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An effective selective assembly model for spinning shells based on the improved genetic simulated annealing algorithm (IGSAA)

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Abstract

For cylinder shell parts produced in batches, computer-aided selective assembly can not only obtain higher product matching accuracy, but also reduce the remaining number of parts, ensuring the welding assembly quality and improving the production efficiency. Aiming at the selective assembly problem for spinning shells with electron beam welding, a selective assembly model based on an improved genetic simulated annealing algorithm was proposed. By analyzing the assembly process characteristics of spinning shells, mapping association matrix of assembly constraints was built to describe the assembly relationship between the different cylinder of spinning shells. Considering the multi-assembly quality loss function using SNR and assembly yield, a multi-objective comprehensive optimization model was established. Based on the measured internal diameter of the parts, a specific coding method and the adaptive cross mutation operator based on the sigmoid curve is introduced to apply an improved genetic simulated annealing algorithm (IGSAA), solving the assembly selection problem of 5 shell parts case. The results show that the model established has a good applicability to the spinning shell parts matching problem, which can effectively improve the success rate of parts matching and assembly accuracy, and meet the production needs of enterprises. Moreover, the produced assembly difference through improved genetic simulated annealing algorithm (IGSAA) is even better than manual selection in matching accuracy and efficiency.

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Funding

This work is supported in by the National Natural Science Foundation of China (52005098) and the Opening Foundation of Shanxi Key Laboratory of Advanced Manufacturing Technology (No.XJZZ202003). The authors wish to record their gratitude for their generous supports.

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Authors and Affiliations

  1. Collega of Mechanical Engineering, Donghua University, Shanghai, 201620, China

    Hu Zhou, Qiwei Zhang, Chongjun Wu & Zhen You

  2. Shanxi Key Laboratory of Advanced Manufacturing Technology, North University of China, Taiyuan, 030051, Shanxi, China

    Chongjun Wu & Yao Liu

  3. Manufacturing Research Center, Georgia Institute of Technology, Atlanta, 30332, USA

    Chongjun Wu & Steven Y. Liang

Authors
  1. Hu Zhou
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  2. Qiwei Zhang
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  3. Chongjun Wu
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  4. Zhen You
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  5. Yao Liu
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  6. Steven Y. Liang
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Contributions

Hu Zhou designed and carried out the whole work. Chongjun Wu conducted the model setup and validation. Qiwei Zhang and Zhen You worked together to finish the paper writing. Yao Liu and Steven Y. Liang contributed to polish the manuscript.

Corresponding author

Correspondence to Chongjun Wu.

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Zhou, H., Zhang, Q., Wu, C. et al. An effective selective assembly model for spinning shells based on the improved genetic simulated annealing algorithm (IGSAA). Int J Adv Manuf Technol 119, 4813–4827 (2022). https://doi.org/10.1007/s00170-021-08580-4

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  • DOI: https://doi.org/10.1007/s00170-021-08580-4

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