This paper presents a statistical model for prediction cutting components force in the ball-end milling of NiTi shape memory alloy (Nitinol). In experiment a ball-end mill (EB-A2 03-04C06E48) was used and a dynamometer Kistler was used for the measurement of cutting forces components. The research trials were conducted for two independent parameters (vc, fz,) affecting the cutting force in milling process. The choice of parameter configurations was performed by factorial design methods using orthogonal plan type L9, with two control factors, changing on three levels, developed by G. Taguchi. The model for the mathematical prediction of cutting force was developed in terms of feed per tooth and cutting speed. The computational model enabled to select optimal machining parameters for minimizing cutting forces values.
Temperature is one of the most important factors in the machining process. This is even more important for modern nonferrous alloys. The subject of the study is the temperature both in the area of the machined surface as well as in the machining zone obtained during the precise rotation of a shaft made of a NiTi shape memory alloy. The temperature was tested in laboratory conditions and recorded using the FLIR 620 thermographic camera. ThermaCam Researcher software was used to archive and analyze the obtained results. The tests were conducted for two independent parameters (vc, f) affecting the temperature in the machining zone. The configuration of parameters was determined using he orthogonal plan L9, with two control factors, changing at three levels, developed by G. Taguchi. The ratio S / N and Anova were made to determine the best cutting parameters affecting the temperature.
This study was conducted to understand the exact turning of the NiTi shape memory alloy using tools made of polycrystalline diamonds (PCD) and consisted of three stages: experimental work, function modeling, Monte Carlo method optimization. In the first stage (experimental work) precise turning experiments were carried out using the Taguchi method. The influence of cutting speed and feed on surface roughness was investigated (Sa and Sz). In the second stage (modelling) all data collected in the experimental work were used to formulate models with interaction using the surface response method. In the third stage, the Monte Carlo method was used to solve problems with machining optimization. This article has the following main objectives: to develop a framework for solving machining optimization problems using the Monte Carlo method.
This paper describes the research results of surface quality research after the NiTi shape memory alloy (Nitinol) precise turning by the tools with edges made of polycrystalline diamonds (PCD). Nitinol, a nearly equiatomic nickel–titanium shape memory alloy, has wide applications in the arms industry, military, medicine and aerospace industry, and industrial robots. Due to their specific properties NiTi alloys are known to be difficult-to-machine materials particularly by using conventional techniques. The research trials were conducted for three independent parameters (vc, f, ap) affecting the surface roughness were analyzed. The choice of parameter configurations were performed by factorial design methods using orthogonal plan type L9, with three control factors, changing on three levels, developed by G. Taguchi. S/N ratio and ANOVA analyses were performed to identify the best of cutting parameters influencing surface roughness.
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