## 4 Results
continuously provided real-time feedback, allowing the operator to make immediate corrections to depth or slope without external assistance. Moreover, the excavation trajectory analysis revealed that MG excavation followed a more structured and predictable sequence, with the excavation carried out in well-defined layers. Conversely, the conventional method showed greater variability in dig patterns, with operators often revisiting previously excavated areas to make corrections. This discrepancy suggests that MG promoted a more systematic and efficient excavation strategy. The fill factor analysis revealed distinct differences in excavation action between the conventional and machine guidance methods (Figure 6). The MG operator consistently achieved higher fill factor scores per bucketload, maintaining five points for extended periods within each footing. Toward the final leveling stage, the score decreased to one or two points, reflecting fine adjustments carried out to achieve precise excavation depth before immediate transition to the next footing. In contrast, the conventional method exhibited greater variability in fill factor scores, initially with a high fill factor score of five points, followed by a progressive decline that included two, three, and four points, forming a distinctive W-shaped excavation pattern before reaching the fine leveling stage. To better illustrate the trends in fill factor score, Table 4 summarizes the fill factor scores and dig counts for both the MG and conventional methods, broken down into the early, mid, and final phases of excavation for each footing (Footing #1 to Footing #4). These data offer a more granular view of how each method performed at distinct stages of the excavation process. Overall, MG tended to produce higher fill factors in the early to mid stages of excavation, followed by a reduction in the final phase as the operators performed finer leveling. By contrast, the conventional method showed greater variability;  
Figure 5: Excavator positions (**a,b**) and excavation time at each position (**c,d**) for the four footings, comparing machine guidance and conventional methods. In (**c,d**), bars are color-coded by footing: #1 (blue), #2 (orange), #3 (gray), and #4 (green). the fill factor values oscillated more sharply, and dig counts often exceeded those of MG, indicating the need for repeated adjustments. Statistical analyses were conducted to compare the performance outcomes, specifically, the fill factor scores, between the conventional (n = 68) and MG (n = 57) groups. Independent samples \(t\)-tests, with variance heterogeneity assessed via [PERSON]'s test, revealed a statistically significant difference in mean scores between the two groups (t = \(-\)2.63, \(p\) = 0.01). Furthermore, non-parametric Mann-Whitney U tests confirmed a significant difference in median values (U = 1435.0, \(p\) = 0.009), with the use of MG resulting in significantly higher fill factor scores compared with the conventional approach. These findings demonstrate that the implementation of MG produced a notable improvement in performance metrics, underscoring its potential impact in practical applications. Additionally, over-ex excavation occurred more frequently with the conventional method, as evidenced by the necessity of backfilling operations, which were assigned a fill factor score of \(-\)1. This issue was notably observed at Footing #2, where the signal person identified excessive excavation depth requiring corrective backfilling. Such corrections not only increased the excavation time but also reduced overall efficiency. These patterns suggest that MG excavation can enable faster and more confident excavation as the operator receives continuous real-time feedback, eliminating the uncertainty associated with traditional signal-based verification. This ability to consistently maintain a high fill factor without excessive corrections indicates that MG can enhance operator confidence and precision, leading to more efficient excavation.