Manufacturing Technology 2021, 21(5):616-626 | DOI: 10.21062/mft.2021.080

Prediction of Surface Roughness and Optimization of Process Parameters for Slow Tool Servo Turning

Hangyan Guo ORCID..., Min Kang ORCID..., Wei Zhou ORCID...
College of Engineering, Nanjing Agricultural University, No.40, Dianjiangtai Road, Pukou Distinct, Nanjing 210031. China.

Surface roughness is an important index to evaluate the quality of a machined surface. In order to accurately predict the surface roughness for slow tool servo (STS) turning, taking toric surface as an example, response surface methodology (RSM) was used to perform the process test. The second-order response surface prediction model was established and the variance analysis and reliability test were carried out. The results showed that the average prediction error was 7.6%. In order to obtain the best process parameters, standard particle swarm optimization (PSO) was used. The results showed that the global optimization ability of standard PSO was poor. In order to solve the problem, compression factor was introduced and particle swarm optimization with compression factor (WCF-PSO) was constructed, which enhanced the convergence of PSO effectively. WCF-PSO was used to optimize the process parameters and the results obtained were Rt=0.87mm, af =0.01mm/r, ap=0.05mm, Δθ=8.70°, with a corresponding surface roughness of Ra=0.0486μm. The results of the verification test showed that the actual value was Ra=0.0520μm, and the error was only 7.0%, indi-cating that WCF-PSO had a better optimization effect.

Keywords: Slow tool servo, Response surface methodology, Prediction model, Particle swarm optimization, Optimization of process parameters
Grants and funding:

Project supported by Jiangsu graduate research and practice innovation program (KYCX19_0607)

Received: June 11, 2021; Revised: August 29, 2021; Accepted: October 15, 2021; Prepublished online: October 21, 2021; Published: November 25, 2021  Show citation

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Guo H, Kang M, Zhou W. Prediction of Surface Roughness and Optimization of Process Parameters for Slow Tool Servo Turning. Manufacturing Technology. 2021;21(5):616-626. doi: 10.21062/mft.2021.080.
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