868 research outputs found

    Process mining : conformance and extension

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    Today’s business processes are realized by a complex sequence of tasks that are performed throughout an organization, often involving people from different departments and multiple IT systems. For example, an insurance company has a process to handle insurance claims for their clients, and a hospital has processes to diagnose and treat patients. Because there are many activities performed by different people throughout the organization, there is a lack of transparency about how exactly these processes are executed. However, understanding the process reality (the "as is" process) is the first necessary step to save cost, increase quality, or ensure compliance. The field of process mining aims to assist in creating process transparency by automatically analyzing processes based on existing IT data. Most processes are supported by IT systems nowadays. For example, Enterprise Resource Planning (ERP) systems such as SAP log all transaction information, and Customer Relationship Management (CRM) systems are used to keep track of all interactions with customers. Process mining techniques use these low-level log data (so-called event logs) to automatically generate process maps that visualize the process reality from different perspectives. For example, it is possible to automatically create process models that describe the causal dependencies between activities in the process. So far, process mining research has mostly focused on the discovery aspect (i.e., the extraction of models from event logs). This dissertation broadens the field of process mining to include the aspect of conformance and extension. Conformance aims at the detection of deviations from documented procedures by comparing the real process (as recorded in the event log) with an existing model that describes the assumed or intended process. Conformance is relevant for two reasons: 1. Most organizations document their processes in some form. For example, process models are created manually to understand and improve the process, comply with regulations, or for certification purposes. In the presence of existing models, it is often more important to point out the deviations from these existing models than to discover completely new models. Discrepancies emerge because business processes change, or because the models did not accurately reflect the real process in the first place (due to the manual and subjective creation of these models). If the existing models do not correspond to the actual processes, then they have little value. 2. Automatically discovered process models typically do not completely "fit" the event logs from which they were created. These discrepancies are due to noise and/or limitations of the used discovery techniques. Furthermore, in the context of complex and diverse process environments the discovered models often need to be simplified to obtain useful insights. Therefore, it is crucial to be able to check how much a discovered process model actually represents the real process. Conformance techniques can be used to quantify the representativeness of a mined model before drawing further conclusions. They thus constitute an important quality measurement to effectively use process discovery techniques in a practical setting. Once one is confident in the quality of an existing or discovered model, extension aims at the enrichment of these models by the integration of additional characteristics such as time, cost, or resource utilization. By extracting aditional information from an event log and projecting it onto an existing model, bottlenecks can be highlighted and correlations with other process perspectives can be identified. Such an integrated view on the process is needed to understand root causes for potential problems and actually make process improvements. Furthermore, extension techniques can be used to create integrated simulation models from event logs that resemble the real process more closely than manually created simulation models. In Part II of this thesis, we provide a comprehensive framework for the conformance checking of process models. First, we identify the evaluation dimensions fitness, decision/generalization, and structure as the relevant conformance dimensions.We develop several Petri-net based approaches to measure conformance in these dimensions and describe five case studies in which we successfully applied these conformance checking techniques to real and artificial examples. Furthermore, we provide a detailed literature review of related conformance measurement approaches (Chapter 4). Then, we study existing model evaluation approaches from the field of data mining. We develop three data mining-inspired evaluation approaches for discovered process models, one based on Cross Validation (CV), one based on the Minimal Description Length (MDL) principle, and one using methods based on Hidden Markov Models (HMMs). We conclude that process model evaluation faces similar yet different challenges compared to traditional data mining. Additional challenges emerge from the sequential nature of the data and the higher-level process models, which include concurrent dynamic behavior (Chapter 5). Finally, we point out current shortcomings and identify general challenges for conformance checking techniques. These challenges relate to the applicability of the conformance metric, the metric quality, and the bridging of different process modeling languages. We develop a flexible, language-independent conformance checking approach that provides a starting point to effectively address these challenges (Chapter 6). In Part III, we develop a concrete extension approach, provide a general model for process extensions, and apply our approach for the creation of simulation models. First, we develop a Petri-net based decision mining approach that aims at the discovery of decision rules at process choice points based on data attributes in the event log. While we leverage classification techniques from the data mining domain to actually infer the rules, we identify the challenges that relate to the initial formulation of the learning problem from a process perspective. We develop a simple approach to partially overcome these challenges, and we apply it in a case study (Chapter 7). Then, we develop a general model for process extensions to create integrated models including process, data, time, and resource perspective.We develop a concrete representation based on Coloured Petri-nets (CPNs) to implement and deploy this model for simulation purposes (Chapter 8). Finally, we evaluate the quality of automatically discovered simulation models in two case studies and extend our approach to allow for operational decision making by incorporating the current process state as a non-empty starting point in the simulation (Chapter 9). Chapter 10 concludes this thesis with a detailed summary of the contributions and a list of limitations and future challenges. The work presented in this dissertation is supported and accompanied by concrete implementations, which have been integrated in the ProM and ProMimport frameworks. Appendix A provides a comprehensive overview about the functionality of the developed software. The results presented in this dissertation have been presented in more than twenty peer-reviewed scientific publications, including several high-quality journals

    Structure discovery techniques for circuit design and process model visualization

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    Graphs are one of the most used abstractions in many knowledge fields because of the easy and flexibility by which graphs can represent relationships between objects. The pervasiveness of graphs in many disciplines means that huge amounts of data are available in graph form, allowing many opportunities for the extraction of useful structure from these graphs in order to produce insight into the data. In this thesis we introduce a series of techniques to resolve well-known challenges in the areas of digital circuit design and process mining. The underlying idea that ties all the approaches together is discovering structures in graphs. We show how many problems of practical importance in these areas can be solved utilizing both common and novel structure mining approaches. In the area of digital circuit design, this thesis proposes automatically discovering frequent, repetitive structures in a circuit netlist in order to improve the quality of physical planning. These structures can be used during floorplanning to produce regular designs, which are known to be highly efficient and economical. At the same time, detecting these repeating structures can exponentially reduce the total design time. The second focus of this thesis is in the area of the visualization of process models. Process mining is a recent area of research which centers on studying the behavior of real-life systems and their interactions with the environment. Complicated process models, however, hamper this goal. By discovering the important structures in these models, we propose a series of methods that can derive visualization-friendly process models with minimal loss in accuracy. In addition, and combining the areas of circuit design and process mining, this thesis opens the area of specification mining in asynchronous circuits. Instead of the usual design flow, which involves synthesizing circuits from specifications, our proposal discovers specifications from implemented circuits. This area allows for many opportunities for verification and re-synthesis of asynchronous circuits. The proposed methods have been tested using real-life benchmarks, and the quality of the results compared to the state-of-the-art.Els grafs són una de les representacions abstractes més comuns en molts camps de recerca, gràcies a la facilitat i flexibilitat amb la que poden representar relacions entre objectes. Aquesta popularitat fa que una gran quantitat de dades es puguin trobar en forma de graf, i obre moltes oportunitats per a extreure estructures d'aquest grafs, útils per tal de donar una intuïció millor de les dades subjacents. En aquesta tesi introduïm una sèrie de tècniques per resoldre reptes habitualment trobats en les àrees de disseny de circuits digitals i mineria de processos industrials. La idea comú sota tots els mètodes proposats es descobrir automàticament estructures en grafs. En la tesi es mostra que molts problemes trobats a la pràctica en aquestes àrees poden ser resolts utilitzant nous mètodes de descobriment d'estructures. En l'àrea de disseny de circuits, proposem descobrir, automàticament, estructures freqüents i repetitives en les definicions del circuit per tal de millorar la qualitat de les etapes posteriors de planificació física. Les estructures descobertes poden fer-se servir durant la planificació per produir dissenys regulars, que son molt més econòmics d'implementar. Al mateix temps, la descoberta i ús d'aquestes estructures pot reduir exponencialment el temps total de disseny. El segon punt focal d'aquesta tesi és en l'àrea de la visualització de models de processos industrials. La mineria de processos industrials es un tema jove de recerca que es centra en estudiar el comportament de sistemes reals i les interaccions d'aquests sistemes amb l'entorn. No obstant, quan d'aquest anàlisi s'obtenen models massa complexos visualment, l'estudi n'és problemàtic. Proposem una sèrie de mètodes que, gràcies al descobriment automàtic de les estructures més importants, poden generar models molt més fàcils de visualitzar que encara descriuen el comportament del sistema amb gran precisió. Combinant les àrees de disseny de circuits i mineria de processos, aquesta tesi també obre un nou tema de recerca: la mineria d'especificacions per circuits asíncrons. En l'estil de disseny asíncron habitual, sintetitzadors automàtics generen circuits a partir de les especificacions. En aquesta tesi proposem el pas invers: descobrir automàticament les especificacions de circuits ja implementats. Així, creem noves oportunitats per a la verificació i la re-síntesi de circuits asíncrons. Els mètodes proposats en aquesta tesi s'han validat fent servir dades obtingudes d'aplicacions pràctiques, i en comparem els resultats amb els mètodes existents

    Semantics and Verification of UML Activity Diagrams for Workflow Modelling

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    This thesis defines a formal semantics for UML activity diagrams that is suitable for workflow modelling. The semantics allows verification of functional requirements using model checking. Since a workflow specification prescribes how a workflow system behaves, the semantics is defined and motivated in terms of workflow systems. As workflow systems are reactive and coordinate activities, the defined semantics reflects these aspects. In fact, two formal semantics are defined, which are completely different. Both semantics are defined directly in terms of activity diagrams and not by a mapping of activity diagrams to some existing formal notation. The requirements-level semantics, based on the Statemate semantics of statecharts, assumes that workflow systems are infinitely fast w.r.t. their environment and react immediately to input events (this assumption is called the perfect synchrony hypothesis). The implementation-level semantics, based on the UML semantics of statecharts, does not make this assumption. Due to the perfect synchrony hypothesis, the requirements-level semantics is unrealistic, but easy to use for verification. On the other hand, the implementation-level semantics is realistic, but difficult to use for verification. A class of activity diagrams and a class of functional requirements is identified for which the outcome of the verification does not depend upon the particular semantics being used, i.e., both semantics give the same result. For such activity diagrams and such functional requirements, the requirements-level semantics is as realistic as the implementation-level semantics, even though the requirements-level semantics makes the perfect synchrony hypothesis. The requirements-level semantics has been implemented in a verification tool. The tool interfaces with a model checker by translating an activity diagram into an input for a model checker according to the requirements-level semantics. The model checker checks the desired functional requirement against the input model. If the model checker returns a counterexample, the tool translates this counterexample back into the activity diagram by highlighting a path corresponding to the counterexample. The tool supports verification of workflow models that have event-driven behaviour, data, real time, and loops. Only model checkers supporting strong fairness model checking turn out to be useful. The feasibility of the approach is demonstrated by using the tool to verify some real-life workflow models

    Process mining and verification

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    A communicating Petri net model for the design of concurrent asynchronous modules

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    Automated synthesis of delay-insensitive circuits

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    Statecharting Petri nets

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    Statecharting Petri nets

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    A Petri net-occam based methodology for the development of dependable distributed control software.

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    Analysis of flexible manufacturing cells (FMCs) shows their requirement for flexible, correct, reliable, safe and distributed control. A comparison of the state of the art in software engineering for parallel systems, and an examination of safety related systems, reveal a need for formal and rigorous techniques at all stages in the software life cycle. However, parallel software, safety related software and formal techniques are complex. It is better to avoid faults rather than eliminate or tolerate them, and although less flexible, avoidance is often simpler to implement. There is a need for a tool which overcomes many of these complexities, and this thesis discusses and defines such a tool in the form of a methodology. The novelty of the work is in the combination of the core goals to manage these issues, and how the strategies guide the user to a solution which will not deadlock and which is comprehensible. Place-transition Petri nets are an ideal representation for designing and modelling the interaction of concurrent (and distributed) processes. Occam is a high level real time parallel language designed to execute on one or a network of transputers. Transputers are processing, memory and communication building blocks, and, together with occam, are shown to be suitable for controlling and communicating the control as the DCS in FMCs. The methodology developed in this thesis adopts the mathematically based tools of Petri nets, occam and transputers, and, by exploiting their structural similarities, incorporates them in a steps and tasks to improve the development of correct, reliable and hence safe occam code. The four steps: identify concurrent and sequential operations, produce Petri net graphs for all controllers, combine controller Petri net graphs and translate Petri net graphs into occam; are structured around three core goals: Petri net/occam equivalence, comprehensibility and pro-activity; which are manifest in four strategies: output-work-backwards, concurrent and sequential actions, structuralise and modularise, and deadlock avoidance. The methodology assists in all stages of the software development life cycle, and is applicable to small DCSs such as an FMC. The methodology begins by assisting in the creation of DCS requirements from the manufacturing requirements of the FMC, and guides the user to the production of dependable occam code. Petri nets allow the requirements to be specified as they are created, and the methodology's imposed restrictions enable the final Petri net design to be translated directly into occam. Thus the mathematics behind the formal tools is hidden from the user, which should be attractive to industry.The methodology is successfully applied to the example FMC, and occam code to simulate the FMC is produced. Due to the novelty of the research, many suggestions for further work are given
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