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

Halaška Michal, Šperka Roman

Engineering Management in Production and Services

2019

Vol. 11, no. 2

106--118

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.

Investigation of agent-based simulation of malicious software

Chumachenko D., Yakovlev S.

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

2016

Vol. 5, No 4

61--67

Epidemics of malicious software are actual problem and network worms are one of the most important issues. Identifying trends in network worm distribution, finding the factors that influence the spread of the Internet worm will help to identify the effective preventive and precautionary measures to prevent epidemics of malicious software. To solve the problem of the development of advanced security mechanisms against network worms, different approaches to modeling the spreading of worms have been studied. Deterministic models of propagation of computer viruses in a heterogeneous network, taking into account its topological and architectural features have been analyzed and improved. Agent-based model of network worm propagation have been developed. Simulated model is based on epidemic approach to modeling. SAIDR structure of agent-based model has been used for simulation of malicious software of “network worm” type. A comparative study of developed mathematical models has been conducted. Comparative graphs of the dependence of the infected nodes number on the time of the computer system functioning in the propagation of the epidemic have been built. Research carried out by the example of the Code Red worm propagation.

Volunteer computing simulation using repast and mason

Byrski A., Feluś M., Gawlik J., Jasica R., Kobak P., Jankowski G., Nawarecki E., Wroczyński M., Majewski P, Krupa T., Strychalski J.

Computer Science

2013

Vol. 14 (1)

153--172

Volunteer environments usually consist of a large number of computing nodes, with highly dynamic characteristics, therefore reliable models for a planning of the whole computing are highly desired. An easy to implement approach to modelling and simulation of such environments May employ agent-based universal simulation frameworks, such as RePast or MASON. In the course of the paper the above-mentioned simulation frame Works are adapter to suport simulation of volunteer computing. After giving implementation details, selected results concerning computing time and speedup are given and are compared with the ones obtained from an actual volunteer environment.