Determination of the Predictive Labor Intensity of Manufacturing Parts on CNC Lathes Using the Feature Recognition

Abstract

The problem of labor intensity operational forecasting of manufacturing parts on CNC lathes is considered. As a method, the recognition of structural and technological elements (features) of a part according to its 2D model was chosen to calculate the predictive labor intensity of machining. The processing of parts of the “sleeve” type on CNC lathes is considered. The feature recognition process is implemented in the form of an applied CAD/CAM system, which is fed with an electronic 2D model and a table of parameters of the manufactured surfaces. These parameters include accuracy and surface roughness requirements, the type of thread being cut, its pitch, the coordinates of the start and end points of the thread. At the output, a running program (NC) is formed for a CNC machine, designed in the form of standard cycles. Automatic assembly of NC becomes possible due to the use of technological templates for processing typical structural elements specially developed for this purpose. Technological templates are developed for all features typical for turning operation (end, open zone, semi-open zone, closed zone, and thread). For external and internal surfaces of the part technological templates are different, because various tools and strategies for constructing trajectories are used to process them. Formalization of closed area processing is of particular difficulty. Therefore various types of closed zones (undercut, groove, groove for thread exit, and face undercut) are classified at the stage of recognition. A separate technological template for their processing has been created for each type of closed areas. To determine the complexity, a standard simulation module NC is used. The results of model adaptation to current production are obtained.