## 3 Results and Discussion
### Answering RQ3 to RQ5  
This section considers all selected articles to establish a broad view about current AR development tools in manufacturing, thus making conclusions about how those tools could be utilized for developing AR solutions for the quality sector. RQ3: What are available tools to develop AR-based applications for quality sector? * Software design  
Regarding Layer 2 Implementation, the number of articles dealing with the software side (150 articles, 75%) and hardware side is nearly balanced (148 articles, 74%). These numbers once more emphasize that AR technology has reached its mature point, where the improvement in either the AR software side or the AR hardware side would boost the technology adoption speed for AR solutions in manufacturing. There are a dominant number of Interaction design articles dealing with high functional user interfaces (95 articles, or 47.5% of the total), which is understandable due to high demands in interactive activities on the shop-floor level in manufacturing. Content design, with 40 articles, or 20% of the total, is the second dominant interest when considering software design. There are 4 articles, or 2% of the total, and 12 articles, or 6% of the total, dedicated to Agent-based AR and Knowledge-based AR systems, respectively. Although these two percentages of Agent-based AR and Knowledge-based AR are not significant, they are essential for the further integration of AI elements into AR systems supporting manufacturing in long term. The articles of each category relating to this sublayer Software design are listed in Table 12 and the number of articles of each category over the period 2010-2021 is depicted in Figure 12.  
There has been a steady interest in Interaction design for AR-based in a manufacturing context over the years, which reached its peak in 2019. This is a positive trend for the long-term adoption of AR solutions in manufacturing be-cause manufacturing at the shop-floor level consists of lots of interactive activities between operators, especially interaction of operators with working spaces as well as and operators that need essential manufacturing information/data in the right manner of time [8; 63; 195]. Content design is the second dominant category in software design for AR solutions in manufacturing. In 2018-2020, AR content design especially focusing on visual elements and the conversion of manufacturing actions into standard symbols for AR content are key points [104; 112; 129; 186]. Knowledge-based AR applications are designed to incorporate the domain knowledge of experts during the authoring phase to create a knowledge-based system (KBS) built on technical documents, manuals and other relevant documentation of the authoring domain (assembly, maintenance, quality control, etc.) [30; 138; 191]. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Classification Criteria** & **References** & **Intelligent Elements** \\ \hline \multirow{8}{*}{Intelligent AR solution} & [37; 155; 190] & Digital twins \\ \cline{2-3}  & [72; 74; 116; 164] & Deep learning, CNN, AI \\ \cline{1-1} \cline{2-3}  & [219; 225] & Industrial IoT \\ \cline{1-1} \cline{2-3}  & [49; 102; 127; 132] & Big Data, Cloud computing, Cloud architecture, Expert system for decision making, Ubiquitous system \\ \hline \hline \end{tabular}
\end{table} 
Table 11: Layer 5 Intelligent AR relevant articles 2010–2021. Agent-based AR utilizes the available entities of a system and their attributes to integrate into the AR solutions, supporting autonomy decision making [102; 190]. * Display devices  
This subsection presents an overview of the most popular display devices used in the development of AR solutions in manufacturing, which provide good references for the development of AR-assisted quality activities later. Table 8 and Figure 13 depict in detail the main display devices mentioned and applied in the selected and analyzed articles for this SLR. The implementation of one device rather than another depends on the purpose justification of the AR application.