# A Review on Recent Trends and Applications of IoT in Additive Manufacturing
## 2 IOT-Enabled 3D Printing Applications
### Digital Twin
This DT feature will assist in  
Figure 4: Digital twin evolution timeline. Figure 5: The working of the digital twin model [41]. improving the flexibility, design, printing quality, and printing style of contemporary 3D printing. Sensors and other features of DT are used to acquire data from the physical 3D component so that it may be integrated into the system. As a result, the IoT-enabled 3D printing industry is finding its place by enhancing the capabilities of contemporary AM procedures. Because of this connectivity, the sensors are now able to send the data that they have collected to a user. The data that is acquired is of the utmost importance when it comes to determining and fixing any issues that may arise throughout the process of 3D printing. There will be many digital twins representing various physical realities in the coming years, such as people, processes, places, and objects. This technology is driving optimal performance and innovation in a variety of industries. DTs are now changing their wings from lab experiments to practical applications where we can see that the United States Air Force (USAF) is working on Reengineering Aircraft Structural Life Prediction using a digital twin. The proposed model utilizes DT in integrating the computation of structural deflections and temperatures in response to flight conditions for developing safety factors in maintenance and operations. This shows the importance of DTs in the occupancy of the 3D printing industrial world. As a relatively new form of technology, its application is becoming more common in a variety of settings, such as the industrial sector, the automotive industry, the medical field, smart cities, and other areas, as shown in Figure 6.  
Additive manufacturing applications, especially in metallic materials, are still facing several limitations before becoming fully functional in several manufacturing processes; however, much research is being performed for implementing IoT-integrated AM in DT and will be the solution to these problems. A study on the feasibility of DT in AM indicates that the creation of a data centralization tool, which is installed when needed and acts as the foundation of the DT to enable automatic data flow between different installed sensors and allow the generation of decisions for controlling several processes with the help of controllers, makes it fully viable as a widespread manufacturing process. DT excels at helping streamline process efficiency, as we find in industrial environments with co-functioning machine systems in additive manufacturing, as shown in Figure 7.  
Figure 6: Applications of digital twin [42]. Although there are other traditional systems, such as drafting and modeling software, analysis, and control strategies, there is higher scope for the automation and optimization of twinning physical models in order to encounter problems through DT (see Figure 7 above). A digital twin, which involves building a bridge between the physical and virtual worlds of printing, can cut down on the number of trial-and-error tests, reduce the risk of defects, shorten the amount of time that elapses between the design stage and the production stage, and make printing more metallic products more cost-effective [43]. The Cyber-Physical Production System (CAPP) acts as a platform for integrating several virtual twins into the physical systems [44; 45]. DT helps additive manufacturing in terms of product design, process optimization, supply chain management, quality management, cross-discipline collaboration, predictive maintenance, and analyzing the customer experience. Thus, implementing the IoT in additive manufacturing will help the process to consume less power, ensure a safe manufacturing environment, increase the rate of production, allow for mass production and long-term viability, reduce material wastage, and make the process more cost-effective.