Implementing a novel TOPSIS-sine cosine algorithm-based hybrid optimization in machining medium-hardened steel

Ramanuj Kumar; Mohammad Rafighi; Oğur İynen; M Prem Kumar Reddy; Shrikant Zade; Mustafa Özdemir; Anish Pandey; Ramanpreet Singh

doi:10.1038/s41598-025-07542-0

Implementing a novel TOPSIS-sine cosine algorithm-based hybrid optimization in machining medium-hardened steel

Sci Rep. 2025 Jul 2;15(1):22740. doi: 10.1038/s41598-025-07542-0.

Authors

Ramanuj Kumar¹, Mohammad Rafighi^{2

3}, Oğur İynen⁴, M Prem Kumar Reddy⁵, Shrikant Zade⁶, Mustafa Özdemir⁷, Anish Pandey⁸, Ramanpreet Singh⁹

Affiliations

¹ School of Mechanical Engineering, Kalinga Institute of Industrial Technology (KIIT), Deemed to Be University, Bhubaneswar, Odisha, 751024, India.
² Department of Mechanical Engineering, Başkent University, Ankara, 06490, Türkiye.
³ School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA.
⁴ Department of Mechanical Engineering, Yozgat Bozok University, 66100, Yozgat, Türkiye.
⁵ Department of Mechanical Engineering, Aditya University, Surampalem, Andhra Pradesh, 533437, India.
⁶ Department of Computer Science Engineering, Nagpur Institute of Technology, Nagpur, Maharashtra, 440013, India.
⁷ Department of Machine and Metal Technology, Yozgat Bozok University, 66100, Yozgat, Türkiye.
⁸ School of Mechanical Engineering, Kalinga Institute of Industrial Technology (KIIT), Deemed to Be University, Bhubaneswar, Odisha, 751024, India. anish.pandeyfme@kiit.ac.in.
⁹ Department of Mechanical Engineering, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India. ramanpreet.singh@jaipur.manipal.edu.

Abstract

Machining medium-hardened steel is particularly challenging because of its high strength and wear resistance, which generate excessive cutting temperatures. The elevated temperature contributes to rapid tool wear and negatively impacts surface quality. Optimizing tool selection, coating composition, geometry, and process variables is crucial for enhancing machinability. This study applied a novel hybrid TOPSIS-sine cosine algorithm to evaluate the performance of three chemical vapor deposited (CVD)-coated carbide cutting inserts in turning medium-hard AISI 4340 grade steel, considering the depth of cut (a), cutting speed (V), feed (f) and workpiece hardness as input variables. Experimentally obtained machining responses, namely resultant force (Fr), power consumption (Pc), surface roughness (Ra), and sound level (SL), were analyzed and compared to determine the optimum insert type. Insert type-3 (TiCN-Al2O3-TiN) demonstrated superior performance, achieving a 16.68% and 26.74% lower Ra than insert type-1 and type-2, respectively. Moreover, the optimal parameters for the most favorable insert (type-3) are determined as H = 30 HRC, V = 190 m/min, f = 0.1 mm/rev, and a = 0.2 mm. Workpiece hardness (H) emerged as the most influential factor affecting machining outcomes. This research recommended insert type-3 at optimized cutting conditions to improve machinability and sustainability in turning medium-hard AISI 4340 grade steel.

Keywords: Coated carbide tools; Cutting forces; Medium hardened steel; Surface roughness; TOPSIS-sine cosine algorithm; Turning.