the inference of gene regulatory networks from noisy gene expression data.

The inference of gene regulatory networks (GRNs) from expression data is a challenging problem in systems biology. The stochasticity or fluctuations in the biochemical processes that regulate the transcription process poses as one of the major challenges. In this paper, we propose a novel GRN inference approach, named the Probabilistic Extended Petri Net for Gene Regulatory Network (PEPN-GRN), for the inference of gene regulatory networks from noisy expression data. The proposed inference approach makes use of transition of discrete gene expression levels across adjacent time points as different evidence types that relate to the production or decay of genes. The paper examines three variants of the PEPN-GRN method, which mainly differ by the way the scores of network edges are computed using evidence types. The proposed method is evaluated on the benchmark DREAM4 in silico data sets and a real time series data set of E. coli from the DREAM5 challenge. The PEPN-GRN_v3 variant (the third variant of the PEPN-GRN approach) sought to learn the weights of evidence types in accordance with their contribution to the activation and inhibition gene regulation process. The learned weights help understand the time-shifted and inverted time-shifted relationship between regulator and target gene. Thus, PEPN-GRN_v3, along with the inference of network edges, also provides a functional understanding of the gene regulation process.

Online fault diagnosis for smart machines embedded in Industry 4.0 manufacturing systems: A labeled Petri net-based approach

Detection of abnormality (or faults) occurrences is of paramount importance in smart manufacturing systems of Industry 4.0 since faults do not usually take the system immediately to a halt, and so, it can jeopardize an entire production. With that in mind, we propose here an online diagnoser based on the Petri model of either a specific machine or part of a smart manufacturing system that makes its decision regarding the fault occurrence by storing the sequence of observed events and, after each new occurrence of an observable event, it updates its state by verifying if two sets of inequalities are satisfied: one set that accounts for the normal behavior, and another one for the faulty behavior. The main advantage of the method proposed here over existing ones are as follow: (i) it requires simple inequality verification, as opposed to online solution of Integer Linear Programming Problems; (ii) it allows different transitions to be labeled by the same event, as opposed to one-to-one event-transition labeling previously assumed, which is a serious limitation, as far as smart manufacturing systems is concerned. The effectiveness of the proposed method is illustrated by applying it to a hypothetical machine embedded in a smart manufacturing line and comparing its performance with a method previously proposed in the literature.

Petri Net-Based Approach for “Cyber” Risks Modelling and Analysis for Industrial Systems

Today, industrial systems are large, complex, and increasingly vulnerable. Specifically, due to the current digital transformation, the industry 4.0 creates crucial cyber-risks and cyber-security challenges. In this context, risk modelling and impact analysis has become a crucial research topic. Based on the formal modelling and performance analysis power of Petri Nets (PN), this paper represents a summary of our methodological approach for “risk” modelling and “impact” analysis of cyber vulnerabilities and / or other critical events. The applicability of the developed approach is demonstrated on a real-life industrial system.

Petri Net Based Data-Flow Error Detection and Correction Strategy for Business Processes

Conceptual modeling, which includes both control-flow and data-flow modeling, has posed great challenges for conventional business process management systems. To support systematic data-flow modeling and analysis, in this paper, we propose a novel and effective Petri net-based approach. We first introduce a new type of Petri net, called WFIO-net, the firing rule of which is formally defined by extending classical Petri net with read and write semantics, to model both the control-flow and data-flow information. Then, we discuss about three possible data-flow errors over a WFIO-net, i.e., the missing, redundant and conflicting data errors. To detect such data-flow errors, we develop a polynomial complexity algorithm based on the so-called Activity Data Incidence Matrix (ADIM) of a WFIO-net. Following by that, we propose three effective correction strategies to resolve the detected data-flow anomalies. Finally, we present a property loan approval business process case study for our approach, and the study results demonstrate that the proposed detection and correction approaches are indeed very effective and can be applied to real-life settings.

Dynamic Monitoring of Service Outsourcing for Timed Workflow Processes

Service outsourcing for workflow processes has drawn much attention from researchers in recent years. Service outsourcing can not only improve the execution efficiency of workflow processes, but also reduce the overall costs and risks effectively. However, the existing methods neglect to consider the dynamic monitoring of the temporal constraints and the data transferring relationship of the activities among the local subplans or subprocesses of service providers in service outsourcing. As a result, the existing methods cannot propose solutions to temporal violations. In this paper, we propose a Petri net-based approach for dynamic monitoring of the temporal constraints of service outsourcing for timed workflow processes. As a widely used formal tool for modeling and analyzing the workflow processes, Petri nets can be used to design the structure of the workflow processes and provide powerful analysis techniques to verify the constraints. Specifically, we first propose a procedure to construct the Petri net-based fragments with data transferring of workflow processes. The monitoring mechanism of the temporal constraints is then set based on the fragments. Finally, we present algorithms for dynamically verifying the temporal constraints during the execution of fragments and repairing the temporal violations on the fragments. Compared with the existing methods, the proposed approach can construct fragments based on arbitrary service outsourcing results and provide optimal solutions to resolving temporal violations. Accordingly, the proposed approach can improve the efficiency of the exception handling in the workflow processes and reduce the overall operational costs.

Context-Aware Service Modeling and Conflicts Discovery Based on Petri Net

In smart environments, context-aware service sense various kinds of context information and reacts automatically to adapt to changing circumstances. These adaptions may lead to context changes which trigger other services elsewhere in the environment and thus produce cascading reactions. Conflict adaptions or unexpected side effects may exist in this process. This article focuses on service conflicts related to frustrations in service execution and violations of the service's objective. A petri net-based approach is proposed to model and simulate context changes as well as services execution, and a conflicts discovery mechanism was built to detect potential conflicts. The case study of smart home scenarios shows how the method helps locate conflicts caused by different services, validating the effectiveness of the proposed approach.

Dependability evaluation of a disaster recovery solution for IoT infrastructures

The ongoing miniaturization and cost reduction of electronic devices (microprocessors, sensors, batteries, and wireless communication units) have allowed the proliferation of the Internet of Things (IoT)-based applications. Many of these applications are mission-critical (e.g., healthcare and traffic road management), in the sense that the IoT system needs to take critical decisions in real-time. Hence, these IoT systems need to be designed using effective fault-tolerant techniques like disaster recovery (DR) solutions. This work proposes a Petri net-based approach for modeling and analysis of DR solutions for IoT infrastructures. The proposed models allow assessing important DR measures, such as system availability, cost, and recovery time objective. To demonstrate the feasibility of our approach, we present a case study in which a real-world healthcare IoT system is modeled and analyzed. Besides, sensitivity analysis is carried out to assess the effects of model parameters on the system availability.

The role of Fenton reaction in ROS-induced toxicity underlying atherosclerosis – modeled and analyzed using a Petri net-based approach

The superoxide-driven Fenton reaction plays an important role in the transformation of poorly reactive radicals into highly reactive ones. These highly reactive species (ROS), especially hydroxyl radicals can lead to many disturbances contributing to the endothelial dysfunction being a starting point for atherosclerosis. Although, iron has been identified as a possible culprit influencing formation of ROS, its significance in this process is still debatable. To better understand this phenomenon, the influence of blockade of Fenton reaction in a proposed Petri net-based model of the selected aspects of the iron ROS-induced toxicity in atherosclerosis has been evaluated. As a result of the blockade of iron ions formation in the model, even up to 70% of the paths leading to the progression of atherosclerosis in this model has been blocked. In addition, after adding to the model, the blockade of the lipids peroxidation paths, progression of atherosclerotic plaque has been not observed. This allowed to conclude that the superoxide-driven Fenton reaction plays a significant role in the atherosclerosis.

Petri nets-based approach for scheduling and rescheduling in multi-site manufacturing system

In multi-site manufacturing systems, operations are subject to a great number of unexpected interruptions that may withdraw the original manufacture schedules. In these cases, rescheduling is prevalent to preserve the performance of the whole system. There are many types of disturbances that can upset the schedule, including; machine failures, processing time delays, clients rush orders, quality problems, transportation failures, etc. In this work, we consider only the machine breakdown as disruption that require schedule updating (rescheduling). For that, we develop a Petri nets (PN) scheduling and rescheduling approach to model and simulate the multi-site manufacturing system while minimising the makespan. Finally, we give a case study to analyse the efficiency of the proposed model.

Petri nets-based approach for scheduling and rescheduling in multi-site manufacturing system

In multi-site manufacturing systems, operations are subject to a great number of unexpected interruptions that may withdraw the original manufacture schedules. In these cases, rescheduling is prevalent to preserve the performance of the whole system. There are many types of disturbances that can upset the schedule, including; machine failures, processing time delays, clients rush orders, quality problems, transportation failures, etc. In this work, we consider only the machine breakdown as disruption that require schedule updating (rescheduling). For that, we develop a Petri nets (PN) scheduling and rescheduling approach to model and simulate the multi-site manufacturing system while minimising the makespan. Finally, we give a case study to analyse the efficiency of the proposed model.

Developmental switching in Physarum polycephalum: Petri net analysis of single cell trajectories of gene expression indicates responsiveness and genetic plasticity of the Waddington quasipotential landscape

The developmental switch to sporulation in Physarum polycephalum is a phytochrome-mediated far-red light-induced cell fate decision that synchronously encompasses the entire multinucleate plasmodial cell and is associated with extensive reprogramming of the transcriptome. By repeatedly taking samples of single cells after delivery of a light stimulus pulse, we analysed differential gene expression in two mutant strains and in a heterokaryon of the two strains all of which display a different propensity for making the cell fate decision. Multidimensional scaling of the gene expression data revealed individually different single cell trajectories eventually leading to sporulation. Characterization of the trajectories as walks through states of gene expression discretized by hierarchical clustering allowed the reconstruction of Petri nets that model and predict the observed behavior. Structural analyses of the Petri nets indicated stimulus- and genotype-dependence of both, single cell trajectories and of the quasipotential landscape through which these trajectories are taken. The Petri net-based approach to the analysis and decomposition of complex cellular responses and of complex mutant phenotypes may provide a scaffold for the data-driven reconstruction of causal molecular mechanisms that shape the topology of the quasipotential landscape.

Petri net-based approach to short-term scheduling of crude oil operations with less tank requirement

With the interaction of discrete-event and continuous processes, the short-term scheduling problem of crude oil operations is essentially combinatorial. Thus, it is preferred to develop computationally efficient techniques for a satisfactory solution other than an exactly optimal one. Based on this idea, such a scheduling issue is studied in the viewpoint of control theory. To do so, as charging tanks are a type of critical resources, it is crucial to determine how many charging tanks are required to obtain a feasible schedule. By using a hybrid Petri net to describe the behavior of crude oil operations, we show that a feasible schedule can be found for a system with two or more than two distillers if there are two charging tanks for each distiller, which is the least number of charging tanks for finding a feasible solution to reach the maximal productivity. Also, the requirements of the initial state for obtaining a feasible schedule are given and scheduling method is proposed. The scheduling method is simple and computationally efficient. An industrial case study is used to show how the proposed approach can be applied.

Petri net-based approach to modeling and analysis of selected aspects of the molecular regulation of angiogenesis.

The functioning of both normal and pathological tissues depends on an adequate supply of oxygen through the blood vessels. A process called angiogenesis, in which new endothelial cells and smooth muscles interact with each other, forming new blood vessels either from the existing ones or from a primary vascular plexus, is particularly important and interesting, due to new therapeutic possibilities it offers. This is a multi-step and very complex process, so an accurate understanding of the underlying mechanisms is a significant task, especially in recent years, with the constantly increasing amount of new data that must be taken into account. A systems approach is necessary for these studies because it is not sufficient to analyze the properties of the building blocks separately and an analysis of the whole network of interactions is essential. This approach is based on building a mathematical model of the system, while the model is expressed in the formal language of a mathematical theory. Recently, the theory of Petri nets was shown to be especially promising for the modeling and analysis of biological phenomena. This analysis, based mainly on t-invariants, has led to a particularly important finding that a direct link (close connection) exist between transforming growth factor β1 (TGF-β1), endothelial nitric oxide synthase (eNOS), nitric oxide (NO), and hypoxia-inducible factor 1, the molecules that play a crucial roles during angiogenesis. We have shown that TGF-β1 may participate in the inhibition of angiogenesis through the upregulation of eNOS expression, which is responsible for catalyzing NO production. The results obtained in the previous studies, concerning the effects of NO on angiogenesis, have not been conclusive, and therefore, our study may contribute to a better understanding of this phenomenon.

A PetriNet-Based Approach for Supporting Traceability in Cyber-Physical Manufacturing Systems.

With the growing popularity of complex dynamic activities in manufacturing processes, traceability of the entire life of every product has drawn significant attention especially for food, clinical materials, and similar items. This paper studies the traceability issue in cyber-physical manufacturing systems from a theoretical viewpoint. Petri net models are generalized for formulating dynamic manufacturing processes, based on which a detailed approach for enabling traceability analysis is presented. Models as well as algorithms are carefully designed, which can trace back the lifecycle of a possibly contaminated item. A practical prototype system for supporting traceability is designed, and a real-life case study of a quality control system for bee products is presented to validate the effectiveness of the approach.