International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

This paper presents the application of an experimental method for determining the numerical values of the machinability factors of medium alloy carbon steel in the drilling process. Research conditions are defined, including tools, machine, and machining parameters. The experiment was performed according to a two-factor orthogonal experimental plan, and the values of cutting forces were monitored using a dynamometer through other elements of the information measuring system. Cutting forces were also considered in relation to the drilling depth.

SYSTEMIn the paper is analyzed the dynamics of a movable block, consist of two boring tool with oppositely positioned cutting inserts, applied as a cutting part of tools for combined machining of deep holes by cutting and surface plastic deformation. Tribo-mechanical and force dependencies were derived, connecting the geometry of the cutting inserts and the friction forces in the contact surfaces of the block with its working capacity.

During the radial deformation of contouring tool, its active diameter is getting smaller than the initial one, and the cutting depth is becoming lower than planned. Thus, the diametrical size of the machined hole is always smaller than contouring tool, by value of the elastic radial deformation. In this regard, in the manufacture of contouring tool, it is necessary to make appropriate adjustments in the diametrical size of its cutting edge, depending on its elastic radial deformation.
The paper dwells on the thermo-elastic problem of calculating contouring tool for the purpose of determining the actuating diametrical size of its cutting edge, and for determining the area of the application of tool material. Solving of non-dimensional non-stationary problem is carried out by method of finite differences. At each time step, the system of algebraic equations is solved by iterative method.
There have been obtained the results for the temperature field and displacement components.

Modelling and prediction of cutting forces in metal cutting is very important, due to their significant impacts on quality of machined surface, tool wear, self-excited vibrations, etc. However, accurate modelling of the cutting forces in high pressure jet assisted machining is not a simply task due to complex relations between many highly interlinked variables of cutting process influencing these forces. The objective of this study is to utilize two artificial intelligence methods, namely particle swarm optimization (PSO) and simulated annealing (SA), for prediction of the cutting forces components in high pressure jet assisted turning of carbon steel Ck45E. A study of effect of various process parameters including feed, cutting speed and depth of cut on the cutting forces was carried out. The results obtained from the PSO and SA based models were compared with experimental results for their performance. The analysis reveals that developed models are able to make accurate prediction of cutting forces by utilizing small sized training and testing datasets.