5. Conclusions
In this paper, cutting tool selection was carried out by using a conventional CNC
machine and by applying the method of an intelligent system for the geometry of a workpiece,
such as turning and milling. The following conclusions have been reached.
The tool path length was presented based on an intelligent tool selection method as well
as the complexities of the workpiece geometries. Also, the tool path for the rotational part is
described by the application of the Matlab software (Fig. 4). In our case, two cutting tools
were used for rough and final machining, the crucial time was carried out within the Matlab
environment and described in relation to tool selection and machining parameters which had a
direct influence on the optimizations of the machining processes.
GAs were utilized except for the tool selection method and at the same time the crucial
times for rough and finished tool path of the turret CNC machine tools are optimized. The red
line shows the tool path for rough machining, and the blue line shows the tool path for final
machining (see above). The tool path length was carried out within the environment of the
Matlab software. Fig. 5 presents the optimization process for the tool selection model. The
analysis of the crucial time and tool selection was performed by estimations of the machining
parameters and the tool paths for rough and final machining processes. The results are
presented in Table 2 for each run for the lower and upper bounds, the number of iterations, as
well as the initial values. The optimum results for our case have shown only one from three
results for the first case, with 52 current iterations, and the best value based on the objective
function value was obtained: 12.469034886859806.