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    Nesting Problems in Additive Manufacturing: Classification and Review

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    Date
    2026
    Author
    Tang, Aohua
    Fu, Guang
    Zhang, Tao
    Song, Pengpeng
    Xiao, Xiaomin
    Peng, Qingguo
    Mo, Taiqian
    Zhang, Ansi
    Zhang, Zhengwen
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    Abstract
    Abstract. At the heart of the nesting dilemma in additive manufacturing (AM) lies the intricate task of meticulously arranging a multitude of geometrically distinct parts within the printing space, striving to optimize material and spatial efficiency to their utmost limits. Throughout the various phases of AM, from standalone production platforms to parallel operations across multiple units, nesting challenges remain a pivotal aspect that permeates the entire manufacturing process. Due to the complexity and diversity of nested problems, solutions in different scenarios often vary greatly. Effective classification can help us better understand the characteristics, challenges, and solution strategies of various nested problems, and provide more targeted guidance and optimization solutions for practical production. The fundamental value of this study resides in its exhaustive review and synthesis of nesting problems in AM, where the graphical representation of nested components is termed “image mapping.” Subsequently, we have categorized 75 articles into 8 distinct classes, based on their respective focus on image mapping, nesting, and nesting optimization algorithms. A rigorous analysis of these categories not only offers a comprehensive and in-depth appraisal of the nesting problem in AM but also sparks a thought-provoking discussion and outlines promising avenues for future research endeavors.
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4315773
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