# Region-Based Approach for Machining Time Improvement in Robot Surface Finishing
## 5 Discussion and Conclusions  
This study delves into robot kinematics' capabilities and velocity performance in machining workpieces with semi-complex surface geometries. We initiated our analysis using an augmented robot Jacobian kinematics matrix incorporating workpiece surface constraints, facilitating a well-known manipulability analysis. Building on this fundamental analysis, a task-constrained method for calculating surface path directions represented by VVF was developed, which enables generating speed-optimal machining paths and implemented it into region-based machining, which enhanced the efficiency of the machining process. While existing studies on robotic hammer peening have primarily focused on the mechanical and structural enhancements of workpieces' surfaces, our research introduces a novel approach by emphasizing the optimization of machining time--a critical factor often overlooked in traditional methodologies. Our study demonstrates that region-based machining strategies enhanced efficiency over traditional single-direction machining significantly, reducing the machining time from 5% to 37%, depending on the stepover distance. Notably, the greatest improvements were observed as the stepover distance decreased, indicating that region-based strategies become increasingly effective with denser toolpaths. This suggests that the benefits of a region-based approach might not justify the implementation complexity for applications with larger stepovers. In particular, while machining times for workpiece WP2 showed only modest improvements of about 5% at the largest stepover distance, this can be attributed to the increased number of regions that required more frequent transitions between machining zones. However, as the stepover distance decreased, the machining times for WP2 tended to converge with those of WP1, highlighting the potential for significant efficiency gains in more finely detailed machining tasks. Figure 10: Joint velocity infinity norm representation for four different placements and two different workpieces: (**a**) WP1, (**b**) WP2. Further enhancements were realized through optimal workpiece positioning, which improved machining times by an additional 4-16%. Although these gains may appear modest, the primary challenge with using lower-capability collaborative robots lies not just in optimizing the position for efficiency, but in finding any feasible position where successful machining can occur. In conclusion, our validation analysis discovered slight discrepancies in machining and robot joint speeds between the model-based design calculations and machining paths, which may have occurred due to low surface model point density, leading us to recommend reducing the surface finishing speeds at a certain margin to ensure safe operation within the robot's kinematical limits. Looking ahead, our research will focus on refining the region-based machining approach by integrating a compactness index into the clustering algorithm. This enhancement aims to create more compact machining regions, minimizing transitions between them, to reduce machining times further and improve operational efficiency. Optimizing the order in which these regions are machined could also streamline the process by reducing non-productive tool movements between regions. Beyond these improvements, the next step also involves applying these optimized strategies to robots in real-world manufacturing settings, allowing for a practical validation and further refinement of the proposed method. The presented work was carried out with significant contributions of both authors. T.P. : conceptualization, methodology, software, validation, and writing--original draft preparation; A.H.: methodology, software, writing--review and editing, and supervision. All authors have read and agreed to the published version of the manuscript. This research was funded by the Slovenian Research Agency (ARRS) under a Grant for the Research Program P2-0028. Not applicable. Data availability StatementData are contained within the article.