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.
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