# Augmented Reality Applications in Industry 4.0 Environment
## 4 Results
### Maintenance  
One-third (34%) of the analyzed papers describe the use of AR in industrial maintenance and repair activities. In this type of application, task technicians are pre-equipped with information, instruction sequences or user manuals on their smart devices [41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51]. Another method for performing maintenance activities is to obtain instructions from a remote expert [52; 53; 54]. Moreover, some of the AR applications have been  
Figure 4: European countries from which relevant publications come. Figure 5: Areas of AR application. developed to support diagnosis and to document the repairs made [55; 56; 57; 58]. Maintenance processes can benefit from these technologies, with consequent advances in maintenance and production execution [59]. A typical and illustrative application for maintenance planning by using machine monitoring and AR monitoring is described in [41]. Developed AR mobile applications can visually see the health of the machine, schedule maintenance and support remote maintenance via AR. _Assembly._ The second most common area (24%) of industrial tasks in which AR applications are applied is assembly [35; 60; 61; 62; 63; 64; 65; 66; 67; 68; 69; 70; 71; 72; 73; 74]. In order to reduce assembly time and improve the quality of the assembly process, employees can, in most cases, be provided with some of the following information: the order of connecting the parts; visual help of the position of the next element; technique of connecting the parts. An interesting AR application for mounting a spindle motor on a CNC carving machine is presented in [75]. This smart instruction system with AR support and deep learning-based tools detection is designed to improve worker achievement through assistive instructions. Utilizing this application reduces the completion time and the number of errors compared to manual assembly. _Human robot collaboration._ AR applications (24% of them) can also be used for human robot collaboration. These applications are not only implemented in cases where humans are serving industrial robots but also for programming or trajectory defining as well; this results in the avoidance of collisions [76; 77; 78; 79; 90; 91]. One of the significant advantages in this area is related to the safety of employees and equipment because these applications can show operators the location of unsafe areas [92]. _Manufacturing._ The current manufacturing era is characterized by high demands on industrial performance, flexibility and agile response to customer requirements and the principles of sustainable production. AR has been identified as one of the key technologies important for the transformation from machine dominant manufacturing to digital manufacturing. Almost 10% of developed AR applications are directly related to the realization of smart manufacturing. Some of the benefits of the AR systems have been already proven, including safety [19], the increased precision [93; 94] and reduced assembly time with AR [95; 96]. Since manufacturing is a complex field that consists of product design, material specifications, machining, quality control, etc., all published papers related to manufacturing are classified in the manufacturing area. AR technology can increase product quality, working quality and productivity. AR applications can assist operators in performing quality control tasks. For example, an approach to online quality assessment of polished surfaces is described in [97]. Here, AR technology is used to project a 3D map of quality data, collected during the inspection, directly onto the correlated surface of the real component. With the support of the Industry 4.0 concept, traditional quality is shifting to a discipline in which products are combined with data or so called Quality 4.0. _Training._ Nearly 6% of AR applications have been developed for employee training in industry, mainly for maintenance and assembly tasks, thus avoiding the repetition of errors and further facilitating the optimization of the production cycle [48; 50; 67; 98].