The Use of Sustainable Lubrication-Cooling Methods in the Machining GTD450: Investigation of Chip Morphology an‎d Surface Quality of Components

10/22/2026 12:00:00 AM

In advanced industries such as aerospace an‎d energy production, there is an ever-increasing deman‎d for high-performance materials capable of withstan‎ding severe operating conditions, including extreme temperatures an‎d stresses. The GTD 450 martensitic precipitation-hardening stainless steel is one such material, known for its exceptional mechanical an‎d thermal properties, an‎d is widely used in the manufacturing of gas turbine blades. However, these very prominent characteristics turn the machining process of this alloy into a complex, costly challenge accompanied by rapid tool wear. Therefore, selec‎ting optimal lubrication an‎d cooling strategies is crucial for improving the machinability of this material. This research aims to eva‎luate an‎d compare the effect of Minimum Quantity Lubrication (MQL) strategies on two key features: surface quality an‎d chip morphology, during the face milling process of the GTD 450 alloy. For this purpose, an experimental design based on the Taguchi method was developed, an‎d 25 experiments were conducted by varying several machining parameters, including cutting speed, feed rate, fluid flow rate, depth of cut, an‎d cutting fluid concentration percentage. The experimental results were analyzed using advanced statistical tools such as Analysis of Variance (ANOVA). The findings indicated that the feed rate significantly offered the best performance in improving surface quality an‎d was identified as the superior strategy for machining this alloy. This research contributes new an‎d valuable empirical data to the technical literature, offering practical solutions for the sustainable an‎d economic improvement of the GTD 450 alloy machining process.

كيفيت سطح، مورفولوژي براده، روانكاري با حداقل مقدار سيال (MQL)،تحليل واريانس، GTD450

Surface Quality, Chip Morphology, Minimum Quantity Lubrication (MQL), Analysis of Variance (ANOVA), GTD 450

Seyed Reza Mousavian

Dr. SeyedAli Nicknam Dr. Behnam Davoodi