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An energy-based modeling and prediction approach for surface roughness in turning

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Abstract

Nowadays, the manufacturing industries are continuously challenged by achieving high-quality products and clean production in order to remain competitiveness. Surface roughness is one of the important factors in evaluation of the quality of a machined part. Meanwhile, it is vital to correlate energy usage with operations being performed in the production lines for the green and energy-saving manufacturing. A novel surface roughness prediction model based on the energy consumption is proposed. Specific cutting energy consumption (SCEC) and cutting parameters are employed as inputs to the prediction model. Particle swarm optimization-support vector machine (PSO-SVM) is used to predict the surface roughness value in turning. Furthermore, this method is verified by conducting experiments in turning process and compared with the PSO-relevance vector machine (PSO-RVM). Besides, the prediction performance of the energy based model is compared with the model with different combinations of cutting parameters, energy, and vibration features. The result shows that the proposed model obtains the lowest mean relative error and indicates that the model is effective and straightforward for practical implementation.

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Acknowledgments

This work is supported by National Natural Science Foundation of China (Grant No. 71471139) and Zhejiang Provincial Natural Science Foundation of China (Grant No. LY14E050020), MITT Intelligent Manufacturing Project of China. The study of interconnection standard and experimental verification in the intelligent manufacturing plant for naval architecture and marine engineering

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Authors and Affiliations

  1. Sino-German College of Applied Science, Tongji University, Shanghai, 201804, China

    Nan Xie

  2. School of Mechanical Engineering, Tongji University, Shanghai, 201804, China

    Junfeng Zhou

  3. College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou, Zhejiang, 325035, China

    Beirong Zheng

Authors
  1. Nan Xie
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  2. Junfeng Zhou
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  3. Beirong Zheng
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Correspondence to Nan Xie.

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Xie, N., Zhou, J. & Zheng, B. An energy-based modeling and prediction approach for surface roughness in turning. Int J Adv Manuf Technol 96, 2293–2306 (2018). https://doi.org/10.1007/s00170-018-1738-y

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  • DOI: https://doi.org/10.1007/s00170-018-1738-y

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