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A novel parameter decision approach in hobbing process for minimizing carbon footprint and processing time

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Abstract

Manufacturing industry has paid more attention to the carbon footprint in the manufacturing process with an increasing focus on ecological environment. Also, optimum machining parameters are usually considered as an efficient solution for minimizing carbon footprint and processing time owing to their great role in process control. To make a better process parameter set, a novel multi-objective parameter decision approach called multi-objective grey wolf optimizer (MOGWO) is adopted to realize the decision process in gear hobbing. First, the problem of gear production is elaborated in detail and the characteristics of carbon footprint in light of hobbing process are synthetically analyzed; the carbon footprint model and processing time model are established subsequently. Second, a parameter decision approach for multi-objectives is presented followed by thorough optimization approach. Finally, a case study is put into practice for verifying the presented parameter decision-making scheme. The results demonstrate good hobbing process parameter solutions under the proposed decision approach, and it reveals a certain functional relationship between carbon footprint and processing time in view of the graphic display.

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Acknowledgments

This work was supported by the Key Projects of Strategic Scientific and Technological Innovation Cooperation of National Key R&D Program of China (No. 2020YFE0201000).

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Authors and Affiliations

  1. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China

    Hengxin Ni, Chunping Yan & Yifan Liu

  2. College of Internet of Things (IOT) Engineering, Hohai University, Nanjing, China

    Weidong Cao

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  1. Hengxin Ni
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  2. Chunping Yan
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  3. Weidong Cao
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  4. Yifan Liu
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Correspondence to Chunping Yan.

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Ni, H., Yan, C., Cao, W. et al. A novel parameter decision approach in hobbing process for minimizing carbon footprint and processing time. Int J Adv Manuf Technol 111, 3405–3419 (2020). https://doi.org/10.1007/s00170-020-06103-1

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  • DOI: https://doi.org/10.1007/s00170-020-06103-1

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