Modified drilling process of AISI 1045 steel: A hybrid optimization

Abstract

The hybrid methods, such as minimum quantity lubrication (MQL) and ultrasonic vibration (UV) can be employed in the drilling process to improve cutting condition and tool life. In the present study, an experimental analysis has been carried out on drilling process under four types of condition (i.e. Ordinary, MQL, UV, and UV-MQL) where thrust force (Fz) and surface roughness (Ra) were measured for certain rotational spindle speeds and feeding rates. Then a hybrid optimization method proposed based on a prediction model using least square support vector machine (LS-SVM) and grey relational analysis for determination of optimum point. Obtained findings evidence that UV drilling outperformed ordinary and MQL methods. It significantly decreases thrust force and surface roughness compared to ordinary condition in single objective optimization problem. Then optimum point, for both Fz and Ra for UV drilling, has been evaluated under an investigation of multi-objective optimization (i.e. grey relational analysis). Furthermore, lower built-up edge on the drill bit caused better surface quality in UV-MQL drilling. This process produces short and broken chips which is directly effects on friction coefficient and in consequence cutting forces. LS-SVM shows superior performance on optimization of problems on account of its training speed and accuracy in which for optimum point (N = 931 RPM and f = 90 mm/min) similar Fz and Ra were obtained with approximately 6% error.