## 3 Results and Discussion
### Answering RQ1 and RQ2
The results showed that AR technology could help in productivity enhancement, maintenance time reduction and quality assurance of maintenance tasks compared to other traditional tools [233]. Similarly, Fiorentino et al. [147] and Uva et al. [142] conducted a series of studies comparing AR-based instructions to 2D documents for assembly, finding that AR-based instructions dramatically increased assembly efficiency [147]. Nevertheless, AR-assisted instructions also enhanced the assembly order memorization of operators [142]. Considering the quality field, the AR-supported quality process has evolved from a basic indicating tool of projecting 2D information onto processed parts to support in situ quality inspection of welding spots using Spatial AR (SAR) [209] to a higher level that combines real-time 3D metrology data and the MR glasses HoloLens for in-line assessing of the quality of parts' polished surfaces [8]. In another scenario, SAR is also applied to improve the repeatability of manual spot-welding in the automotive industry to assure the precision and accuracy of the process [201]. Several types of cues visualized with different sizes and colors (red, green, white, yellow and blue) are defined and superimposed on the welding area to support operators in focusing the weld guns onto the correct welding spot. In a real case at the Igamo company in Spain, AR technology was adopted to work as an innovative Poka-Yoke tool. In the packaging sector, setting up the die cutters is crucial to ensuring the final quality of the cardboard. However, this process is error-prone, causing defects and low-quality products. Thus, correction templates, which are made of paper marked with tapes using different colors, are applied to balance the press differences of die cutters. These correction templates are made based on the traditional Poka-Yoke method for error prevention. The templates are then digitalized and directly projected onto the die cutter, resulting in warehouse cost reduction, which comes from storing correction templates, and data loss prevention, which is caused by damaged templates [198]. Additionally, 3D models or CAD are implemented into AR tools for design discrepancies [206] and design variations inspection [195]. In a quality assurance of sheet metal parts in the automotive industry, an interactive SAR system integrating point cloud data is implemented and validated [234]. In recent studies [30, 210], an AR-based solution for improving the original quality control procedure used on the shop floor to check error deviation in several key points of an automotive part has been investigated and developed to automatically generate virtual guidance content for operators during measuring tasks. The main problem of the original procedure is that quality control consists of repetitive and precise tasks, which are frequently complex, requiring a high mental workload for the operator. Although quality control tests are facilitated with documents of static media such as video recording, photos or diagrams to support the operators, they still need to divide the attention between the task and the documents, which also lack in-time feedback. This leads to a slowing of the processes as well as movement waste due to the operator's need to move between a workstation and a computer to validate measuring results after a certain number of tests. In detail, the original quality control is to measure deviation errors of an automotive part at specific positions in accordance with the essential specification of clients. A wireless measurement device (a comparator) is manually positioned by operators at specific locations for evaluation. During the nine measures, the operators need to move back and forth between the working cell and a display device to verify the measurements. For the AR-based solution, a camera is mounted on a tripod, pointing downwards at the gauge where the test takes place.