1 Research Method

1.1 Design Framework

The workflow was structured to isolate the contribution of each manufacturing stage—additive forming, CNC machining, and finishing. A cylindrical test component with stepped shoulders and internal channels was selected to ensure sensitivity to geometric deviation. All manufacturing parameters were kept constant across repeated trials to ensure replicability.

1.2 Data Sources

Dimensional and surface data were obtained from 30 samples produced under identical process settings. Measurements were taken with a coordinate measuring machine (CMM), a laser confocal microscope, and process-embedded sensors that logged temperature and spindle load. The selection of these devices was based on their ease of calibration and ability to reproduce measurement accuracy across sessions.

1.3 Equipment and Models

• 3D Printer: SLM system, 200 W fiber laser, 30 µm layer thickness
• CNC Machine: 5-axis machining center with automatic tool compensation
• Finishing Tools: CBN milling head, diamond abrasive media
• Data Model: Regression models for deviation prediction, validated through repeated-measure ANOVA
• All parameters used in the machining and finishing steps are listed in Appendix A to ensure full experimental reproducibility.

2 Results and Analysis

2.1 Dimensional Accuracy

Table 1 shows the mean dimensional deviation across the three conditions.
Hybrid samples maintained a deviation below ±0.015 mm, compared to ±0.042 mm for additive-only parts. This improvement aligns with studies reporting that material redistribution during post-machining compensates for layer-wise heat accumulation effects [1].

2.2 Surface Roughness

Hybrid finishing reduced Ra from an average of 12.4 µm to 1.8 µm, as summarized in Figure 1. The finishing step eliminated partially fused particles and reduced stair-step artifacts.

2.3 Process Efficiency

Cycle time analysis indicates a 23% reduction in overall processing time compared with conventional subtractive machining alone. Tool load logs showed a 9–12% decrease in spindle torque due to the smaller machining allowance left after additive preforming.

2.4 Comparative Interpretation

Cross-reference with earlier research [2,3] shows that the dimensional improvement aligns with expectations for hybrid manufacturing. However, the magnitude of surface-quality enhancement is higher than previously reported, likely due to refined temperature control in the additive stage.

3 Discussion

3.1 Interpretation of Findings

The results demonstrate that hybrid workflows compensate for thermal instability typical of metal powder fusion. The machining allowance designed into the printed geometry effectively removes heat-induced deformation zones. Lower tool load suggests reduced mechanical stress on cutting edges, contributing to cycle-time stability.

3.2 Limitations

The study focused on a single geometry and metal alloy. Results may vary with more complex internal structures or materials with different coefficient-of-thermal-expansion behaviors. Additionally, only one finishing tool type was evaluated.

3.3 Practical Implications

Industries requiring rapid iterations—such as robotics, aerospace components, and customized medical devices—can benefit from hybrid manufacturing to achieve precision without full subtractive workflows. The reduction in machining time is particularly relevant for small-batch custom orders.

4 Conclusion

The integrated approach combining 3D printing, CNC machining, and surface finishing improves dimensional accuracy and surface consistency while reducing cycle time. The workflow addresses geometric distortion caused by additive manufacturing and supports tighter tolerance requirements. Future work may investigate multi-material components, adaptive finishing toolpaths, and model-driven process optimization.