Abstract
The aim of this study was to optimize machining parameters to obtain the smallest average surface roughness (Ra) and flank wear (Vb) values as a result of the surface milling of a nickel-titanium (NiTi) shape memory alloy (SMA) with uncoated cutting tools with different nose radius (rε) under dry cutting conditions. Tungsten carbide cutting tools with different rε (0.4 mm and 0.8 mm) were used in milling operations. The milling process was performed as lateral/surface cutting at three different cutting speeds (Vc) (20, 35 and 50 m/min), feed rates (fz) (0.03, 0.07 and 0.14 mm/tooth) and a constant axial cutting depth (0.7 mm). The effects of machining parameters in milling experiments were investigated based on the Taguchi L18 (21 × 32) orthogonal sequence, and the data obtained were analyzed using the Minitab 17 software. To determine the effects of processing parameters on Ra and Vb, analysis of variance (ANOVA) was used. The analysis results reveal that the dominant factor affecting the Ra is the cutting tool rε, while the main factor affecting Vb is the fz. Since the predicted values and measured values are very close to each other, it can be said that optimization is correct according to the validation test results.
Highlights
The demand for functional products due to the problems encountered in medicine and industrial areas has led scientists to improve the properties of materials and to produce new materials with superior properties
austenite start (As) tungsten carbide cutting tool with two different rε, three different V c and three different f z were selected as thecarbide processing parameters effects will analyzed, andVcthe milling
In this study, which was carried out based on the findings of exhaustive research studies, the effect of the nose radius and cutting parameters (V c and f z ) on the surface roughness (Ra) of NiTi shape memory alloy and tool wear in the milling process under dry cutting conditions was investigated
Summary
The demand for functional products due to the problems encountered in medicine and industrial areas has led scientists to improve the properties of materials and to produce new materials with superior properties. Smart materials, which have made great progress in recent years, have the ability to change their properties according to environmental conditions. Smart materials are used to transform one type of energy into other [1]. The use of smart materials is increasing in the biomedical, aerospace, and automotive industries. Shape memory alloys (SMAs), which are among smart materials, can return to their original form (shape or size) when subjected to a recall process between two transformation phases dependent on temperature or magnetic field [2]. Among the SMAs, nickel-titanium (NiTi) alloy is the most widely used one in the biomedical field
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