Integration of taguchi method and digital metrology for precision fused deposition modelling of PLA-based vibration-damping components

Danang Yudistiro; Salahuddin Junus; Dani Hari Tunggal Prasetiyo; Istiqomah Rahmawati; Helda Wika Amini; Meta Fitri Rizkiana

doi:10.30811/jpl.v24i1.8352

Integration of taguchi method and digital metrology for precision fused deposition modelling of PLA-based vibration-damping components

Danang Yudistiro, Salahuddin Junus, Dani Hari Tunggal Prasetiyo, Istiqomah Rahmawati, Helda Wika Amini, Meta Fitri Rizkiana

Abstract

This study integrates the Taguchi method and 3D digital metrology to improve dimensional accuracy in the Polylactic Acid (PLA)-based Fused Deposition Modelling (FDM) process. The research focuses on the fabrication of vibration-damping roller components in a Continuously Variable Transmission (CVT) system that demands high geometric precision. A Taguchi L9 experimental design was used to analyze the effects of layer height, extrusion temperature, and filling density on the volume deviation of the printed product. The evaluation was conducted using 3D scanning and analyzed using the Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA). The optimal parameter combination was obtained at a layer height of 0.25 mm and an extrusion temperature of 220 °C, resulting in the minimum volume deviation and the highest process stability. The ANOVA results identified layer height as the most dominant factor, followed by extrusion temperature, while filling density had a relatively small effect. Validation tests showed good agreement between the predictions and the experimental results. These findings confirm the effectiveness of integrating the Taguchi method with digital metrology in supporting the development of PLA-based precision additive manufacturing for sustainable automotive component applications.

Keywords

Additive Manufacturing, Fused Deposition Modeling (FDM), Polylactic Acid (PLA), Taguchi Method, Dimensional Accuracy

Full Text:

PDF

References

A. Shany, R. Hashemi, and M. Shahbazi, “Optimizing FDM Process Parameters : Predictive Insights through Taguchi, Regression, and Neural Networks,” Phys. Scr., vol. 99, no. 6, pp. 1–22, 2024, doi: 10.1088/1402-4896/ad42d7.

K. Sharma, K. Kumar, R. K. Singh, and M. S. R. Greater, “Optimization of FDM 3D printing process parameters using Taguchi technique Optimization of FDM 3D printing process parameters using Taguchi technique,” 2022, doi: 10.1088/1757-899X/1168/1/012022.

A. E. Tontowi, L. Ramdani, R. V Erdizon, and D. K. Baroroh, “Optimization of 3D-Printer Process Parameters for Improving Quality of Polylactic Acid Printed Part,” vol. 9, no. 2, pp. 589–600, 2017, doi: 10.21817/ijet/2017/v9i2/170902044.

A. M. N. Contuzzi, L. Fabbiano, and G. Casalino, “Multi-Attribute Decision Making: Parametric Optimization and Modeling of the FDM Manufacturing Process Using PLA/Wood Biocomposites,” 2024.

R. Hasanzadeh, P. Mihankhah, T. Azdast, S. Aghaiee, and C. B. Park, “Optimization of Process Parameters of Fused Filament Fabrication of Polylactic Acid Composites Reinforced byAluminum Using Taguchi Approach,” Metals (Basel)., vol. 13, no. 1013, pp. 1–14, 2023, doi: https://doi.org/10.3390/met13061013.

G. K. Megersa, W. Sitek, A. J. Nowak, and N. Tomaši´, “Investigation of the Influence of Fused Deposition Modeling 3D Printing Process Parameters on Tensile Properties of Polylactic Acid Parts Using the Taguchi Method,” Materials (Basel)., vol. 17, no. 23, pp. 1–21, 2024, doi: https://doi.org/10.3390/ma17235951.

A. Solouki, M. R. M. Aliha, A. Makui, N. Choupani, and H. Seiti, “Analyzing the effects of printing parameters to minimize the dimensional deviation of polylactic acid parts by applying three different decision-making approaches,” Nature, pp. 1–26, 2024.

V. Wankhede, D. Jagetiya, A. Joshi, and R. Chaudhari, “Experimental investigation of FDM process parameters using Taguchi analysis,” in Materials Today: Proceedings, 2019, pp. 1–4. doi: https://doi.org/10.1016/j.matpr.2019.09.078.

T. S. Em and S. C. Kiong, “Optimization of Process Parameters for Polylactic Acid ( PLA ) of FDM Using Particle Swarm Optimization ( PSO ),” vol. 4, no. 1, pp. 205–217, 2023.

B. C. Olaiya, “Application of Taguchi Grey- Based ANFIS model for prediction of process parameters in fused deposition modelling of PETG,” pp. 1–14, 2025.

B. A. Ahmed et al., “Printing Parameter Optimization of Additive Manufactured PLA Using Taguchi Design of Experiment,” Polymers (Basel)., vol. 15, no. 22, pp. 1–18, 2023, doi: https://doi.org/10.3390/polym15224370.

M. N. Ahmad et al., “Application of Taguchi Method to Optimize the Parameter of Reinforced Thermoplastic Composites,” Polymers (Basel)., vol. 14, no. 11, pp. 2140–2155, 2022, doi: https://doi.org/10.3390/polym14112140.

M. Kam, A. Ipekci, and O. Sengul, “Investigation of the effect of FDM process parameters on mechanical properties of 3D printed PA12 samples using Taguchi method,” J. Thermoplast. Compos., vol. 2, no. 3, pp. 1–19, 2021, doi: 10.1177/08927057211006459.

M. Kama, A. Ipekcia, and O. Sengul, “Taguchi optimization of fused deposition modeling process parameters on mechanical characteristics of PLA + lament material,” vol. 29, pp. 79–89, 2022, doi: 10.24200/sci.2021.57012.5020.

K. Evangelia, A. Konstantinos, K. John, D. K. Nikolaos, and D. E. Manolakos, “On the application of grey Taguchi method for benchmarking the dimensional accuracy of the PLA fused filament fabrication process,” 2020.

B. Beylergil, “Hoop Strength Optimization of 3D-Printed Polylactic Acid ( PLA ) Rings Using Taguchi Method,” Int. Rev. Mech. Eng., vol. 18, no. 5, pp. 256–265, 2024, doi: https://doi.org/10.15866/ireme.v18i5.24978.

P. Mishra, S. Sood, V. Bharadwaj, A. Aggarwal, and P. Khanna, “Parametric Modeling and Optimization of Dimensional Error and Surface Roughness of Fused Deposition Modeling Printed,” Polymers (Basel)., vol. 15, pp. 1–26, 2023, doi: https://doi.org/10.3390/polym15030546.

A. Karadag and O. Ulkir, “Prediction of Dimensional Accuracy and Surface Quality in Additively Manufactured Biomedical Implants Using ANN,” Int. J. Precis. Eng. Manuf., vol. 26, no. 4, pp. 1187–1213, 2025, doi: https://doi.org/10.1007/s12541-025-01229-2.

K. Patel, S. Acharya, and G. D. Acharya, “Multi Objective Optimization of FDM Parameters Using Taguchi Grey Relation Analysis for PLA Specimen,” vol. 36, no. 1, pp. 113–122, 2024.

C. J. Luis-p and I. Buj-corral, “Modeling of the Influence of Input AM Parameters on Dimensional Error and Form Errors in PLA Parts Printed with FFF Technology,” Polymers (Basel)., vol. 13, no. 2, pp. 1–23, 2021, doi: https://doi.org/10.3390/polym13234152.

H. Alzyod and P. Ficzere, “Optimizing fused filament fabrication process parameters for quality enhancement of PA12 parts using numerical modeling and taguchi method,” Heliyon, vol. 9, no. February, pp. 1–11, 2023, doi: https://doi.org/10.1016/j.heliyon.2023.e14445.

M. Baraheni and M. R. Shabgard, “Effects of FDM 3D printing parameters on PLA biomaterial components dimensional accuracy and surface quality,” in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2023, pp. 1–10. doi: 10.1177/09544062231202142.

H. H. Abdulridha, T. F. Abbas, and A. S. Bedan, “Predicting Mechanical Strength And Optimized Parameters In FDM-Printed Polylactic Acid Parts Via Artificial Neural Networks And Desirability Analysis,” vol. 0, 2024, doi: 10.2478/mspe-2024-0040.

M. Abouelmajd et al., “Experimental analysis and optimization of mechanical properties of FDM-processed polylactic acid using Taguchi design of experiment,” Int. J. Simul. Multidisci., vol. 30, no. 12, pp. 1–9, 2021, doi: https://doi.org/10.1051/smdo/2021031.

M. Altan and M. Eryildiz, “Effects of process parameters on the quality of PLA products fabricated by fused deposition modeling ( FDM ): surface roughness and tensile strength,” Mater. Test., vol. 60, no. 2, pp. 471–477, 2018, doi: 10.3139/120.111178.

B. K. Singh and S. Samanta, “Experimental investigation and Taguchi optimization of FDM process parameters for the enhancement of tensile properties of Bi-layered printed PLA-ABS Experimental investigation and Taguchi optimization of FDM process parameters for the enhancement of tens,” Mater. Res. Express, vol. 10, no. 9, pp. 1–18, 2023, doi: 10.1088/2053-1591/acf1e7.

M. Rahman, J. Sultana, S. Bin, and R. Ammar, “Optimization of FDM manufacturing parameters for the compressive behavior of cubic lattice cores : an experimental approach by Taguchi method,” Int. J. Adv. Manuf. Technol., vol. 129, pp. 1329–1343, 2023, doi: https://doi.org/10.1007/s00170-023-12342-9.

N. Maguluri and G. Suresh, “Assessing the effect of FDM processing parameters on mechanical properties of PLA parts using Taguchi method,” J. Thermoplast. Compos. Mater., vol. 36, no. 4, pp. 1–17, 2021, doi: https://doi.org/10.1177/08927057211053036.

N. K. Balasubramainian, L. Kothandaraman, T. Sathish, and M. I. Ammarullah, “Optimization of process parameters to minimize circularity error and surface roughness in fused deposition modelling (FDM) using Taguchi method for biomedical implant fabrication,” vol. 0340, 2024, doi: 10.1080/20550340.2024.2406156.

A. Alafaghani and A. Qattawi, “Investigating the e ff ect of fused deposition modeling processing parameters using Taguchi design of experiment method,” J. Manuf. Process., vol. 36, no. 10, pp. 164–174, 2018, doi: https://doi.org/10.1016/j.jmapro.2018.09.025.

H. M. Teng, K. Fan, C. H. Jiang, Q. W. Yang, F. H. Liu, and C. C. Tsao, “Study on the printing quality of fused deposition modeling using Taguchi method Study on the printing quality of fused deposition modeling using Taguchi method,” in Journal of Physics: Conference Series, 2022, pp. 1–9. doi: 10.1088/1742-6596/2345/1/012014.

R. I. Yaqin et al., “Material and process parameter optimization for dimensional accuracy in Fused Deposition Modeling 3D printing,” Polimesin, vol. 22, no. 6, 2024.

N. Ezati and P. Sadeghi, “Optimization of FDM process parameters for tensile properties of polylactic acid specimens using Taguchi design of experiment method,” 2020, doi: 10.1177/0892705720964560.

M. Nazma, O. Shadat, and N. Ranjan, “Heliyon Parametric optimization and sensitivity analysis of the integrated Taguchi-CRITIC-EDAS method to enhance the surface quality and tensile test behavior of 3D printed PLA and ABS parts,” vol. 11, no. December 2024, 2025.

T. Sai, V. Kumar, P. Ashish, and K. Srivastava, “Modeling and optimization of fused deposition modeling ( FDM ) process through printing PLA implants using adaptive neuro ‑ fuzzy inference system ( ANFIS ) model and whale optimization algorithm,” J. Brazilian Soc. Mech. Sci. Eng., vol. 42, no. 617, pp. 1–19, 2020, doi: https://doi.org/10.1007/s40430-020-02699-3.

L. Sandanamsamy et al., “A comprehensive review on fused deposition modelling of polylactic acid,” Prog. Addit. Manuf., vol. 8, no. 5, pp. 775–799, 2022, doi: 10.1007/s40964-022-00356-w.

K. Kumar and H. Singh, “Multi ‑ Objective Optimization of Fused Deposition Modeling for Mechanical Properties of Biopolymer Parts Using the Grey ‑ Taguchi Method,” Chinese J. Mech. Eng., vol. 36, no. 30, 2023, doi: https://doi.org/10.1186/s10033-023-00847-z (2023).

J. Sultana, M. Rahman, Y. Wang, A. Ahmed, and C. Xiaohu, “Influences of 3D printing parameters on the mechanical properties of wood PLA filament : an experimental analysis by Taguchi method,” Prog. Addit. Manuf., pp. 1239–1251, 2024.

M. Pant, R. M. Singari, P. K. Arora, G. Moona, and H. Kumar, “Wear assessment of 3 – D printed parts of PLA ( polylactic acid ) using Taguchi design and Artificial Neural Network ( ANN ) technique Wear assessment of 3 – D printed parts of PLA ( polylactic acid ) using Taguchi design and Arti fi cial Neural Network (”.

R. Kumar, J. S. Chohan, S. Singh, S. Sharma, Y. Singh, and S. Rajkumar, “Implementation of Taguchi and Genetic Algorithm Techniques for Prediction of Optimal Part Dimensions for Polymeric Biocomposites in Fused Deposition Modeling,” Int. J. Biomater., vol. 1, no. 1, pp. 1–7, 2022, doi: https://doi.org/10.1155/2022/4541450.

M. Nizam, A. Rafeq, N. Daud, K. Ariffin, and F. Abdul, “Experimental Analysis of Color Influence on Optimized FDM Parameters for PLA using the Taguchi Method,” vol. 37, no. 6, pp. 2739–2748, 2025.

J. R. Stojkovi, “An Experimental Study on the Impact of Layer Height and Annealing Parameters on the Tensile Strength and Dimensional Accuracy of FDM 3D Printed Parts,” 2023.

Y. Li, A. Molazem, H. Kuo, V. Ahmadi, and V. P. Shastri, “Comparative Analysis of Dimensional Accuracy in PLA-Based 3D Printing : Effects of Key Printing Parameters and Related Variables,” pp. 1–15, 2025.

E. B. Hungria, F. Gonçalves, D. Nisio, F. C. Cano, and R. Voltolini, “A study about weak intralayer bonding in extrusion-based additive manufacturing due to resumed extrusion during filling,” vol. 140, no. May, 2024.

M. S. Kumar, M. U. Farooq, C. H. Yang, V. Kavimani, A. A. Adediran, and N. S. Ross, “Achieving effective interlayer bonding of PLA parts during the material extrusion process with enhanced mechanical properties,” pp. 1–21, 2023.

T. K. Singh, A. K. Birru, and K. N. Singh, “Optimizing the printing parameters for dimensional accuracy of distal femur bone by using Taguchi ’ s method,” pp. 1–18, 2024.

N. Aiman et al., “Heliyon Evaluation of the surface roughness and dimensional accuracy of low-cost 3D-printed parts made of PLA – aluminum,” vol. 10, no. November 2023, 2024.

K. Mohan, P. Shubham, D. Bhatia, P. Sharma, and H. Vaid, “Analyzing the Impact of Print Parameters on Dimensional Variation of ABS specimens printed using Fused Deposition Modelling ( FDM ),” Sensors Int., vol. 3, no. November 2021, 2022.

R. Turudija et al., “An Experimental Study on the Impact of Layer Height and Annealing Parameters on the Tensile Strength and Dimensional Accuracy of FDM 3D Printed Parts,” Materials (Basel)., vol. 16, no. 13, pp. 1–19, 2023, doi: https://doi.org/10.3390/ma16134574.

V. E. Alexopoulou, I. T. Christodoulou, and A. P. Markopoulos, “Effect of Printing Speed and Layer Height on Geometrical Accuracy of FDM-Printed Resolution Holes of PETG Artifacts,” in Engineering Proceedings, 2022, pp. 1–6. doi: https://doi.org/10.3390/IECMA2022-12887.

Ç. Bolat and B. Egene, “An Investigation on Dimensional Accuracy of 3D Printed PLA, PET-G and ABS Samples with Different Layer Heights,” Araştırma Makal., vol. 37, no. 3, pp. 449–458, 2022, doi: https://doi.org/10.21605/cukurovaumfd.1146401.

D. Chen and Y. Chen, “Optimization Parameters for PLA Through Additive Manufacturing : Taking Mixed Shapes as an Example,” no. 1, 2024.

R. E. Petruse, C. Simion, and I. Bondrea, “Geometrical and Dimensional Deviations of Fused Deposition Modelling ( FDM ) Additive-Manufactured Parts,” pp. 411–429, 2024.

H. H. Abdulridha and T. F. Abbas, “Analyzing the Impact of FDM

Parameters on Compression Strength and Dimensional Accuracy in 3D printed PLA Parts,” Eng. Technol. J., vol. 41, no. 3, pp. 1611–1626, 2023, doi: http://doi.org/10.30684/etj.2023.143615.1599.

H. H. Abdulridha and T. F. Abbas, “Analysis and Investigation the Effect of the Printing Parameters on the Mechanical and Physical Properties of PLA Parts Fabricated via FDM Printing,” Adv. Sci. Technol., vol. 17, no. 6, pp. 49–62, 2023, doi: https://doi.org/10.12913/22998624/173562.

DOI: http://dx.doi.org/10.30811/jpl.v24i1.8352