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

Area of Science:

• Materials Science
• Manufacturing Engineering
• Mechanical Engineering

Background:

• Machining medium-hardened steel presents challenges due to high strength and wear resistance, leading to elevated temperatures, rapid tool wear, and compromised surface quality.
• Optimizing tool selection, coating composition, geometry, and process parameters is critical for improving machinability and ensuring sustainable manufacturing practices.

Purpose of the Study:

• To evaluate the performance of three chemical vapor deposited (CVD)-coated carbide cutting inserts in turning medium-hard AISI 4340 steel.
• To determine the optimal insert type and machining parameters for enhanced machinability and surface quality.
• To identify the most influential factors affecting the machining process.

Main Methods:

• A hybrid TOPSIS-sine cosine algorithm was employed to analyze experimental data.
• Input variables included depth of cut (a), cutting speed (V), feed (f), and workpiece hardness (H).
• Machining responses such as resultant force (Fr), power consumption (Pc), surface roughness (Ra), and sound level (SL) were measured and compared.

Main Results:

• Insert type-3 (TiCN-Al2O3-TiN) exhibited superior performance, yielding significantly lower surface roughness (Ra) compared to insert types 1 and 2.
• Optimal machining parameters for insert type-3 were identified as H=30 HRC, V=190 m/min, f=0.1 mm/rev, and a=0.2 mm.
• Workpiece hardness (H) was found to be the most significant factor influencing machining outcomes.

Conclusions:

• Insert type-3 is recommended for machining medium-hard AISI 4340 steel under optimized conditions.
• The developed hybrid optimization approach effectively determined the best insert and parameters for improved machinability and sustainability.
• This study provides valuable insights for enhancing the efficiency and quality of machining operations for hardened steels.