Engineering framework for service-oriented automation systems

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

The DS-Pnet modeling formalism for cyber-physical system development

This work presents the DS-Pnet modeling formalism (Dataflow, Signals and Petri nets), designed for the development of cyber-physical systems, combining the characteristics of Petri nets and dataflows to support the modeling of mixed systems containing both reactive parts and data processing operations. Inheriting the features of the parent IOPT Petri net class, including an external interface composed of input and output signals and events, the addition of dataflow operations brings enhanced modeling capabilities to specify mathematical data transformations and graphically express the dependencies between signals. Data-centric systems, that do not require reactive controllers, are designed using pure dataflow models. Component based model composition enables reusing existing components, create libraries of previously tested components and hierarchically decompose complex systems into smaller sub-systems. A precise execution semantics was defined, considering the relationship between dataflow and Petri net nodes, providing an abstraction to define the interface between reactive controllers and input and output signals, including analog sensors and actuators. The new formalism is supported by the IOPT-Flow Web based tool framework, offering tools to design and edit models, simulate model execution on the Web browser, plus model-checking and software/hardware automatic code generation tools to implement controllers running on embedded devices (C,VHDL and JavaScript). A new communication protocol was created to permit the automatic implementation of distributed cyber-physical systems composed of networks of remote components communicating over the Internet. The editor tool connects directly to remote embedded devices running DS-Pnet models and may import remote components into new models, contributing to simplify the creation of distributed cyber-physical applications, where the communication between distributed components is specified just by drawing arcs. Several application examples were designed to validate the proposed formalism and the associated framework, ranging from hardware solutions, industrial applications to distributed software applications

Computational Techniques for the Structural and Dynamic Analysis of Biological Networks

The analysis of biological systems involves the study of networks from different omics such as genomics, transcriptomics, metabolomics and proteomics. In general, the computational techniques used in the analysis of biological networks can be divided into those that perform (i) structural analysis, (ii) dynamic analysis of structural prop- erties and (iii) dynamic simulation. Structural analysis is related to the study of the topology or stoichiometry of the biological network such as important nodes of the net- work, network motifs and the analysis of the flux distribution within the network. Dy- namic analysis of structural properties, generally, takes advantage from the availability of interaction and expression datasets in order to analyze the structural properties of a biological network in different conditions or time points. Dynamic simulation is useful to study those changes of the biological system in time that cannot be derived from a structural analysis because it is required to have additional information on the dynamics of the system. This thesis addresses each of these topics proposing three computational techniques useful to study different types of biological networks in which the structural and dynamic analysis is crucial to answer to specific biological questions. In particu- lar, the thesis proposes computational techniques for the analysis of the network motifs of a biological network through the design of heuristics useful to efficiently solve the subgraph isomorphism problem, the construction of a new analysis workflow able to integrate interaction and expression datasets to extract information about the chromo- somal connectivity of miRNA-mRNA interaction networks and, finally, the design of a methodology that applies techniques coming from the Electronic Design Automation (EDA) field that allows the dynamic simulation of biochemical interaction networks and the parameter estimation

Intelligent Business Process Optimization for the Service Industry

The company\u27s sustainable competitive advantage derives from its capacity to create value for customers and to adapt the operational practices to changing situations. Business processes are the heart of each company. Therefore process excellence has become a key issue. This book introduces a novel approach focusing on the autonomous optimization of business processes by applying sophisticated machine learning techniques such as Relational Reinforcement Learning and Particle Swarm Optimization

A petri-net based methodology for modeling, simulation, and control of flexible manufacturing systems

Global competition has made it necessary for manufacturers to introduce such advanced technologies as flexible and agile manufacturing, intelligent automation, and computer-integrated manufacturing. However, the application extent of these technologies varies from industry to industry and has met various degrees of success. One critical barrier leading to successful implementation of advanced manufacturing systems is the ever-increasing complexity in their modeling, analysis, simulation, and control. The purpose of this work is to introduce a set of Petri net-based tools and methods to address a variety of problems associated with the design and implementation of flexible manufacturing systems (FMSs). More specifically, this work proposes Petri nets as an integrated tool for modeling, simulation, and control of flexible manufacturing systems (FMSs). The contributions of this work are multifold. First, it demonstrates a new application of PNs for simulation by evaluating the performance of pull and push diagrams in manufacturing systems. Second, it introduces a class of PNs, Augmented-timed Petri nets (ATPNs) in order to increase the power of PNs to simulate and control flexible systems with breakdowns. Third, it proposes a new class of PNs called Realtime Petri nets (RTPNs) for discrete event control of FMS s. The detailed comparison between RTPNs and traditional discrete event methods such as ladder logic diagrams is presented to answer the basic question \u27Why is a PN better tool than ladder logic diagram?\u27 and to justify the PN method. Also, a conversion procedure that automatically generates PN models from a given class of logic control specifications is presented. Finally, a methodology that uses PNs for the development of object-oriented control software is proposed. The present work extends the PN state-of-the-art in two ways. First, it offers a wide scope for engineers and managers who are responsible for the design and the implementation of modem manufacturing systems to evaluate Petri nets for applications in their work. Second, it further develops Petri net-based methods for discrete event control of manufacturing systems

Intelligent Business Process Optimization for the Service Industry

The company's sustainable competitive advantage derives from its capacity to create value for customers and to adapt the operational practices to changing situations. Business processes are the heart of each company. Therefore process excellence has become a key issue. This book introduces a novel approach focusing on the autonomous optimization of business processes by applying sophisticated machine learning techniques such as Relational Reinforcement Learning and Particle Swarm Optimization

Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review

YesSystem safety, reliability and risk analysis are important tasks that are performed throughout the system lifecycle to ensure the dependability of safety-critical systems. Probabilistic risk assessment (PRA) approaches are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to, Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). Growing complexity of modern systems and their capability of behaving dynamically make it challenging for classical PRA techniques to analyse such systems accurately. For a comprehensive and accurate analysis of complex systems, different characteristics such as functional dependencies among components, temporal behaviour of systems, multiple failure modes/states for components/systems, and uncertainty in system behaviour and failure data are needed to be considered. Unfortunately, classical approaches are not capable of accounting for these aspects. Bayesian networks (BNs) have gained popularity in risk assessment applications due to their flexible structure and capability of incorporating most of the above mentioned aspects during analysis. Furthermore, BNs have the ability to perform diagnostic analysis. Petri Nets are another formal graphical and mathematical tool capable of modelling and analysing dynamic behaviour of systems. They are also increasingly used for system safety, reliability and risk evaluation. This paper presents a review of the applications of Bayesian networks and Petri nets in system safety, reliability and risk assessments. The review highlights the potential usefulness of the BN and PN based approaches over other classical approaches, and relative strengths and weaknesses in different practical application scenarios.This work was funded by the DEIS H2020 project (Grant Agreement 732242)

Optimisation of Rail-road Level Crossing Closing Time in a Heterogenous Railway Traffic: Towards Safety Improvement - South African Case Study

The gravitation towards mobility-as-a service in railway transportation system can be achieved at low cost and effort using shared railway network. However, the problem with shared networks is the presence of the level crossings where railway and road traffic intersects. Thus, long waiting time is expected at the level crossings due to the increase in traffic volume and heterogeneity. Furthermore, safety and capacity can be severely compromised by long level crossing closing time. The emphasis of this study is to optimise the rail-road level crossing closing time in order to achieve improved safety and capacity in a heterogeneous railway network. It is imperative to note that rail-road level crossing system assumes the socio-technical and safety critical duality which often impedes improvement efforts. Therefore, thorough understanding of the factors with highest influence on the level crossing closing time is required. Henceforth, data analysis has been conducted on eight active rail-road level crossings found on the southern corridor of the Western Cape metro rail. The spatial, temporal and behavioural analysis was conducted to extract features with influence on the level crossing closing time. Convex optimisation with the objective to minimise the level crossing closing time is formulated taking into account identified features. Moreover, the objective function is constrained by the train's traction characteristics along the constituent segments of the rail-road level crossing, speed restriction and headway time. The results show that developed solution guarantees at most 53.2% and 62.46% reduction in the level crossing closing time for the zero and nonzero dwell time, respectively. Moreover, the correctness of the presented solution has been validated based on the time lost at the level crossing and railway traffic capacity consumption. Thus, presented solution has been proven to achieve at most 50% recovery of the time lost per train trip and at least 15% improvement in capacity under normal conditions. Additionally, 27% capacity improvement is achievable at peak times and can increase depending on the severity of the headway constraints. However, convex optimisation of the level crossing closing time still fall short in level crossing with nonzero dwell time due to the approximation of dwell time based on the anticipated rather than actual value