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In the paper, the problem of chatter vibration detection in the milling process of carbon fiber-reinforced plastic is investigated. Chatter analysis may be considered theoretically based on data from impact test of an end mill cutter. However, a stability region obtained in such way may not agree with the real one. Therefore, this paper presents a method that can predict chatter vibrations based on cutting force components measurements. At the beginning, a stability lobe diagram is created to establish the range of experimental test in the plane of tool rotational speed and depth of cut. Next, an experiment of composite milling is performed. The experimentally-measured time series of cutting forces are decomposed with the use of the improved Hilbert–Huang transform (HHT). To detect chatter, statistical methods and recurrence quantification analysis (RQA) are used. However, much better results are obtained when new chatter indexes are proposed. The indexes, derived directly from the HHT and RQA methods, can be used to build an effective chatter prediction system.

Abstract. In the paper a cutting stability in the milling process of nickel based alloy Inconel 625 is analysed. This problem is often considered theoretically, but the theoretical finding do not always agree with experimental results. For this reason, the paper presents different methods for instability identification during real machining process. A stability lobe diagram is created based on data obtained in impact test of an end mill. Next, the cutting tests were conducted in which the axial cutting depth of cut was gradually increased in order to find a stability limit. Finally, based on the cutting force measurements the stability estimation problem is investigated using the recurrence plot technique and Hilbert vibration decomposition method.

This paper presents an intelligent system for optimization of the cylindrical traverse grinding process whose objective is to maximize the material removal rate with constraints on workpiece out-of-roundness and waviness errors, on surface finish, and on grinding temperature. A theoretical analysis of wheel wear development in the traverse grinding process is presented. Next, the results of an experimental test are discussed to establish the most efficient strategy for grinding allowance removal. In the optimization scheme a feedforward neural network is employed to obtain a model which describes relations between the process input parameters and the grinding results. Then this model is used to optimize adaptively the traverse grinding process. The performance of the proposed optimization system is evaluated by simulation research.

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Abstract. In the paper, chatter vibrations in the cylindrical plunge grinding process are investigated. An improved model of the grinding process was developed which is able to simulate self-excited vibrations due to a regenerative effect on the workpiece and the grinding wheel surface. The model includes a finiteelement model of the workpiece, two degrees of freedom model of the grinding wheel headstock and a model of wheel-workpiece geometrical interferences. The model allows to studying the influence of different factors, i.e. workpiece and machine parameters as well as grinding conditions on the stability limit and a chatter vibration growth rate. At the end, simulation results are shown and compared with exemplified real grinding results.