Investigation on the surface roughness modeling and analysis for ultra-precision diamond turning processes constrained by the complex multisource factors

Abstract

Ultra-precision machining is widely used in the manufacturing of national defense and sophisticated civil products because of its high precision, nearly no surface damage and other advantages. The surface roughness of a workpiece is the key indicator of ultraprecision machining technology, which is affected by many factors in the process of machining. However, the existing surface roughness prediction model only considers a single error factor between the tool and workpiece, lacking comprehensive consideration of multisource error factors. Therefore, based on the research of the single error factor, multisource errors that affect the surface roughness of a workpiece in machining was investigated in this paper. A prediction model of workpiece surface roughness under multisource error affecting was established to improve the accuracy of prediction models. According to the vibration model, the sensitive direction of roughness can be determined. In the axial direction, the error of each point on the surface is superimposed with the theoretical surface shape to obtain the final surface profile. The three-dimensional morphology was established and the two-dimensional topography can be obtained by intercepting the three-dimensional topography. The roughness simulation value is obtained by extracting the peak value of each point of the two-dimensional topography. A single-point diamond turning experiment is performed to verify the simulation models. The result concluded from the experiment is compared with the simulation result, showing that the error between the simulation and the experiment is less than 4%, which is of great significance to optimizing machining process parameters and improving machining precision of workpiece surfaces for ultraprecision single point diamond turning.

Genetic algorithm-based error correction algorithm for CNC turning machining of mechanical parts

“…Mechanical parts are usually machined using multiple tool passes to ensure machining quality and minimize DE. Although smaller cutting amounts can reduce DE, they can lead to long machining times and reduced productivity [17][18]. Therefore, to achieve a certain level of productivity in the turning of mechanical parts, it is essential for choosing the parameters with the shortest machining time as the optimization target.…”

An Efficient Structural Optimization Method for the Hinge Beam of a Cubic Press

“…Diamond is the hardest, strongest, and most wear-resistant material found in nature, and it is widely used in aerospace, geological drilling, medical and military defense [1][2][3][4][5]. The high price and low production limits of natural diamonds require synthetic diamonds to meet the industry's great demand [6,7].…”