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.

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