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1

Machine Activity Recognition Using Clustering Method

Kęsek Marek, Ogrodnik Romuald, Podobińska-Staniec Marta

Inżynieria Mineralna

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2023

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no. 1

327--332

EN

Machine activity recognition is important for benchmarking and analysing the performance of individual machine, machine maintenance needs and automated monitoring of work progress. Additionally, it can be the basis for optimizing manufacturing processes. This article presents an attempt to use object clustering algorithms for recognizing the type of activity in the production complex. For this purpose, data from the production process and the k-means algorithm were used. The most common object clustering algorithms were also discussed. The results and the presented analysis approach demonstrate that this method can be successfully utilized in practice.

PL

Rozpoznawanie czynności realizowanych przez maszyny jest bardzo istotne dla porównania i analizy wydajności poszczególnych maszyn, potrzeb konserwacji maszyn oraz automatycznego monitorowania postępu prac. Dodatkowo, może być ono podstawą do optymalizacji realizowanych procesw produkcyjnych. W niniejszym artykule przedstawiono próbę wykorzystania algorytmów grupowania obiektów do rozpoznawania rodzaju aktywności kompleksu urabiającego. Do tego celu użyto danych pochodzących z procesu produkcyjnego oraz algorytmu k-means. Przyblizono także najpowszechniejsze algorytmy grupowania obiektów. Wyniki olraz zaprezentowany sposb przeprowadzania analizy pokazują, że taki sposob postępowania może być z powodzeniem wykorzystywany w praktyce.

2

Continuous update of business process trees using Continuous Inductive Miner

Pawlak Tomasz P., Górka Bartosz

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2023

|

Vol. 71, nr 1

art. no. e143551

EN

Business processes are omnipresent in nowadays economy: companies operate repetitively to achieve their goals, e.g., deliver goods, complete orders. The business process model is the key to understanding, managing, controlling, and verifying the operations of a company. Modeling of business processes may be a legal requirement in some market segments, e.g., financial in the European Union, and a prerequisite for certification, e.g., of the ISO-9001 standard. However, business processes naturally evolve, and continuous model adaptation is essential for rapid spot and reaction to changes in the process. The main contribution of this work is the Continuous Inductive Miner (CIM) algorithm that discovers and continuously adapts the process tree, an established representation of the process model, using the batches of event logs of the business process. CIM joins the exclusive guarantees of its two batch predecessors, the Inductive Miner (IM) and the Inductive Miner – directlyfollows-based (IMd): perfectly fit and sound models, and single-pass event log processing, respectively. CIM offers much shorter computation times in the update scenario than IM and IMd. CIM employs statistical information to work around the need to remember event logs as IM does while ensuring the perfect fit, contrary to IMd.

3

Methods of process mining and prediction using deep learning

Cieplak Tomasz, Rymarczyk Tomasz, Kłosowski Grzegorz, Maj Michał, Pliszczuk Damian, Rymarczyk Paweł

Przegląd Elektrotechniczny

|

2021

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R. 97, nr 3

146--149

EN

The first part of the article presents analytical methods to understand how processes (security or business) occur and function over time. The second part presents the concept of a predictive system using deep learning methods that would enable the prediction of subsequent operations or steps that are part of the process under consideration. The article was supplemented with a review of scientific publications related to the content and theoretical foundations were provided. The research was of an applied nature, therefore the considerations are based on the example of analysis and forecasts based on historical data contained in process logs.

PL

Pierwsza część artykułu przedstawia metody analityczne pozwalające zrozumieć, w jaki sposób procesy (dotyczące bezpieczeństwa lub biznesu) zachodzą i funkcjonują w czasie. W drugiej części przedstawiono koncepcję systemu predykcyjnego wykorzystującego metody głębokiego uczenia, które umożliwiałyby przewidywanie kolejnych operacji lub kroków wchodzących w skład rozważanego procesu. Uzupełnieniem artykułu był przegląd publikacji naukowych pod kątem merytorycznym oraz podano podstawy teoretyczne. Badania miały charakter aplikacyjny, dlatego rozważania opierają się na przykładzie analiz i prognoz opartych na danych historycznych zawartych w logach procesów.

4

Inferring Unobserved Events in Systems with Shared Resources and Queues

Fahland Dirk, Denisov Vadim, van der Aalst Wil. M.P.

Fundamenta Informaticae

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2021

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Vol. 183, nr 3-4

203--242

EN

To identify the causes of performance problems or to predict process behavior, it is essential to have correct and complete event data. This is particularly important for distributed systems with shared resources, e.g., one case can block another case competing for the same machine, leading to inter-case dependencies in performance. However, due to a variety of reasons, real-life systems often record only a subset of all events taking place. To understand and analyze the behavior and performance of processes with shared resources, we aim to reconstruct bounds for timestamps of events in a case that must have happened but were not recorded by inference over events in other cases in the system. We formulate and solve the problem by systematically introducing multi-entity concepts in event logs and process models. We introduce a partial-order based model of a multi-entity event log and a corresponding compositional model for multi-entity processes. We define PQR-systems as a special class of multi-entity processes with shared resources and queues. We then study the problem of inferring from an incomplete event log unobserved events and their timestamps that are globally consistent with a PQR-system. We solve the problem by reconstructing unobserved traces of resources and queues according to the PQR-model and derive bounds for their timestamps using a linear program. While the problem is illustrated for material handling systems like baggage handling systems in airports, the approach can be applied to other settings where recording is incomplete. The ideas have been implemented in ProM and were evaluated using both synthetic and real-life event logs.

5

Automated Repair of Process Models with Non-local Constraints Using State-Based Region Theory

Kalenkova Anna, Polyvyanyy Artem, Carmona Josep, La Rosa Marcello

Fundamenta Informaticae

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2021

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Vol. 183, nr 3-4

293--317

EN

State-of-the-art process discovery methods construct free-choice process models from event logs. Consequently, the constructed models do not take into account indirect dependencies between events. Whenever the input behaviour is not free-choice, these methods fail to provide a precise model. In this paper, we propose a novel approach for enhancing free-choice process models by adding non-free-choice constructs discovered a-posteriori via region-based techniques. This allows us to benefit from the performance of existing process discovery methods and the accuracy of the employed fundamental synthesis techniques. We prove that the proposed approach preserves fitness with respect to the event log while improving the precision when indirect dependencies exist. The approach has been implemented and tested on both synthetic and real-life datasets. The results show its effectiveness in repairing models discovered from event logs.

6

The K-means Grouping Method as a Mean to Control the Performance of the Production Process

Kęsek Marek

Inżynieria Mineralna

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2020

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no. 1, vol. 1

257--264

EN

The paper presents a concept of using clusters of objects using the k-means method to control the performance of the production process, which runs under variable conditions. The distribution of the production process performance in production cycles grouped according to similarity is the basis for controlling the performance of subsequent production cycles. The practical part of the paper contains an example of calculations carried out according to this concept using the VBA and R languages, and is relates to the bolting process in underground mines.

PL

W artykule przedstawiono koncepcję wykorzystania grupowania obiektów metodą k-średnich do kontroli wydajności procesu produkcyjnego, który przebiega w zmiennych warunkach. Rozkłady wydajności procesu produkcyjnego w pogrupowanych pod względem podobieństwa cyklach produkcyjnych, stanowią podstawę kontroli wydajności kolejnych cykli produkcyjnych. Część praktyczna pracy zawiera przykład obliczeń przeprowadzonych według tej koncepcji z użyciem języka VBA oraz języka R i dotyczy procesu kotwienia w kopalniach podziemnych.

7

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.

8

An Overview of Data Mining and Process Mining Applications in Underground Mining

Brzychczy Edyta

Inżynieria Mineralna

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2019

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R. 21, nr 1

301--314

EN

The underground mining process can be analysed with a data-oriented or process-oriented approach. The first of them is popular and wide known as data mining while the second is still not often used in the conditions of the mining companies. The aim of this paper is an overview of data mining and process mining applications in an underground mining domain and an investigation of the most popular analytic techniques used in the defined analytic perspectives (“Diagnostics and machinery”, “Geomechanics”, “Hazards”, “Mine planning and safety”). In the paper two research questions are formulated: RQ1: What are the most popular data mining/process mining tasks in the analysis of the underground mining process? and RQ2: What are the most popular data mining/process mining techniques applied in the multi-perspective analysis of the underground mining process? In the paper sixty--two published articles regarding to data mining tasks and analytic techniques in the mentioned domain have been analysed. The results show that predominatingly predictive tasks were formulated with regard to the analysed phenomena, with strong overrepresentation of classification task. The most frequent data mining algorithms is comprised of the following: artificial neural networks, decision trees, rule induction and regression. Only a few applications of process mining in analysis of the underground mining process have been found – they were briefly described in the paper.

PL

Celem artykułu jest przegląd zastosowań eksploracji danych (data mining) i procesów (process mining) w analizie procesu wydobywczego w kopalniach podziemnych oraz identyfikacja najpopularniejszych technik analizy danych w tym zakresie. W artykule sformułowano dwa pytania badawcze: P1: Jakie są najpopularniejsze zadania eksploracji danych/eksploracji procesów w analizie procesu wydobywczego w kopalniach podziemnych? oraz P2: Jakie są najpopularniejsze techniki eksploracji danych/eksploracji procesów stosowane w wielowymiarowej analizie procesu wydobywczego w kopalniach podziemnych? W artykule przeanalizowano sześćdziesiąt dwie opublikowane prace dotyczące eksploracji danych w ujęciu zdefiniowanych perspektyw analitycznych (“Diagnostyka i maszyny”, “Geomechanika”, “Zagrożenia”, “Projektowanie kopalń i bezpieczeństwo”). Wyniki pokazują, że w odniesieniu do analizowanych zjawisk formułowano głównie zadania predykcyjne, z silną nadreprezentacją zadania klasyfikacji. Do najczęściej wykorzystywanych technik eksploracji danych należą: sztuczne sieci neuronowe, drzewa decyzyjne, indukcja reguł i regresja. Eksploracja procesów w analizie procesu wydobywczego w kopalniach podziemnych została opisana tylko w kilku artykułach, które pokrótce omówiono.

9

Lucent Process Models and Translucent Event Logs

van der Aalst Wil M. P.

Fundamenta Informaticae

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2019

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Vol. 169, nr 1-2

151--177

EN

A process model is lucent if no two reachable states are enabling the same set of activities. An event log is translucent if each event carries information about the set of activities enabled when the event occurred (normally one only sees the activity performed). Both lucency and translucency focus on the set of enabled activities and are therefore related. Surprisingly, these notions have not been investigated before. This paper aims to (1) characterize process models that are lucent, (2) provide a discovery approach to learn process models from translucent event logs, and (3) relate lucency and translucency. Lucency is defined both in terms of automata and Petri nets. A marked Petri net is lucent if there are no two different reachable markings enabling the same set of transitions, i.e., states are fully characterized by the transitions they enable. We will also provide a novel process discovery technique starting from a translucent event log. It turns out that information about the set of activities is extremely valuable for process discovery. We will provide sufficient conditions to ensure that the discovered model is lucent and show that a translucent event log sampled from a lucent process model can be used to rediscover the original model. We anticipate new analysis techniques exploiting lucency. Moreover, as shown in this paper, translucent event logs provide valuable information that can be exploited by a new breed to process mining techniques.

10

Performance of an automated process model discovery – the logistics process of a manufacturing company

Halaška Michal, Šperka Roman

Engineering Management in Production and Services

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2019

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Vol. 11, no. 2

106--118

EN

The simulation and modelling paradigms have significantly shifted in recent years under the influence of the Industry 4.0 concept. There is a requirement for a much higher level of detail and a lower level of abstraction within the simulation of a modelled system that continuously develops. Consequently, higher demands are placed on the construction of automated process models. Such a possibility is provided by automated process discovery techniques. Thus, the paper aims to investigate the performance of automated process discovery techniques within the controlled environment. The presented paper aims to benchmark the automated discovery techniques regarding realistic simulation models within the controlled environment and, more specifically, the logistics process of a manufacturing company. The study is based on a hybrid simulation of logistics in a manufacturing company that implemented the AnyLogic framework. The hybrid simulation is modelled using the BPMN notation using BIMP, the business process modelling software, to acquire data in the form of event logs. Next, five chosen automated process discovery techniques are applied to the event logs, and the results are evaluated. Based on the evaluation of benchmark results received using the chosen discovery algorithms, it is evident that the discovery algorithms have a better overall performance using more extensive event logs both in terms of fitness and precision. Nevertheless, the discovery techniques perform better in the case of smaller data sets, with less complex process models. Typically, automated discovery techniques have to address scalability issues due to the high amount of data present in the logs. However, as demonstrated, the process discovery techniques can also encounter issues of opposite nature. While discovery techniques typically have to address scalability issues due to large datasets, in the case of companies with long delivery cycles, long processing times and parallel production, which is common for the industrial sector, they have to address issues with incompleteness and lack of information in datasets. The management of business companies is becoming essential for companies to stay competitive through efficiency. The issues encountered within the simulation model will be amplified through both vertical and horizontal integration of the supply chain within the Industry 4.0. The impact of vertical integration in the BPMN model and the chosen case identifier is demonstrated. Without the assumption of smart manufacturing, it would be impossible to use a single case identifier throughout the entire simulation. The entire process would have to be divided into several subprocesses.

11

Enhancing business process event logs with software failure data

Gruszczyński K.

ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes

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2019

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Vol. 8, No 1

27--32

EN

Process mining techniques allow for the analysis of the real process flow. This flow might be disturbed for many reasons, including software failures. It is also possible for failure occurrence to be the consequence of the faulty process execution. A method for measuring the harmfulness of the software failure regarding business processes executed by the user would be a valuable asset for quality and reliability improvement. In this paper, we take the first step towards developing this method by providing a tool for enhancing XES event logs with failure data. We begin with an introduction to this topic and background analysis in the field of failure classification and process mining techniques supporting failure analysis. Then we present our method for merging operational and failure data. By carrying out a case study based on real data, we evaluate our tool and present the aim of our future work.

12

Modelowanie procesów przemysłowych - doświadczenia i perspektywy

Brzychczy E., Napieraj A.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2018

|

z. 125

35--51

PL

W artykule przedstawiono istotę modelowania procesów przemysłowych na przykładzie procesu wydobywczego. Przedstawiono dotychczasowe doświadczenia i opracowane modele wykorzystywane w analizie procesu wydobywczego. Zaprezentowano również nowe możliwości analizy procesów w przedsiębiorstwach przemysłowych, w tym również działających w branży górniczej, w oparciu o dzienniki zdarzeń pochodzące z systemów informatycznych.

EN

The article presents the essence of industrial processes modeling on the example of mining process. Present experiences and developed models used in the analysis of the mining process have been presented. New possibilities of process analysis, based on event logs from information systems in industrial enterprises, including those operating in the mining industry, were also presented.

13

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

|

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.

14

Eksploracja procesów logistycznych z wykorzystaniem pakietu PROM

Janke P.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2018

|

z. 121

165--174

EN

This article presents an analysis of logistics flows using the process exploration technique. On the basis of the collected data, a process model was generated and an evaluation of its functioning was carried out. In the article particular attention was paid to the problem of the form of input data for the example in question

PL

W artykule przedstawiono analizę procesu realizacji zamówienia klienta na nowe części zamienne w przedsiębiorstwie dystrybucji robotów przemysłowych z wykorzystaniem techniki eksploracji procesów. Na podstawie zgromadzonych danych wygenerowano model procesu oraz przeprowadzono ocenę jego funkcjonowania. Szczególną uwagę w artykule zwrócono na problematykę postaci danych wejściowych dla omawianego przykładu.

15

Guidelines for recording transport event logs

Dramski M.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

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2018

|

nr 53 (125)

102--105

EN

A process is an ordered set of related activities taking place in a given time. Processes are present in all branches of the economy, engineering, science, etc. Due to the huge amount of data produced the rapid development of data mining techniques has been observed. Similar methods are also used in the context of processes and are called process mining. The main task of process mining is to create a process model, which is used to reason about the process and to make decisions inside it. The process model may be used to discuss responsibilities, simulations, predictions, etc. The main data structures in process mining are event logs. It is always very important to have correct data which makes creating a reliable process model possible. In this paper the basic guidelines for recording such event logs have been described and conclusions were drawn. The main focus of this research was transport problems.

16

Process Modelling Based on Event Logs

Brzychczy E.

Multidisciplinary Aspects of Production Engineering

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2018

|

Vol. 1, Iss. 1

385--392

EN

Process modelling is a very important stage in a Business Process Management cycle enabling process analysis and its redesign. Many sources of information for process modelling purposes exist. It may be an analysis of documentation related directly or indirectly to the process being analysed, observations or participation in the process. Nowadays, for this purpose, it is increasingly proposed to use the event logs from organization’s IT systems. Event logs could be analysed with process mining techniques to create process models expressed by various notations (i.e. Petri Nets, BPMN, EPC). Process mining enables also conformance checking and enhancement analysis of the processes. In the paper issues related to process modelling and process mining are briefly discussed. A case study, an example of delivery process modelling with process mining technique is presented.

17

Practical Aspects of Event Logs Creation for Industrial Process Modelling

Trzcionkowska A., Brzychczy E.

Multidisciplinary Aspects of Production Engineering

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2018

|

Vol. 1, Iss. 1

77--83

EN

In the paper we address the challenge of applying process mining techniques for discovering models of underground mining operations based on a sensor data. The paper presents practical approach of creation an event log based on industrial sensors data gathered in an underground mine monitoring systems. The proposed approach enables to generate event logs at different generalization levels based on several numbers of discovered stages of devices performance. For discovering process stages data mining techniques such as exploratory data analysis, clustering and classification have been applied. Created event log has been used in one of the process mining tasks - process model discovery.

18

Software architecture design of the information technology for real-time business process monitoring

Batyuk A., Voityshyn V.

ECONTECHMOD : An International Quarterly Journal on Economics of Technology and Modelling Processes

|

2018

|

Vol. 7, No 3

13--22

EN

Having precise understanding of how business processes are performed in real-life is an important input for decision makers and consequently is a strong competitive advantage for an organization. In the constantly changing modern business environment it is crucial to provide that information as soon as possible, preferably in the real-time mode. In practice, such kind of tasks are usually resolved by means of Business Intelligence solutions implemented either from scratch or based upon customizable packages. Despite of the wide range currently available types of data visualizations, modern BI solutions still lacks features to represent data obtained from process-aware systems, for example control flow charts. Current paper is devoted to the information technology for real-time business process monitoring. The represented solution is an extendable software which is based on the lambda architecture and a streaming process discovery technique.

19

New possibilities for process analysis in an underground mine

Brzychczy E., Trzcionkowska A.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

|

2017

|

z. 111

13--25

EN

The paper presents selected issues related to process and risk management in mining companies. For the purpose of identification and analysis of processes in the underground mine, process mining techniques were proposed. An example of their application in analysis of roof support operation process in underground coal mine is presented.

PL

W artykule przedstawiono wybrane zagadnienia dotyczące zarządzania procesami i ryzykiem w przedsiębiorstwach górniczych. Na potrzeby identyfikacji i analizy procesów w kopalni podziemnej zaproponowano wykorzystanie technik eksploracji procesów. Opisano przykład eksploracji procesu działania obudowy zmechanizowanej w kopalni podziemnej.

20

Eksploracja procesów w analizie usług elektronicznych administracji publicznej

Janke P.

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

|

2017

|

z. 101

195--205

PL

W artykule przedstawiono problematykę analizy funkcjonowania usług elektronicznych administracji publicznej. Opisano przykład sposobu wykorzystania rejestrów systemowych potrzebnych do analizy procesów związanych z realizacją e-usług. Szczególną uwagę zwrócono na możliwości metody oraz dostępne narzędzia eksploracji procesów.

EN

This article presents the analysis of the problems in functioning electronic services of public administration. The article describes the possibility of using system logs to analyze the processes related to the implementation of e-services. Special attention in the article is paid to the possibility of process mining methods and tools.