The study determines the most suitable pattern of alignment and fixing of low-rigidity shafts; it also presents factors that determine such choice. The part is fixed both by force closing and kinematic closing. A new method for machining low rigidity shafts is developed to control the elastic-deformable state of these shafts in a technological system and to produce parts with the required accuracy during turning. To implement this new developed method for low rigidity shafts, an apparatus is designed. The apparatus allows to increase the rigidity of shafts during machining by the application of axial tensile force to the workpiece. Rational prime costs of preparing technological alignment centers at the stage of production preparation are determined; knowing these costs, it is possible to select a suitable machining technology for low rigidity shafts, to produce a technology-oriented design, and to reduce the costs of machining these shafts.
The paper presents an analysis of the possibility of increasing the accuracy and stability of machining of low-rigidity shafts while ensuring high efficiency and economy of their machining. An effective way of improving the accuracy of machining of shafts is increasing their rigidity as a result of oriented change of the elasticdeformable state through the application of a tensile force which, combined with the machining force, forms longitudinal-lateral strains. The paper also presents mathematical models describing the changes of the elastic-deformable state resulting from the application of the tensile force. It presents the results of experimental studies on the deformation of elastic low-rigidity shafts, performed on a special test stand developed on the basis of a lathe. An estimation was made of the effectiveness of the method of control of the elastic-deformable state with the use, as the regulating effects, the tensile force and eccentricity. It was demonstrated that controlling the two parameters: tensile force and eccentricity, one can improve the accuracy of machining, and thus achieve a theoretically assumed level of accuracy.Key words low rigidity shaft, control of machining accuracy, mathematical models of machining, efficiency, mechanics of machine tools
The article presents an original machine-learning-based automated approach for controlling the process of machining of low-rigidity shafts using artificial intelligence methods. Three models of hybrid controllers based on different types of neural networks and genetic algorithms were developed. In this study, an objective function optimized by a genetic algorithm was replaced with a neural network trained on real-life data. The task of the genetic algorithm is to select the optimal values of the input parameters of a neural network to ensure minimum deviation. Both input vector values and the neural network’s output values are real numbers, which means the problem under consideration is regressive. The performance of three types of neural networks was analyzed: a classic multilayer perceptron network, a nonlinear autoregressive network with exogenous input (NARX) prediction network, and a deep recurrent long short-term memory (LSTM) network. Algorithmic machine learning methods were used to achieve a high level of automation of the control process. By training the network on data from real measurements, we were able to control the reliability of the turning process, taking into account many factors that are usually overlooked during mathematical modelling. Positive results of the experiments confirm the effectiveness of the proposed method for controlling low-rigidity shaft turning.
The paper focuses on the problem of control of accuracy of forming elastic-deformable shafts with low rigidity. In particular, results of analysis of basic factors affecting the accuracy of machining of low-rigidity shafts such as the stiffness of the technological system, geometry of cutting tool, lathe temperature, degree of cutting tool wear, cutting tool strength, lubrication-cooling fluid and machining parameters are presented. Moreover, the performed analysis encompassed the effect of stiffness of particular elements of the technological system, the analytical relations determining the changes of defined parameters, values of elasticity of the fixed headstock and tailstock, as well as of the stiffness of the machining system from the zones of rigidity of the parts. To analyse appearing errors in the real industrial conditions, the study was realized on the example of manufacturing precision mechanics tooling in two and a single pass, with the application of specific parameters of machining.
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