Difficulties in chip breaking and poor machined surface quality are usually considered as the main negative outcomes in conventional drilling (CD). Although researchers have attempted to solve these problems for many years by employing ultrasonic vibrations in the drilling process, studies containing both experimental and theoretical analyses are seldom reported. Based on an in-depth analysis of the kinematic characteristics of ultrasonically assisted drilling (UAD), the conditions for complete geometric chip breaking are derived. The results of the theoretical analysis are verified through a series of experiments, wherein good agreement is found between the experimental and theoretical results. The analyses reveal that UAD has obvious advantages over CD in breaking chips and improving the final surface quality. Additionally, the results show that a low feed rate and an appropriate rotational speed are favorable for chip breaking. The influences of the vibration amplitude, spindle speed, feed rate, and drill bit diameter on the surface roughness are analyzed, and the optimal processing parameters are investigated. The influences of the four factors on the surface roughness in descending order as obtained is amplitude, spindle speed, drill bit diameter, and feed rate. The optimum machining parameters are obtained as 15 μm of amplitude, 450 r/min of spindle speed, 4 mm of drill diameter and 0.08 mm/r of feed rate. Furthermore, a reliable prediction model of surface roughness is established through regression analysis. With this prediction model, the surface roughness under different processing parameters can be approximately predicted.
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This project is supported by National Natural Science Foundation of China (Grant No. 51875097).
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Tian, Y., Zou, P., Yang, X. et al. Study on chip morphology and surface roughness in ultrasonically assisted drilling of 304 stainless steel. Int J Adv Manuf Technol 108, 2079–2090 (2020). https://doi.org/10.1007/s00170-020-05440-5
- 304 stainless steel
- Ultrasonically assisted drilling
- Kinematic characteristics
- Surface roughness
- Optimization of processing parameters
- Prediction model