Enhancing Surface Roughness in the Taguchi Method for Turning Alloy Steel in Wet and Dry Environments

Year : 2025 | Volume : 03 | Issue : 02 | Page : 1 6
    By

    Rone,

  1. Assistant Professor, Department of Mechanical Engineering, Echelon Institute of Technology, Faridabad, Haryana, India

Abstract

The present investigation focuses on evaluating the performance of turning operations in alloy steel with particular emphasis on the effect of cutting parameters on surface roughness. In the machining of alloy steel, tool life and surface integrity are significantly influenced by parameters such as spindle speed, depth of cut, and feed rate. Among these, feed rate has been observed to exert the most prominent effect on surface roughness. To systematically analyze these influences, the Taguchi method employing an L9 orthogonal array design was selected as the most suitable approach for experimental planning. This method not only reduces the number of experimental trials but also provides an efficient statistical framework to evaluate the contribution of individual parameters. Three levels were chosen for each cutting factor to comprehensively study their interactions and effects. The experiments were performed under both wet and dry turning conditions using a CNC lathe machine, with workpieces of 45 mm diameter and 145 mm length. For each condition, three sets of trials were conducted to ensure repeatability, and the average values were considered as the final outcomes. The signal-to-noise (S/N) ratio analysis was used to determine the robustness of the parameters, while analysis of variance (ANOVA) was employed to quantify the percentage contribution of each factor. Optimization of the experimental data was carried out using Minitab 17 software, which assisted in identifying the optimal combination of parameters for achieving minimum surface roughness. The results revealed that feed rate was the most critical factor influencing surface finish, followed by spindle speed and depth of cut. Furthermore, it was observed that wet turning yielded comparatively better results in terms of surface quality when compared to dry turning, thereby highlighting the importance of lubrication in improving machining performance. The findings of this work provide useful insights for industry practitioners to optimize cutting conditions, enhance tool life, and improve productivity in alloy steel machining. This study demonstrates the efficiency of the Taguchi method in machining optimization and emphasizes its applicability in both academic and industrial research contexts.

Keywords: Turning, orthogonal array, roughness, spindle, Taguchi method, signal-to-noise.

[This article belongs to International Journal of Robotics and Automation in Mechanics ]

How to cite this article:
Rone. Enhancing Surface Roughness in the Taguchi Method for Turning Alloy Steel in Wet and Dry Environments. International Journal of Robotics and Automation in Mechanics. 2025; 03(02):1-6.
How to cite this URL:
Rone. Enhancing Surface Roughness in the Taguchi Method for Turning Alloy Steel in Wet and Dry Environments. International Journal of Robotics and Automation in Mechanics. 2025; 03(02):1-6. Available from: https://journals.stmjournals.com/ijram/article=2025/view=235172


References

  1. Sobh Arafa S, Sayed Esraa M, Barakat Azzz F, Elshaerr Ramadan N. Turning parameters optimization for TC21 Ti-alloy using Taguchi technique. Beni-Suef Univ J Basic Appl Sci. 2023; 12(1): 20.
  2. Mulugundam Shiva Surya. Optimization of turning parameters while turning Ti-6Al-4V titanium alloy for surface roughness and material removable rate using response surface methodology. Mater Today Proc. 2022; 62(Part 6): 3479–3484.
  3. Thirumalai R, Kuaanan Techato, Chandrashekharan M, Venkatapathy K, Seenivasan. Experimental Investigation during turning process of titanium material for surface roughness. Mater Today Proc. 2021; 45(Part 2): 1423–1426.
  4. Emre Altas, Hasan Gokkaya, Meltem Altin Karatas, Dervis Ozkan. Analysis of Surface Roughness and Flank Wear Using the Taguchi Method in Milling of NiTi Shape Memory Alloy with Uncoated Tools. Coating, MDPI. 2020; 10(12): 1259.
  5. DuyTrinh Nguyen, Shaohui Yin, Qingchun Tang, Phung Xuan Son, Le Anh Duc. Online monitoring of surface roughness and grinding wheel wear when grinding Ti-6Al-4V titanium alloy using ANFIS-GPR hybrid algorithm and Taguchi analysis. Precis Eng. 2019; 55: 275–292.
  6. Raghvendra MJ, Ramachandra CG, Srinivas TR, Prashanth Pai M. Optimization of surface roughness in turning operation in machining of ti-6al-4v. IOP Conf Ser: Mater Sci Eng. 2018; 376: 012118.
  7. Ravikumar SM, Suneel Kumar Kulkarni. Analysis of hard machining of Titanium Alloy by Taguchi Method. Mater Today Proc. 2017; 4(10): 10729–10738.
  8. Mittal D, Garg MP, Khanna R. An investigation of the effect of the process parameters on MRR in turning of pure Titanium (Grade-2). Int J Eng Sci Technol. 2011; 3(8): 6345–6349.
  9. Pahda S, Sharma SM. Malhotra N. Analysis of variance and Optimization of surface roughness in CNC Turning of EN-8 steel by Taguchi method. Int J Adv Eng Technol. 2011; 3(1): 264–267.
  10. Vellibor M, Milos M. Optimization of surface roughness in turning alloy steel by using Taguchi method. Sci Res Essays. 2011; 6(16): 3474–3484.
  11. Khrais S, Hassan AM, Gazawi A. Investigations into the turning parameters effect on the surface roughness of flame hardened medium carbon steel with TiN-Al2O3- TiCN coated inserts based on Taguchi techniques. Word Acad Sci Eng Technol: Int Sch Sci Res Innov. 2011; 5(11): 2137–214.
  12. Yadav UK, Narang D, Attri PS. Experimental investigation and optimization of machining parameters for surface roughness in CNC turning by Taguchi method. Int J Eng Res Appl. 2012; 2(4): 2060–2065.
Regular Issue Subscription Original Research
Volume 03
Issue 02
Received 11/07/2025
Accepted 14/11/2025
Published 29/11/2025
Publication Time 141 Days
35

Login


My IP

PlumX Metrics