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An improved grey wolf optimizer for minimizing drilling deformation and residual stress in AA2024 sheet

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Abstract

Aiming at the problem of large deformation and residual stress after drilling of aircraft skin Aluminum Alloy 2024 (AA2024) sheet, an Improved Grey Wolf Optimizer (IGWO) is proposed to optimize its fixture layout to make the deformation and residual stress smaller. A layout coding scheme is designed to obtain the maximum deformation and residual stress under different fixture layouts. Then, a kriging prediction model is developed with a prediction error of 3.7% for deformation and 2.2% for residual stress. The model is integrated with the IGWO to provide a comprehensive set of optimal solutions. The specific improvements of IGWO included initializing the population with good point set to increase population diversity, incorporation of Lévy flight to prevent local optimum, adjustable distance control parameter tuning for balance the global and local searches and optimizing the population by non-dominated sort and crowding distance. In addition, experimental studies and algorithmic comparisons are carried out to verify the efficacy of both the proposed model and the algorithm.

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Funding

This work is supported by the National Natural Science Foundation of China (Grant No. 52205148), the China Postdoctoral Science Foundation (Grant No. 2023M731392) and the doctoral scientific research foundation of Hubei University of Technology (BSQD2020007).

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Authors Rui Wu and Shiyao Huang designed this methodology and were responsible for initial draft. Author Wenqian Zhang organized and analyzed the data. Authors Huan Xue and Min Zhu provided technical support in the analysis. Authors Zhong Zheng and Tao Li contributed to the improvement of the manuscript.

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Correspondence to Huan Xue.

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Wu, R., Huang, S., Zhang, W. et al. An improved grey wolf optimizer for minimizing drilling deformation and residual stress in AA2024 sheet. Int J Adv Manuf Technol 130, 4443–4458 (2024). https://doi.org/10.1007/s00170-023-12905-w

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