Effect of Novel Finishing Strategies on the Machinability and Geometrical Tolerances of Free-Form Curved Surfaces

Document Type : Manufacturing and Production

Author

Associate Professor, Faculty of Engineering, University of Maragheh, Maragheh, Iran

Abstract

Achieving high surface quality, dimensional accuracy, and productivity in free-form and complex 3D geometries is crucial, especially in industries such as aerospace and medicine. This study investigates the effects of three modern finishing strategies—spiral, curve machining, and steep and shallow—on surface roughness, form error (as a geometric tolerance), and material removal rate. Simulations were performed using PowerMILL software, and experimental tests were conducted on a CNC milling machine. The results showed that the steep and shallow strategy delivered the best performance in terms of surface quality and geometric accuracy, achieving a surface roughness of 0.077𝜇𝑚 and a form error of 0.0184mm, with improvements of 27.49% and 76.86%, respectively, compared to other strategies. Conversely, the spiral strategy exhibited the highest productivity, with a material removal rate of 0.1325gr/s and a machining time of 30 minutes, demonstrating a 19.8% improvement in material removal rate compared to the lowest-performing strategy. These findings emphasize the importance of selecting a finishing strategy that balances surface quality, geometric accuracy, and process productivity to meet the specific requirements of each workpiece.

Graphical Abstract

Effect of Novel Finishing Strategies on the Machinability and Geometrical Tolerances of Free-Form Curved Surfaces

Highlights

  • Free-form components were manufactured using innovative machining strategies.
  • The choice of the proper strategy depends on the component’s application and the importance level of quality, accuracy, and speed criterion.
  • The results indicate an improvement of 19%-76% in the performance of modern strategies compared to traditional ones.

Keywords

Main Subjects

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References

[1] Dodok T, Čuboňová N, Císar M, Kuric I, Zajačko I. Utilization of strategies to generate and optimize machining sequences in CAD/CAM. Procedia Engineering. 2017; 192: 113-118. DOI: https://doi.org/10.1016/j.proeng.2017.06.020.
[2] Zamani J, Hemati MH, Morsalu R. Statistical analysis on dimensional accuracy of wax patterns of gas turbine blades produced by rapid tooling. Journal of Aerospace Mechanics. 2015; 11(3): 59-68. DOR: https://dor.isc.ac/dor/20.1001.1.26455323.1394.11.2.3.4
[3] Davoudi B, Eskandari B. Surface roughness optimization in machining of n-155 iron-nickel-base superalloy using the Taguchi method. Journal of Aerospace Mechanics. 2015; 11(2): 43-53. DOR:  https://dor.isc.ac/dor/20.1001.1.26455323.1394.11.2.5.6
[4] Pashmforoush F, Ebrahimi Araghizad A, Budak E. Physics-informed tool wear prediction in turning process: A thermo-mechanical wear-included force model integrated with machine learning. Journal of Manufacturing Systems. 2024; 77: 266-283. DOI: https://doi.org/10.1016/j.jmsy.2024.09.008.
[5] Pilecco RO, Vaz Machry R, Baldi A, Paulo J Tribst M, Sarkis-Onofre R, Valandro LF, Kleverlaan CJ, Scotti N, Pereira GKR. Influence of CAD-CAM milling strategies on the outcome of indirect restorations: A scoping review. The Journal of Prosthetic Dentistry. 2024; 131(5): 811-820. DOI: https://doi.org/10.1016/j.prosdent.2024.02.021.
[6] Tianchi D, Yingguang L, Xu L. An inexact subgraph matching algorithm for subpart retrieval in NC process reuse. Journal of Manufacturing Systems. 2023; 67: 410-423. DOI: https://doi.org/10.1016/j.jmsy.2023.02.011.
[7] Bosch G, Ender A, Mehl A. A 3-dimensional accuracy analysis of chairside CAD/CAM milling processes. The Journal of Prosthetic Dentistry. 2014; 112(6): 1425-1431. DOI: https://doi.org/10.1016/j.prosdent.2014.05.012.
[8] Pimenov DY, Kiran M, Khanna N, et al. Review of improvement of machinability and surface integrity in machining on aluminum alloys. International Journal of Advcanced Manufacturing Technology. 2023; 129: 4743–4779. DOI: https://doi.org/10.1007/s00170-023-12630-4.
[9] Demirpolat H, Binali R, Kuntoğlu M, et al. The influences of alloying elements and processing conditions on the machinability of wrought aluminium alloys: A literature review. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. 2024;0(0). DOI: https://doi.org/10.1177/09544089241290395.
[10] Sah MK, Vijaya A. Experimental studies on reflective finishing of aluminum sheet by CNC abrasive lapping. Materials and Manufacturing Processes. 2023; 39(4): 546–562. DOI: https://doi.org/10.1080/10426914.2023.2244034.
[11] Saravanakumar A, Karthikeyan SC, Dhamotharan B, Gokul kumar V. Optimization of CNC turning parameters on aluminum alloy 6063 using Taguchi robust design. Materials Today: Proceedings. 2018; 15(2): 8290-8298. DOI: https://doi.org/10.1016/j.matpr.2017.11.520
[12] Sarkhosh R, Kazemi Nasrabadi M, Nazari Googli Sh.  The Effect of Machining Strategies on the Surface Roughness and Milling Time of Part with Convex, Concave, and Smooth Surfaces. Modares Mechanical Engineering. 2024;24(03):189-201. DOI: https://doi.org/10.3390/app122010638.
[13] Varga J. Tóth T, Kaščák Ľ, Spišák E. The effect of the machining strategy on the surface accuracy when milling with a ball end cutting tool of the aluminum alloy AlCu4Mg. Applied Sciences. 2022; 12: 10638. DOI: https://doi.org/10.3390/app122010638.
[14] Varga J, Spišák E, Gajdos I, Mulidrán P.  Comparison of Milling Strategies in the Production of Shaped Surfaces. Advances in Science and Technology Research Journal. 2022; 16(6): 267–274. DOI: https://doi.org/10.12913/22998624/156817.
[15] Ramazani Sales H, Amir Abadi H. Investigation of tool path strategies for three-axes and five-axes milling with federate optimization. Modares Mechanical Engineering. 2015; 15(13): 150-157. DOI: https://doi.org/20.1001.1.10275940.1394.15.13.86.6.
[16] Hasanpour H, Shajari S, Rasti A, Sadeghi MH. Investigation of milling strategies effect on microhardness of a typical curved surface.   Modares Mechanical Engineering. 2015, 15(2): 34-40. DOI: https://doi.org/20.1001.1.10275940.1394.15.2.26.4.
[17] Makulavičius M, Petkevičius S, Rožėnė J, Dzedzickis A, Bučinskas V. Industrial Robots in Mechanical Machining: Perspectives and Limitations. Robotics. 2023; 12(6):1-27. DOI: https://doi.org/10.3390/robotics12060160.
[18] Lebon N, Tapie L, Vennat E, Mawussi B. Influence of CAD/CAM tool and material on tool wear and roughness of dental prostheses after milling. Journal of Prosthetic Dentistry. 2015;114(2):236-47. DOI: https://doi.org/10.1016/j.prosdent.2014.12.021.
[19] Mebrahitom A, Rizuan D, Azmir M, Nassif. Effect of high-speed milling tool path strategies on the surface roughness of Stavax ESR mold insert machining. IOP Conference Series: Materials Science and Engineering. 2016; 114:1-6. DOI: https://doi.org/10.1088/1757899X/114/1/012006.
[20] Ramos AM, Relvas C, Simoes JA. The influence of finishing milling strategies on texture, roughness and dimensional deviations on the machining of complex surfaces. Journal of materials processing technology. 2003; 136:209-216. DOI: https://doi.org/10.1016/S0924-0136(03)00160-2.
[21] Scandola L, Erber M, Hagenlocher P, Steinlehner F, Volk W. Reconstruction of the bending line for free-form bent components extracting the centroids and exploiting NURBS curves. Graphical Models. 2024; 135: 101227. DOI: https://doi.org/10.1016/j.gmod.2024.101227.
[22] Ji S, Lei L, Zhao J, Lu X, Gao H. An adaptive real-time NURBS curve interpolation for 4-axis polishing machine tool. Robotics and Computer-Integrated Manufacturing. 2021; 67: 102025. DOI: https://doi.org/10.1016/j.rcim.2020.102025.
[23] Michal F, Peter I, Miroslav T, František K, Melichar K. Use of cam strategies for tool movement in machining surfaces of various shapes. Acta Mechanica Slovaca. 2020; 24(3):40-48. DOI: https://doi.org/10.21496/ams.2020.020.
Aerospace Mechanics
Volume 21, Issue 1 - Serial Number 79
Serial No. 79, Spring Quarterly
June 2025
Pages 61-74

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History

  • Receive Date: 28 October 2024
  • Revise Date: 17 December 2024
  • Accept Date: 28 December 2024
  • Publish Date: 22 May 2025

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