A Fuzzy Logic Model for the Analysis of Ultrasonic Vibration Assisted Turning and Conventional Turning of Ti-Based Alloy

Abstract

Titanium and its alloys are largely used in various applications due its prominent mechanical properties. However, the machining of titanium alloys is associated with assured challenges, including high-strength, low thermal conductivity, and long chips produced in conventional machining processes, which result in its poor machinability. Advanced and new machining techniques have been used to improve the machinability of these alloys. Ultrasonic vibration assisted turning (UVAT) is one of these progressive machining techniques, where vibrations are imposed on the cutting insert, and this process has shown considerable improvement in terms of the machinability of hard-to-cut alloys. Therefore, selecting the right cutting parameters for conventional and assisted machining processes is critical for obtaining the anticipated dimensional accuracy and improved surface roughness of Ti-alloys. Hence, fuzzy-based algorithms were developed for the ultrasonic vibration assisted turning (UVAT) and conventional turning (CT) of the Ti-6Al7Zr3Nb4Mo0.9Nd alloy to predict the maximum process zone temperature, cutting forces, surface roughness, shear angle, and chip compression ratio for the selected range of input parameters (speed and depth-of-cut). The fuzzy-measured values were found to be in good agreement with the experimental values, indicating that the created models can be utilized to accurately predict the studied machining output parameters in CT and UVAT processes. The studied alloy resulted in discontinued chips in both the CT and UVAT processes. The achieved results also demonstrated a significant decline in the cutting forces and improvements in the surface quality in the UVAT process. Furthermore, the chip discontinuity is enhanced by the UVAT process due to the higher process zone temperature and the micro-impact imposed by the cutting tool on the workpiece.

Analysis of Carbon Footprints and Surface Quality in Green Cutting Environments for the Milling of AZ31 Magnesium Alloy

“…The experiments in this study were conducted using the robust fuzzy logic DOE technique [47]. After conducting a thorough literature review [9,10,48] and preliminary experimentation, three control variables were chosen at three levels, namely the cutting environment, the cutting speed (CS), and the feed (F), as presented in Table 3. Given the bio-compatibility of AZ31, the study focused on two machining responses, surface roughness (SR) and microhardness (HV), while taking into account carbon footprints as prime response parameter.…”

Surface Quality Improvement for Ultrasonic-Assisted Inner Diameter Sawing with Six-Axis Force Sensors

“…Chen Y. ground sapphire and found that ultrasonic-assisted grinding improved the surface finish of the sapphire in the axial and tangential direction compared with ordinary grinding [ 17 ]. Muhammad Riaz applied ultrasonic vibration to a turning tool to study the influence of processing parameters on the surface roughness of titanium alloy and confirmed that the ultrasonic-assisted process could significantly reduce the cutting force and improve the sawing surface quality [ 18 ]. Sui H. et al combined ultrasonic vibration-assisted machining and boring and found that the combined approach was effective in reducing the boring force and improving the accuracy of the boring.…”

The Influence of Cutting Parameters on Plastic Deformation and Chip Compression during the Turning of C45 Medium Carbon Steel and 62SiMnCr4 Tool Steel

“…In addition to turning, milling, and drilling, cutting zone research continues for a variety of other materials [38,39] and cutting technologies such as grinding [40], milling with a disc cutter [41], and Micro and Macro Machining (MMM) [42,43] by using FEM [44] and fuzzy algorithms [45].…”