# A Systematic Literature Review of Industry 4.0 Technologies within Medical Device Manufacturing
## 4 Discussion  
The findings presented in the literature review revealed that the main features of the application of Industry 4.0 technologies in manufacturing setting are real-time overview, decentralization, ability to connect devices via IoT and gather real-time data, cloud computing for computationally costly models and transparency and trackability of individual products (Figure 6A). As smart manufacturing solutions tend to be costly investments, a lower level of expense is a preferrable feature of various solutions [51; 70; 92; 112]. Moreover, as displayed in Figure 7A, out of the 104 papers analyzed, 29 were relating to the field of AI/ML, 17 to IoT, 12 to modeling of various scenarios, 9 focused on digital twin concepts and 8 on cloud computing. Out of the 14 articles covering AI algorithms, 8 are using CNN and 4 ANN, as depicted in Figure 7B. Due to the nature of the algorithm, CNN can be used in various ways for the automation of processes. As CNN is popular choice for image pattern classification, it can be used for detection of user actions in assembly lines as in [PERSON] et al. and [PERSON] et al., or applied to timeseries problems, such as done in the works by [PERSON] et al., [PERSON] et al., or to multi-sensor information fusion that is then converted to image, as in the work by [PERSON] et al. [48; 87; 91; 95; 108]. In a similar manner, ANN can accurately predict various problems in manufacturing setting, such as inspection by exception, identifying specific process with 100% accuracy, detecting haptic feedback forecasting events with 99% accuracy, or detecting production faults and machine wear with 99.82% accuracy [39; 47; 73; 93]. Moreover, [PERSON] et al. showed that neural network models outperform regression models for manufacturing related pattern detections, which can explain the preference of them [47]. Aside from ML/DL solutions, six papers discuss the use of blockchain. In this instance, Ethereum smart contracts were the most dominant choice for studies focusing on blockchain solutions (Figure 7B). Ethereum blockchain is open ended and decentralized, which allows the smart contracts to solve problems such as transaction processing and real time data availability [85]. Figure 6: (**A**): Most commonly occurring features in papers. (**B**): Most frequent application domains in papers. Figure 7: (**A**): Number of occurrences of technology categories. (**B**): Most frequently applied technologies in articles. It is notable that XR solutions are not that prominent research topics within the selected papers (Figure 7A). The main obstacles with XR are that the solutions tend to be hard to generalize, costly, and not user friendly [42, 113]. Lastly, a considerable portion of the digital twin studies are on framework level, for example in the works by [PERSON] et al., [PERSON] et al., and [PERSON] et al. [21, 40, 58]. This is because, with the advancements of IoT, the communication between physical and digital twin is realized [51]. In this way, digital twins can add value to the business by predicting equipment failure and remote monitoring of manufacturing process [60, 104]. Despite the search query specified in Section 2.1, many of the SLR results were not in the field of medical devices, as visible in Figure 6B. Due to the grading approach taken, as previously outlined in Tables 1 and 2, some of the articles that were not directly linked to medical device manufacturing were not filtered out. For that reason, some of the application domains include automotive production and CNC milling machine. These papers were still considered, as for instance CNC milling machine was used by studies defining the 5-dimensional manufacturing digital twin and visualization of the digital twin using manufacturing, both of which can be on a conceptual level transferred to medical device manufacturing [21, 105]. The articles listed under manufacturing theme cover various shop-floor solutions for general smart manufacturing, like optimization of information collection [15] or CPS self-awareness [8].