Research article
● Open access
Optimization of Machining Parameters for Polyamide 6: A Comprehensive Review of Surface Roughness Influences Using Experimental and Statistical Methods
Abstract
Background: Polyamide 6 (PA6) is a widely used engineering thermoplastic known for its excellent mechanical properties, thermal stability, and wear resistance. However, its semi-crystalline structure and low thermal conductivity present significant challenges during machining operations, particularly in achieving optimal surface finish. Surface roughness is a critical quality indicator that affects the functional performance, fatigue life, and aesthetic appearance of machined polymer components. Understanding the complex interactions between machining parameters and environmental conditions is essential for optimizing the turning process of PA6.
Objective: This comprehensive review investigates the influence of machining parameters—cutting velocity (Vc), feed rate (FR), and depth of cut (Dc)—and machining environments—dry (D), compressed air (A), and air-water mixture (A+W)—on the surface roughness (Ra) of Polyamide 6 during turning operations. The study aims to identify the most influential parameters, quantify their percentage contributions, and determine the optimal combination for achieving minimum surface roughness.
Methods: A systematic experimental approach was combined with statistical analysis using Taguchi Experiment Design (TED) and Analysis of Variance (ANOVA). Experiments were conducted on a CU-500 lathe using a carbide cutting tool (Mitsubishi CNMG 120408 UE6020) with a PCLNR 2525 M12 tool holder. PA6 samples of 40 mm diameter and 500 mm length were machined at three levels for each parameter: cutting velocity (125, 200, 250 m/min), feed rate (0.05, 0.1, 0.15 mm/rev), depth of cut (2, 4, 6 mm), and three machining environments. Surface roughness was measured using an SRT5000 roughness tester. The Taguchi L9 orthogonal array was employed to design experiments efficiently, and the signal-to-noise ratio (SNR) with "smaller-is-better" criterion was used for optimization. ANOVA quantified the percentage contribution of each parameter.
Results: The experimental results demonstrate that feed rate is the most dominant factor affecting surface roughness, contributing 61% of the total effect. Machining environment contributes 15%, depth of cut 13%, and cutting velocity 11%. Lower feed rates (0.05 mm/rev) consistently produced superior surface finishes (Ra = 1.2 μm), while higher feed rates (0.15 mm/rev) resulted in rougher surfaces (Ra = 2.5 μm). The air-water mixture environment significantly improved surface quality compared to dry and compressed air conditions due to enhanced cooling and lubrication effects. Lower cutting velocities (125-200 m/min) and shallower depths of cut (2 mm) also contributed to better surface finishes by reducing cutting forces, vibration, and thermal deformation. The optimal combination for minimum surface roughness was identified as: cutting velocity of 125 m/min, feed rate of 0.05 mm/rev, depth of cut of 2 mm, and air-water mixture environment, achieving a minimum Ra of 1.2 μm.
Conclusion: This comprehensive investigation establishes that feed rate is the primary control parameter for achieving high-quality surface finishes in PA6 turning operations. The air-water mixture environment provides significant improvements in surface quality through effective cooling and lubrication. The study provides manufacturers with evidence-based guidelines for selecting optimal machining parameters to enhance product quality, reduce costs, and extend tool life. The findings contribute to the broader understanding of polymer machining and offer a foundation for developing predictive models and process optimization strategies.
Keywords
Polyamide 6; surface roughness; turning; machining parameters; Taguchi method; ANOVA; cutting velocity; feed rate; depth of cut; machining environment
References
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Moshkbid, E., Cree, D. E., Bradford, L., & Zhang, W. (2024). Biodegradable alternatives to plastic in medical equipment: Current state, challenges, and the future. Journal of Composites Science, 8(9), 342. https://doi.org/10.3390/jcs8090342
O'wal, M., & Bharti, P. (2023). Investigation of optimization machining parameter for POM (Polyoxymethylene) while using TNMG insert by Taguchi, ANOVA. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4664300
Parodi, E. (2017). Structure properties relations for polyamide 6 [Doctoral dissertation, Technische Universiteit Eindhoven].
Patti, A., & Acierno, D. (2022). Towards the sustainability of the plastic industry through biopolymers: Properties and potential applications to the textiles world. Polymers, 14(4), 692. https://doi.org/10.3390/polym14040692
Pelin, G., Sonmez, M., & Pelin, C.-E. (2024). The use of additive manufacturing techniques in the development of polymeric molds: A review. Polymers, 16(8), 1055. https://doi.org/10.3390/polym16081055
Quitiaquez, P., Cocha, J., Quitiaquez, W., & Vaca, X. (2022). Investigation of geometric parameters with HSS tools in machining polyamide 6 using Taguchi method. Materials Today: Proceedings, 49, 181-187. https://doi.org/10.1016/j.matpr.2021.08.002
Salman, M. A., Al-Aloosi, R. A., Tolephih, M. H., Shaheen, W. H. A., Abd Al-Sabh, W. S., & Abdullah, O. I. (2025). Effect of nozzle diameter and raster angle on the mechanical properties of 3D printed nylon/carbon fibers. Engineering, Technology & Applied Science Research, 15(2), 21410-21417. https://doi.org/10.48084/etasr.9979
Shaheen, W. H. A., Salman, M., Alaloosi, R. A., Tolephih, M. H., Abd Al-Sabh, W. S., & Abdullah, O. I. (2025). Investigation of effective parameters on oxygen free high conductivity copper deformation based on cutting molds design and numerical approach. Advances in Science and Technology Research Journal, 19(7), 480-495. https://doi.org/10.12913/22998624/204303
Sidiq, P., Abdalrahman, R. M., & Rostam, S. (2020). Optimizing the simultaneous cutting-edge angles, included angle and nose radius for low cutting force in turning polyamide PA66. Results in Materials, 7, 100100. https://doi.org/10.1016/j.rinma.2020.100100
Sztankovics, I. (2023). Study on the roughness parameters describing surface functionality in bore honing. Multidiszciplináris Tudományok, 13(2), 135-143. https://doi.org/10.35925/j.multi.2023.2.12
Ying, H., Zhang, J., Liu, X., Wang, Y., & Chen, Z. (2023). Investigation of the effect of the cut parameter on the machining performance of PTFE cutting. Journal of Manufacturing Processes, 103, 144-155. https://doi.org/10.1016/j.jmapro.2023.08.041
Alateyah, A. I., El-Taybany, Y., El-Sanabary, S., El-Garaihy, W. H., & Kouta, H. (2022). Experimental investigation and optimization of turning polymers using RSM, GA, hybrid FFD-GA, and MOGA methods. Polymers, 14(17), 3585. https://doi.org/10.3390/polym14173585
Antony, J. (2023). Design of experiments for engineers and scientists (3rd ed.). Elsevier.
Aruna, M. (2020). Optimization of cutting parameters in machining polyoxymethylene using RSM. IOP Conference Series: Materials Science and Engineering, 893(1), 012005. https://doi.org/10.1088/1757-899X/893/1/012005
Ayyildiz, E. A., Ayyildiz, M., & Kara, F. (2021). Optimization of surface roughness in drilling medium-density fiberboard with a parallel robot. Advances in Materials Science and Engineering, 2021(1), 6658968. https://doi.org/10.1155/2021/6658968
Belkhiri, A. (2022). *Controlling glass/matrix interfacial interactions applied to in situ anionic PA6 synthesis for composite manufacturing* [Doctoral dissertation, National Polytechnic Institute of Toulouse].
Bertolini, R., Ghiotti, A., & Bruschi, S. (2020). Machinability of polyamide 6 under cryogenic cooling conditions. Procedia Manufacturing, 48, 419-427. https://doi.org/10.1016/j.promfg.2020.05.064
Bozdemir, M. (2018). Prediction of surface roughness considering cutting parameters and humidity condition in end milling of polyamide materials. Computational Intelligence and Neuroscience, 2018, 1-7. https://doi.org/10.1155/2018/5850432
Fu, H., Xu, H., Liu, Y., Yang, Z., Kormakov, S., Wu, D., & Sun, J. (2020). Overview of injection molding technology for processing polymers and their composites. ES Materials & Manufacturing, 8, 3-23. https://doi.org/10.30919/esmm5f713
Hamzaçebi, C. (2021). Taguchi method as a robust design tool. In P. Li, P. António Rodrigues Pereira, & H. Navas (Eds.), Quality control - Intelligent manufacturing, robust design and charts. IntechOpen. https://doi.org/10.5772/intechopen.94930
Kumar, R., Mishra, S. K., & Jayapalan, S. (2025). Experimental analysis on the microstructural, mechanical, thermal and tribological properties of graphene nanoplatelets and molybdenum disulfide filled polyamide-6,6 novel hybrid composite. Polymer Composites, 46(5), 4703-4728. https://doi.org/10.1002/pc.29270
Li, X., Liu, F., Gong, N., Yang, C., & Wang, Q. (2020). Enhanced thermal properties of polyamide 6,6 composite/aluminum hybrid via injection joining strategy. International Communications in Heat and Mass Transfer, 116, 104696. https://doi.org/10.1016/j.icheatmasstransfer.2020.104696
Moshkbid, E., Cree, D. E., Bradford, L., & Zhang, W. (2024). Biodegradable alternatives to plastic in medical equipment: Current state, challenges, and the future. Journal of Composites Science, 8(9), 342. https://doi.org/10.3390/jcs8090342
O'wal, M., & Bharti, P. (2023). Investigation of optimization machining parameter for POM (Polyoxymethylene) while using TNMG insert by Taguchi, ANOVA. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4664300
Parodi, E. (2017). Structure properties relations for polyamide 6 [Doctoral dissertation, Technische Universiteit Eindhoven].
Patti, A., & Acierno, D. (2022). Towards the sustainability of the plastic industry through biopolymers: Properties and potential applications to the textiles world. Polymers, 14(4), 692. https://doi.org/10.3390/polym14040692
Pelin, G., Sonmez, M., & Pelin, C.-E. (2024). The use of additive manufacturing techniques in the development of polymeric molds: A review. Polymers, 16(8), 1055. https://doi.org/10.3390/polym16081055
Quitiaquez, P., Cocha, J., Quitiaquez, W., & Vaca, X. (2022). Investigation of geometric parameters with HSS tools in machining polyamide 6 using Taguchi method. Materials Today: Proceedings, 49, 181-187. https://doi.org/10.1016/j.matpr.2021.08.002
Salman, M. A., Al-Aloosi, R. A., Tolephih, M. H., Shaheen, W. H. A., Abd Al-Sabh, W. S., & Abdullah, O. I. (2025). Effect of nozzle diameter and raster angle on the mechanical properties of 3D printed nylon/carbon fibers. Engineering, Technology & Applied Science Research, 15(2), 21410-21417. https://doi.org/10.48084/etasr.9979
Shaheen, W. H. A., Salman, M., Alaloosi, R. A., Tolephih, M. H., Abd Al-Sabh, W. S., & Abdullah, O. I. (2025). Investigation of effective parameters on oxygen free high conductivity copper deformation based on cutting molds design and numerical approach. Advances in Science and Technology Research Journal, 19(7), 480-495. https://doi.org/10.12913/22998624/204303
Sidiq, P., Abdalrahman, R. M., & Rostam, S. (2020). Optimizing the simultaneous cutting-edge angles, included angle and nose radius for low cutting force in turning polyamide PA66. Results in Materials, 7, 100100. https://doi.org/10.1016/j.rinma.2020.100100
Sztankovics, I. (2023). Study on the roughness parameters describing surface functionality in bore honing. Multidiszciplináris Tudományok, 13(2), 135-143. https://doi.org/10.35925/j.multi.2023.2.12
Ying, H., Zhang, J., Liu, X., Wang, Y., & Chen, Z. (2023). Investigation of the effect of the cut parameter on the machining performance of PTFE cutting. Journal of Manufacturing Processes, 103, 144-155. https://doi.org/10.1016/j.jmapro.2023.08.041