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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月2日

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

摘要

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.