Wyniki wyszukiwania - BazTech

1

Discovering Object-centric Petri Nets

van der Aalst Wil M. P., Berti Alessandro

Fundamenta Informaticae

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2020

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Vol. 175, nr 1-4

1--40

EN

Techniques to discover Petri nets from event data assume precisely one case identifier per event. These case identifiers are used to correlate events, and the resulting discovered Petri net aims to describe the life-cycle of individual cases. In reality, there is not one possible case notion, but multiple intertwined case notions. For example, events may refer to mixtures of orders, items, packages, customers, and products. A package may refer to multiple items, multiple products, one order, and one customer. Therefore, we need to assume that each event refers to a collection of objects, each having a type (instead of a single case identifier). Such object-centric event logs are closer to data in real-life information systems. From an object-centric event log, we want to discover an object-centric Petri net with places that correspond to object types and transitions that may consume and produce collections of objects of different types. Object-centric Petri nets visualize the complex relationships among objects from different types. This paper discusses a novel process discovery approach implemented in PM4Py. As will be demonstrated, it is indeed feasible to discover holistic process models that can be used to drill-down into specific viewpoints if needed.

2

Modelling of processes with use of process mining techniques

Brzychczy E., Napieraj A., Sukiennik M.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2018

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z. 116

23--36

EN

The main purpose of the paper is presentation of new opportunities for process modelling. In the literature review section, Petri nets as one of the formal modelling notation of processes is highlighted and introduction of relatively young research discipline – process mining – is presented. One of the process mining tasks is process model discovery from event logs gathered in informatics systems in enterprise. In the article practical example of process model discovery with ProM software is given with use of real event log from Volvo IT Belgium. In conclusions further opportunities of process mining techniques in process management are emphasized.

3

Odkrywanie procesów po stronie klienta za pomocą dziennika API systemu centralnego

Koryl M., Dymora P., Mazurek M.

Elektronika : konstrukcje, technologie, zastosowania

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2018

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Vol. 59, nr 10

18--20

PL

Powszechnym podejściem budowania systemów informatycznych spełniających złożone wymagania współczesnych użytkowników korporacyjnych jest rozproszenie tradycyjnych systemów monolitycznych na zestaw wielu różnorodnych usług połączonych przez API. środowisko finansowe, zwłaszcza bankowe, nadal jest przykładem "dinozaurów", w których główną rolę odgrywają systemy scentralizowane, ale nawet tam coraz częściej pojawia się dystrybucja przetwarzania danych. Wiedza o procesach zachodzących w firmie, tradycyjnie zakodowana w silnikach workflow, instrukcjach biurowych czy umysłach pracowników, jest teraz "gdzieś" rozproszona i nowo pojawiającym wyzwaniem jest aby ją uchwycić. Proponowane podejście opiera się na logach, które są zwykle tworzone podczas wywołań API. Wiedza ukryta w takich dziennikach może zostać ujawniona i uwidoczniona za pomocą techniki odkrywania procesów. Podano przykład rzeczywistego przedsiębiorstwa finansowego, a wyniki odkrywania procesów przebadano i porównywano z wiedzą dziedzinową.

EN

The common approach to build information systems which meet complex requirements of contemporary enterprise users is to disperse traditional monolith systems into the set of many manifold services connected by APIs. Financial, especially banking environments, are still examples of "dinosaurs" where centralized systems play the leading role, but even there more and more often, distribution of data processing starts to emerge. The knowledge about processes accomplished in the company, traditionally encoded in workflow engines, office instructions or brains of employees, now is dispersed somewhere and the new challenge appears to capture it. The approach proposed, is based on logs which typically are produced during API calls. The knowledge hidden in such logs may be revealed and made explicit using process discovery technique. An example of the real financial enterprise is taken and results of process discovery are studied and compared with a domain knowledge.

4

Incremental Process Discovery using Petri Net Synthesis

Badouel E., Schlachter U.

Fundamenta Informaticae

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2017

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Vol. 154, nr 1/4

1--13

EN

Process discovery aims at constructing a model from a set of observations given by execution traces (a log). Petri nets are a preferred target model in that they produce a compact description of the system by exhibiting its concurrency. This article presents a process discovery algorithm using Petri net synthesis, based on the notion of region introduced by A. Ehrenfeucht and G. Rozenberg and using techniques from linear algebra. The algorithm proceeds in three successive phases which make it possible to find a compromise between the ability to infer behaviours of the system from the set of observations while ensuring a parsimonious model, in terms of fitness, precision and simplicity. All used algorithms are incremental which means that one can modify the produced model when new observations are reported without reconstructing the model from scratch.

5

Extracting process-related information from ERP systems for process discovery

Fliegner W.

Research in Logistics & Production

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2014

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Vol. 4, No. 4

315--329

EN

This paper discusses various aspects that should be considered when defining and executing extraction process-related information from the source data (ERP system) to an event log. This includes trace and event selection, as well as important project decisions that should be made beforehand. The basic idea of a proposed approach is demonstrated by performing a case study which is related to a standard sales order processing, that is, business process from sales quotation through sales order and delivery to invoicing. For this processes we showed the characteristics of the event logs, and the models we can discover.

6

Process Discovery and Conformance Checking Using Passages

van der Aalst W. M. P., Verbeek H. M. W.

Fundamenta Informaticae

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2014

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Vol. 131, nr 1

103--138

EN

The two most prominent process mining tasks are process discovery (i.e., learning a process model from an event log) and conformance checking (i.e., diagnosing and quantifying differences between observed and modeled behavior). The increasing availability of event data makes these tasks highly relevant for process analysis and improvement. Therefore, process mining is considered to be one of the key technologies for Business Process Management (BPM). However, as event logs and process models grow, process mining becomes more challenging. Therefore, we propose an approach to decompose process mining problems into smaller problems using the notion of passages. A passage is a pair of two non-empty sets of activities (X, Y) such that the set of direct successors of X is Y and the set of direct predecessors of Y is X. Any Petri net can be partitioned using passages. Moreover, process discovery and conformance checking can be done per passage and the results can be aggregated. This has advantages in terms of efficiency and diagnostics. Moreover, passages can be used to distribute process mining problems over a network of computers. Passages are supported through ProM plug-ins that automatically decompose process discovery and conformance checking tasks.

7

Process Discovery using Integer Linear Programming

van der Werf J.M.E.M., van Dongen B.F., Hurkens C.A.J., Serebrenik A.

Fundamenta Informaticae

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2009

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Vol. 94, nr 3/4

387-412

EN

The research domain of process discovery aims at constructing a process model (e.g. a Petri net) which is an abstract representation of an execution log. Such a model should (1) be able to reproduce the log under consideration and (2) be independent of the number of cases in the log. In this paper, we present a process discovery algorithm where we use concepts taken from the language-based theory of regions, a well-known Petri net research area. We identify a number of shortcomings of this theory from the process discovery perspective, and we provide solutions based on integer linear programming.