Multi-Criteria Performance Analysis of Dry, Vortex Air and Compressed Air Environments in Turning Hastelloy X Superalloy

Year 2025, Volume: 11 Issue: 2, 243 - 253, 31.08.2025

Yusuf Siyambaş , Aslan Akdulum

Abstract

Hastelloy X superalloy, which exhibits superior performance under harsh conditions such as extreme temperature, oxidation, and corrosion, is widely used in the aviation and energy sectors but causes significant problems in machining due to its difficult machinability properties. This situation has brought up the need for alternative cooling strategies to reduce cutting forces and temperatures during machining, improve surface quality, and minimize environmental impacts. In this research, the impacts of varying cutting variables (depth of cut, feed rate, and cutting speed) on cutting force (FR), surface roughness (Ra), and cutting temperature (T) in the turning of Hastelloy X superalloy under three different machining environments (dry, vortex air, and compressed air) were experimentally investigated. The Taguchi L9 orthogonal layout was utilized for the experimental design, and simultaneous optimization of multiple performance outcomes was carried out by the grey relational analysis (GRA) technique. According to the findings, the lowest FR and Ra occurred in dry, compressed air and vortex air processing environments, respectively. The lowest values in terms of T were obtained in compressed air, vortex air, and dry machining environments, respectively. In summary, the effect of cooling conditions on T was not reflected in FR and Ra. As a result of GRA optimization, where all performance criteria were evaluated together, the most suitable machining condition was determined to be a dry machining environment, an 80 m/min cutting speed, a 0.075 mm/rev feed rate, and a 0.8 mm cutting depth. Vortex air and compressed air environments have been evaluated as a strong alternative to dry environments.

Keywords

Sustainable processing environments , cutting force , cutting temperature , surface roughness , grey relational analysis

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