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<p>This study develops an integrated RSM–Fermatean fuzzy WASPAS framework for multi-response drilling optimization of wire arc additively manufactured ERNiCrMo-3/316LSi nickel–stainless steel bimetallic structures. WAAM bimetallics often contain bead waviness, geometric deviation, residual stress, thermal distortion, and microstructural heterogeneity, which make drilling performance difficult to optimize through a single response. The effects of cutting speed, feed rate, tool point angle, and coolant condition were evaluated through twelve drilling trials. Four responses were considered: surface roughness, material removal rate, hole dimensional accuracy, and energy consumption. The measured results showed clear variation across the tested conditions. Surface roughness ranged from 0.666 to 2.166&#xa0;μm, material removal rate from 10 to 75&#xa0;mm³/min, hole dimensional accuracy from 90 to 99%, and energy consumption from 120 to 300&#xa0;W. Response Surface Methodology was used to model factor effects and interaction behavior, while Fermatean fuzzy logic was applied to reduce the influence of response uncertainty in ranking. WASPAS combined the weighted criteria into a single ranking index to identify the best compromise among the tested alternatives. The selected condition was 50&#xa0;m/min cutting speed, 0.1&#xa0;mm/rev feed rate, 135° tool point angle, and oil-based cooling, producing Ra = 1.1667&#xa0;μm, MRR = 50&#xa0;mm³/min, HDA = 96%, and EC = 220&#xa0;W. This condition offered a balanced trade-off among surface quality, productivity, dimensional accuracy, and energy demand. The observed performance is associated with reduced chip load, stable tool engagement, improved chip evacuation, lower friction, and controlled heat generation at the tool–workpiece interface. Statistical validation and sensitivity analysis showed that the ranking remained stable within the tested experimental range. The proposed framework provides a reproducible decision-support method for drilling the investigated WAAM bimetallic system and requires validation before use in other WAAM material combinations.</p>

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Development of a hybrid RSM–Fermatean fuzzy WASPAS framework for multi-objective drilling optimization of WAAM nickel–stainless steel bimetallics

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  • 发表日期：

    2026年7月4日

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  • S. P. Sundar Singh Sivam,
  • Stalin Kesavan,
  • P. Sathishkumar

摘要

This study develops an integrated RSM–Fermatean fuzzy WASPAS framework for multi-response drilling optimization of wire arc additively manufactured ERNiCrMo-3/316LSi nickel–stainless steel bimetallic structures. WAAM bimetallics often contain bead waviness, geometric deviation, residual stress, thermal distortion, and microstructural heterogeneity, which make drilling performance difficult to optimize through a single response. The effects of cutting speed, feed rate, tool point angle, and coolant condition were evaluated through twelve drilling trials. Four responses were considered: surface roughness, material removal rate, hole dimensional accuracy, and energy consumption. The measured results showed clear variation across the tested conditions. Surface roughness ranged from 0.666 to 2.166 μm, material removal rate from 10 to 75 mm³/min, hole dimensional accuracy from 90 to 99%, and energy consumption from 120 to 300 W. Response Surface Methodology was used to model factor effects and interaction behavior, while Fermatean fuzzy logic was applied to reduce the influence of response uncertainty in ranking. WASPAS combined the weighted criteria into a single ranking index to identify the best compromise among the tested alternatives. The selected condition was 50 m/min cutting speed, 0.1 mm/rev feed rate, 135° tool point angle, and oil-based cooling, producing Ra = 1.1667 μm, MRR = 50 mm³/min, HDA = 96%, and EC = 220 W. This condition offered a balanced trade-off among surface quality, productivity, dimensional accuracy, and energy demand. The observed performance is associated with reduced chip load, stable tool engagement, improved chip evacuation, lower friction, and controlled heat generation at the tool–workpiece interface. Statistical validation and sensitivity analysis showed that the ranking remained stable within the tested experimental range. The proposed framework provides a reproducible decision-support method for drilling the investigated WAAM bimetallic system and requires validation before use in other WAAM material combinations.