## 3 Result of Identification of Key Attributes of Industry 4.0  
The summarised studies and research clearly show the necessary attributes for the needs of digitisation and the shift of production of small- and medium-sized enterprises to a level close to that of a Smart Factory:  
1. Big Data, which most of the research has evaluated as a key attribute in digitisation,2. Artificial Intelligence, in connection with data processing and the expansion of production automation,
3. IoT, as a key element in data collection and processing,
4. Cloud Computing, especially needed for small- and medium-sized businesses to increase data processing and backup speeds, but large businesses can also benefit from it,
5. Simulation, especially creating a digital twin for predictive maintenance purposes,
6. Cybersecurity to protect data, either from outside attacks or from data loss. Figure 4 shows an Industry 4.0 diagram for SMEs with the identified attributes. The remaining Industry 4.0 technologies are mentioned less frequently in the studies. Horizontal and Vertical System Integration is also possible to unify the systems used in companies and to share critical data more efficiently. By incorporating the mentioned technologies, companies could get significantly closer to the level of a Smart Factory, but for small- and medium-sized companies, it is still necessary to address the financial side and ensure the cheapest possible transition to Industry 4.0. The results and references are summarised in Table 1. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Attributes** & **Quantity** & **References** \\ \hline Artificial Intelligence & 6 & [PERSON], et al., 2021 [19], [PERSON], et al., 2016 [21], \\  & 6 & [PERSON], et al., 2021 [22], [PERSON], et al., 2019 [25], \\  & & [PERSON], et al., 2017 [33], [PERSON], et al., 2020 [34] \\ \hline Big Data & 17 & [PERSON], et al., 2021 [3], [PERSON], et al., 2022 [4], \\  & & [PERSON], et al., 2020 [5], [PERSON], et al., 2018 [6], [PERSON], et al., 2021 [19], [PERSON], et al., 2022 [20], \\  & & [PERSON], et al., 2016 [21], [PERSON], et al., 2021 [22], \\  & & [PERSON], et al., 2019 [25], [PERSON], et al., 2020 [27], \\  & & [PERSON], et al., 2021 [28], [PERSON], et al., 2018 [29], \\  & & [PERSON], et al., 2017 [33], [PERSON], et al., 2020 [34], \\  & & [PERSON], et al., 2018 [39], [PERSON], 2017 [40], \\  & & [PERSON], et al., 2019 [41] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Quantity of individual attributes of Industry 4.0 marked as important in scientific articles. Figure 4: Industry 4.0 scheme for SMEs. Figure 5 shows the number of articles in the Web of Science database for the year 2021 when single-individual attributes are entered as keywords. As the figure shows, the highest number of articles occurred when the Simulation attribute was entered, followed by AI, Big Data, Horizontal and Vertical Integration and IoT. The graph, like Table 1, confirms the importance of the identified attributes. The difference is visible in the attribute Cybersecurity, with 1588 articles. This number does not diminish the importance of the attribute but shows the need to focus scientific research on Cybersecurity.