Research on the Optimization of High-Precision Grinding Process Parameters for Gear Shafts Based on Response Surface Methodology
Release time:
2024-12-31
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Research was conducted on abnormal noise occurring in a certain transmission, identifying the fundamental cause of the problem as non-conformance in roundness, and subsequently pinpointing the failure occurrence time during the high-precision grinding process of the outer circle of the gear shaft. Five significant factors affecting roundness were identified. Using the central composite response surface method, factors and their levels were designed, and a matrix of 108 random experiments was generated using Minitab software. Analysis of the results from the 108 experiments revealed that the first-order and second-order square terms of the model significantly affected the abnormal noise, while the second-order interaction effects were not significant. Residual analysis confirmed that the model met the assumptions, leading to the optimal solution of the model regression equation. Additionally, based on the model, factor parameters were adjusted, processing time was shortened, production efficiency was improved, and the issue of non-conformance in roundness during the high-precision grinding process was resolved. The study indicates that this method can identify curved and nonlinear relationships within the model, achieving a globally optimal solution. Furthermore, the established model provides a basis for adjusting parameters in the part processing process.
Gear shafts and other components are widely used in various fields of automobile manufacturing, particularly in automotive power systems. With the release of the "Energy Saving and New Energy Vehicle Technology Roadmap 2.0," the technology roadmap for energy saving and new energy has become clear. From a national strategic perspective, energy-saving vehicles, new energy vehicles, and intelligent connected vehicles have been elevated to a core strategic development position. From a market perspective, new energy vehicles are expected to become mainstream products by 2035. In 2021, the production and sales of new energy vehicles both exceeded 3.5 million units, a year-on-year increase of 1.6 times. In the field of new energy vehicle power transmission systems, the vehicle drive unit has shifted from traditional engines to electric motors, making vehicles quieter and raising the requirements for noise, vibration, and harshness (NVH) performance of the entire vehicle transmission system. To achieve better NVH performance, the grinding process of gear shafts primarily relies on high-precision grinding. However, in practical processing, even with high-precision processing equipment, there can still be dimensional deviations and insufficient process capability of part dimensions, leading to abnormal noise in the power system. Therefore, optimizing equipment parameters during the processing to ensure part dimensions are qualified and the processing process is stable is of significant practical value and relevance for improving product quality.
Currently, the response surface method, as an optimization technique, has begun to be applied across various industries: in the power system, optimization of electronic water pump impellers; in the chip industry, multi-objective optimization of the SiC single crystal cutting process; in the railway system, optimization of magnetic levitation switched reluctance motors; and in the automotive industry, optimization research on the laser welding process of turbocharger wastegate valves. At the same time, various fields are also using the models obtained from the response surface method for prediction and pre-control. This study achieved optimization of process control parameters through response surface experimental analysis of high-precision grinding process parameters, and ultimately provided guidance for setting high-precision grinding processing parameters through the obtained model.
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