Machine tool vibrations have great impact on machining process. Modal testing is a form of vibration testing which is able to determine the Frequency Response Function (FRF) of the mechanical test structures. In this paper, the main focus is to identify a procedure to obtain natural frequency values for machine tool components in order to establish better conditions in the cutting process on the machine tool. For this purpose, a 3D model of the machine tools structure is made using design software and exported to analysis software. Later on, the Finite Element Method (FEM) modal analysis was used to obtain the natural frequencies. The model is evaluated and corrected through an experimental modal test. In the experiment, the machine tool vibration is excited by impact hammer and the response of excited vibration is recorded. In the end, the result of both FEM and experimental shows a good consistency in comparison.
Milling is one of the most common manufacturing processes for automotive component, but its productivity is limited by chatter. This form of chatter is undesirable because it results in premature tool wear, poor surface finish on the machined component and the possibility of serious damage to the machine itself. Modal testing is a form of vibration testing which is able to determine the Frequency Response Function (FRF) of the mechanical test structures. In this paper, the main focus is to obtain natural frequency values for machine tool components in order to establish better conditions in the cutting process on the machine tool. For this purpose, a 3D model of the machine tool’s part is made using design software and exported to analysis software. Later on, the Finite Element Method (FEM) modal analysis was used to obtain the natural frequencies. The model is evaluated and corrected through an experimental modal test. In the experiment, the machine tool vibration is excited by impact hammer and the response of excited vibration is recorded. In the end, the result of both FEM and experimental shows a good consistency in comparison.
This paper presents two important parameters for an electromagnetic energy harvester exploiting various shaker excitation frequencies: (1) number of turns of the coil and (2) length of the beams for the device. This system consists of a cantilever beam based which represent a spring element of the system, permanent NdFeB magnet, coil system and wiring system to be connected to the data acquisition system. It is found that the induced voltage is proportional to the increment of the number of turns and the length of beams. The expected resonance happens at 300 Hz for case (1) and 100 Hz for case (2). The maximum voltage produced by this device is 915.395 millivolts for length 13 cm at 100 Hz excitation and 275.058 millivolts for 1050 turns at 300 Hz excitation. Experimental data have demonstrated that the geometry and number of turns of the coil would affect the performance of the energy harvester while excitation frequency as a non-physical factor also contributes to its effectiveness.
In this paper, productivity and self-excited vibration are simultaneously optimized using multiobjective optimization in cutting process. At high material removal rate, machining processes accelerates tool wear, poor surface finish and failure of machine parts. The effect of self-excited vibration or chatter prevents high machining productivity. This chatter vibration can be avoided by modifying tool geometry at low material removal rate but not at high productivity. To compensate material removal rate and chatter, multiobjective optimization is applied using ε-constraint algorithm to achieve a Pareto front solution. Differential Evolution as intelligent optimization algorithm is shown better results than traditional technique of Sequential Quadratic Programming.
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