## 6 Conclusions  
This study investigated the impact of machine guidance (MG) on excavation efficiency by comparing conventional and MG footing excavation processes. The experimental results provide clear evidence that the MG system significantly improved excavation performance by enhancing accuracy, reducing relocation frequency, and optimizing workflow continuity. The findings reveal that MG excavation reduced total excavation time by 27.3% compared with the conventional method. This efficiency gain was attributable to the more precise excavation cycles, as indicated by the higher average fill factor score. The ability to maintain a higher fill factor for extended periods suggests that MG can enable more confident and controlled excavation, minimizing unnecessary corrections and rework. Another key observation was the relocation pattern. The MG system reduced the number of relocations by approximately 40%, allowing operators to remain in position for longer durations while efficiently completing excavation. In contrast, the conventional method required frequent repositioning to verify the excavation depth manually, disrupting the workflow continuity. The data also suggest that the MG operations were more assertive in their excavation strategy, reaching target depths more quickly and transitioning to fine leveling phases with minimal hesitation. Furthermore, the trajectory analysis demonstrated that the MG excavation followed a structured and predictable pattern, while the conventional excavation exhibited a W-pattern, reflecting cautious adjustments to avoid over-excavation. This cautious approach adopted in the conventional excavation often led to inefficiencies, with some instances requiring backfilling due to over-excavation, adding additional time and effort to the process. The real-time feedback provided by MG playeda crucial role in these performance improvements. By continuously displaying the depth information, MG eliminated the need for manual verification by a signal person, reducing interruptions and allowing operators to execute tasks with greater certainty. Additionally, while both excavation methods faced challenges in performing precise leveling at extended boom-arm reaches, the MG operators exhibited greater control and confidence in their adjustments, demonstrating the system's potential to enhance precision even under difficult excavation conditions. Despite the promising results, several limitations of the present study must be acknowledged. Due to the inherent challenges of conducting controlled experiments in an active construction environment--such as the high operational costs of heavy machinery and the need to avoid interference with ongoing construction activities--the sample size was necessarily limited. The within-subject pilot test design, while effective in controlling external variables, may not fully capture the variability present in larger-scale or multi-day operations. These constraints limit the generalizability of the current findings. Future research should aim to overcome these limitations by expanding the sample size, conducting multi-site experiments over longer time periods, and exploring the application of machine guidance systems across a broader range of construction tasks. Additionally, incorporating qualitative methods such as operator interviews and field observations could offer further insights into the decision-making processes and subjective experiences associated with machine guidance. From a broader perspective, these findings suggest that MG systems are not only able to enhance excavation efficiency but can also reduce operator workload and reliance on external guidance. By minimizing the need for frequent repositioning and manual depth verification, MG technology can improve overall site productivity, particularly in large-scale earthwork projects where efficiency and accuracy are critical.