Business Process Simulation Using Coloured Petri Nets

Äriprotsesside juhtimine on tänapäeva maailmas muutunud järjest olulisemaks tänu suurenevatele nõudmistele protsesside tõhusamaks muutmisel. Protsesside juhtimisega üritatakse leida võimalikke kitsaskohti, tõsta tootlikust ja vähendada vajadust ressursside järjele. Paljud protsesside modelleerimise vahendid toetavad lisaks protsesside modelleerimisele mudelite juurutamist ning simulatsioone. Simulatsioonid on üks parimaid tehnikaid protsesside efektiivsemaks muutmisel. Enamus äriprotsesside modelleerimise standardeid ei toeta simulatsioone (k.a. de facto standard BPMN). Mitmed protsesside modelleerimise vahendid võimaldavad simulatsioone, kuid simulatsioonimootor on peidetud nende vahendite sisse. See piirab simulatsioonimootorite laiendatavust ning protsesside simulatsioonides tuleb läbi ajada tarkvara vahenditega. Kuid modelleerimistarkvara võimalused on võrreldes reaalse maailma situatsioonidega väga piiratud. Antud töö eesmärgiks on välja pakkuda eelpool mainitud probleemile üks võimalik lahendus – BPMN meta-mudeli laiendus simulatsiooni atribuutidega. Töös kasutatakse simulatsioonimootorit CPN Tools, mis baseerub Coloured Petri Nets (CPN) modelleerimis-keelel. CPN on loodud spetsiaalselt diskreetsete süsteemide simulatsiooni keeleks. Esmalt tehakse ülevaade BPMN standardist ning kahest levinumast BPMN modelleerimise vahendist – IBM WebSphere Modeller ja IPT Commerce. Järgnevalt antakse lühiülevaade Petri Nets ja CPN mudelitest ning CPN Tools modelleerimisvahendist. Kasutades olemasolevate vahendite analüüsist saadud kogemusi, laiendatakse BPMN standardi meta-mudelit simulatsioonide meta-mudeliga. Seejärel kirjeldatakse kuidas saada simulatsiooni andmetega täiendatud BPMN mudelist CPN mudel ning demonstreeritakse erinevaid võimalusi CPN mudelite simuleerimiseks kasutades CPN Tools vahendeid. Töös kirjeldatud simulatsiooni meta-mudel ja BPMN mudeli elementide teisendamine CPN mudeli konstruktsioonideks on esitatud üldiselt, sest eesmärgiks oli testida välja pakutava lahenduse võimalikkust. CPN Tools sai valitud simulatsioonimootoriks sellepärast, et tema mudelid on kirjeldatud kasutades XML-i. Töö edasiarendusena pakub autor välja BPMN mudelitest CPN mudelite automaatse konverteri loomist.Business process management plays an increasingly important role in the business world as it promotes effectiveness and efficiency in business operations. The simulation of business processes is one of the most versatile techniques for analyzing business processes quantitatively in order to identify and remove performance bottlenecks. The graphical representation of business process models has proven to be a very effective tool for presenting information to business stakeholders, including business analysts and system developers. Unfortunately most of the graphical business process modeling standards (including de facto standard BPMN) do not support attaching simulation information to the models. Major business process modelling tools and suites still provide ability to add simulation data and execute those models. However, only models designed with the tools themselves can be simulated and no extensibility mechanism is provided to add new features or change the pre-built simulation and reporting options. This paper proposes a meta-model for specifying simulation scenarios on the top of the BPMN meta-model. Also, the paper advocates using CPN Tools as an open and extensible business process model simulator. The paper provides an initial design of a transformation from BPMN process models to CPN models. The proposed design has been validated through one fully-worked case study

Business Process Improvement of Production Systems Using Coloured Petri Nets

The quality of information systems affects the company's business performance. Therefore, it is necessary to analyze business processes to determine any discrepancies between the planned business processes and the actual ones. Based on the results of this analysis, the business process can be improved. The fundamental factor of manufacturing companies is production process. In reality, there are many discrepancies between the actual business processes with the pre-planned, so that there should be analyzed. The analysis can be performed by modeling the business process using Coloured Petri Nets (CPN). In this study, the objectives are to determine the level of conformance checking of business processes, reachability graph and the bottleneck analysis. The results of the analysis are used to construct a recommended model. Based on the analysis of the case study, e.g. a steel industry in Indonesia, the recommended model has a better value than initial model

Enhancing workflow-nets with data for trace completion

The growing adoption of IT-systems for modeling and executing (business) processes or services has thrust the scientific investigation towards techniques and tools which support more complex forms of process analysis. Many of them, such as conformance checking, process alignment, mining and enhancement, rely on complete observation of past (tracked and logged) executions. In many real cases, however, the lack of human or IT-support on all the steps of process execution, as well as information hiding and abstraction of model and data, result in incomplete log information of both data and activities. This paper tackles the issue of automatically repairing traces with missing information by notably considering not only activities but also data manipulated by them. Our technique recasts such a problem in a reachability problem and provides an encoding in an action language which allows to virtually use any state-of-the-art planning to return solutions

Seventh Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools, Aarhus, Denmark, October 24-26, 2006

This booklet contains the proceedings of the Seventh Workshop on Practical Use of Coloured Petri Nets and the CPN Tools, October 24-26, 2006. The workshop is organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark. The papers are also available in electronic form via the web pages: http://www.daimi.au.dk/CPnets/workshop0

What's next? : operational support for business process execution

In the last decade flexibility has become an increasingly important in the area of business process management. Information systems that support the execution of the process are required to work in a dynamic environment that imposes changing demands on the execution of the process. In academia and industry a variety of paradigms and implementations has been developed to support flexibility. While on the one hand these approaches address the industry demands in flexibility, on the other hand, they result in confronting the user with many choices between different alternatives. As a consequence, methods to support users in selecting the best alternative during execution have become essential. In this thesis we introduce a formal framework for providing support to users based on historical evidence available in the execution log of the process. This thesis focuses on support by means of (1) recommendations that provide the user an ordered list of execution alternatives based on estimated utilities and (2) predictions that provide the user general statistics for each execution alternative. Typically, estimations are not an average over all observations, but they are based on observations for "similar" situations. The main question is what similarity means in the context of business process execution. We introduce abstractions on execution traces to capture similarity between execution traces in the log. A trace abstraction considers some trace characteristics rather than the exact trace. Traces that have identical abstraction values are said to be similar. The challenge is to determine those abstractions (characteristics) that are good predictors for the parameter to be estimated in the recommendation or prediction. We analyse the dependency between values of an abstraction and the mean of the parameter to be estimated by means of regression analysis. With regression we obtain a set of abstractions that explain the parameter to be estimated. Dependencies do not only play a role in providing predictions and recommendations to instances at run-time, but they are also essential for simulating the effect of changes in the environment on the processes, both locally and globally. We use stochastic simulation models to simulate the effect of changes in the environment, in particular changed probability distribution caused by recommendations. The novelty of these models is that they include dependencies between abstraction values and simulation parameters, which are estimated from log data. We demonstrate that these models give better approximations of reality than traditional models. A framework for offering operational support has been implemented in the context of the process mining framework ProM