# Augmented Reality for PCB Component Identification and Localization
## 6 Discussion
Future research should extend this framework to evaluate the applicability of AR systems in more interactive and sequential assembly steps, where motor precision, timing, and multi-modal feedback are involved. Recent work has demonstrated the potential of AR to support such complex operations by enhancing multi-modal perception and interaction [40] and optimizing task performance in precise manual assembly scenarios [41]. The precision and stability of 3D markers were essential for successful task completion. While markers performed well under optimal conditions, their precision declined at steeper angles. Participants recommended increasing marker size and contrast and reducing flickering to improve stability. These findings align with previous ergonomic research emphasizing display clarity and visual marker stability as key to effective AR deployment [27; 36]. A key limitation of this study is the relatively small sample size (\(n=10\) per experiment), which constrains the statistical power of both within-group and between-group comparisons. Subgroup analyses, such as those based on user expertise or component size, lack sufficient statistical resolution to support definitive conclusions and may reflect individual variability or task-specific factors. In addition, long-term adoption of AR systems in industrial settings depends not only on performance metrics but also on user acceptance and training effectiveness--factors increasingly recognized in immersive technology research [42]. While the findings offer preliminary insights into AR-assisted component identification performance, they require confirmation through studies with larger and more diverse participant cohorts to enable statistically robust inferences and broader generalizability across industrial applications [43]. In addition, Experiment 1 participants were recruited from the same industrial company, and the PCB used in both experiments represented a single, moderately complex design. While this allowed for consistency in experimental control and reduced confounding variables, it limits the ecological validity of the findings. Likewise, the non-domain participants in Experiment 2 represent a narrow user profile, which may not reflect the diversity of skills and roles found in real industrial environments. Future research should incorporate a broader range of PCB types and layouts, as well as participant groups from multiple industrial domains, to better evaluate the generalizability and robustness of AR-based component identification systems across varied production scenarios. A further limitation in Experiment 1 is the use of a fixed task sequence, with all participants performing the traditional method before the AR-based task. This design may have introduced order effects, such as fatigue or reduced attention in the second phase, potentially confounding the observed performance differences. While the faster performance in Run 1 may reflect such effects, it cannot be disentangled from method-specific influences. Future research may consider using counterbalanced or randomized task sequences, such as Latin square designs [44], Williams designs [45], or randomized complete block designs [46] to better isolate genuine method effects and reduce sequence-related bias. While the present study provides controlled insights into AR-based component identification, translating these findings into industrial-scale deployment involves additional challenges. In actual manufacturing environments, PCBs are often more densely populated, with components varying in size, shape, and labeling clarity [47; 48]. Lighting conditions can also fluctuate, affecting marker detection and spatial mapping accuracy [47]. Moreover, technicians may use AR systems for extended periods during multi-step assembly or inspection tasks, where cumulative physical strain and marker drift may become more pronounced [20]. These contextual factors were not fully replicated in the current experimental setup.