MULTI-OBJECTIVE OPTIMIZATION OF Ti-6Al-4V ALLOY MILLING PROCESS UNDER MQL CONDITION

Abstract

This article compares the TOPSIS-Entropy method with the Desirability Function Approach (DFA) in optimizing the milling process of Ti-6Al-4V alloy. The study
focuses on determining the optimal cutting parameters including cutting speed Vc (m/min), tooth feed fz (mm/tooth), and cutting depth ap (mm) under minimum
quantity lubrication (MQL) conditions with lubrication parameters of air pressure P (bar) and oil flow rate Q (ml/h). The research involves experimental work,
developing predictive models for the responses (surface roughness value Ra, material removal rate MRR, and specific cutting energy Uc), performing analysis of
variance (ANOVA), and determining the optimal cutting parameters using the desirability function approach. The research findings indicate that the DFA and TOPSIS-
Entropy methods yield different optimal values. The TOPSIS-Entropy method ranks 27 experimental options to identify the optimal set of process parameters, while
DFA provides the top 27 optimal values based on desired values computed from regression equations. Comparing the TOPSIS-Entropy and DFA methods provides
important insights into optimizing the milling process of Ti-6Al-4V alloy. The choice of the optimization method depends on the research objectives and the trade-off
between process quality and performance.