## 2 Materials and Methods
### Literature Review and Identification of Key Attributes of Industry 4.0 for SMEs
According to the authors of [25], the implementation of the basic attributes of Industry 4.0 in medium-sized enterprises requires:  
1. collection of all available data from the company's facilities,
2. protect data against unauthorised access,
3. evaluate usable data,
4. prepare employees for changes in companies. To incorporate a more advanced Industry 4.0 strategy in medium-sized companies, it will be necessary to:  
1. visualise data,
2. create a virtual representation of the entire system to identify and eliminate weaknesses in production,
3. design autonomous production systems [25]. The authors of the case study [26] incorporated data from four industries and evaluated the most important parameters of Industry 4.0 from economic, social and environmental points of view using a multi-context method that integrates a hesitant fuzzy set, cumulative prospect theory, and VIKOR for evaluating the degree of Industry 4.0 technologies. The results of the method are shown in the Figure 3 down below [26]. On x-axis, there are the individual technologies used in Industry 4.0, and the y-axis indicates the score with which these technologies ended up in the calculations. The data were used by industry as well as a World Economic Forum White Paper. They found that in the case of the manufacturing sector, the implementation of mobile technologies, namely 5G, cloud computing, sensors and drives and Big Data analytics, had the highest final value. In [5], using the Kaizen method, Big Data with analytics, Cloud computing, virtual simulation, and virtual reality are identified as key Industry 4.0 technologies, providing decentralisation, real-time capability, interoperability and virtualisation. The article shows how Lean Manufacturing practices are closely related to Industry 4.0 technologies. The authors of [27] consider virtual reality, 3D printing and IoT to be the key technologies in Industry 4.0. They deal intensively with the education of students in these three areas and bring a methodology for incorporating them into school curricula. They point to the need to train new and retrain old workers in key areas of Industry 4.0. A large survey [28] describes much of the Industry 4.0 technology--3D printing, Horizontal and Vertical Integration, Virtual Reality, Autonomous Robotics, Simulation, IIoT, CPS, Big Data analytics and Cybersecurity. The authors consider Horizontal and Vertical Integration to improve logistics and supply chains, robotics to increase productivity and quality and reduce production times, and Simulation, for instance a digital twin, to improve prediction. Among the strongest pillars are IIoT, especially with the support of 5G technology, Big Data analytics providing smart manufacturing and providing Business Intelligence to improve business models, and Cybersecurity to secure all production against external attacks. Implementing these technologies provides increased profits, a better supply chain and faster production. Article [29] highlights Big Data and Cloud Computing as the key technologies of the Industry 4.0 concept. The use of both technologies is independent of the size of the company, and companies should include them in their business-innovation strategies. The authors would like to orient their future research to Big Data, with a focus on Cybersecurity. They emphasise the need to update existing Big Data standards and define new ones to ensure interoperability and complementarity. Article [30] describes Big Data as a critical component for efficient work with data generated by CPS. Future research should focus on global design from data collection and processing to forecasting future events, optimisation and management, and production plans beyond CPS for Industry 4.0 objectives.