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In modern production, problems arise when modeling 3D objects using the FDM method. Among the common mistakes are insufficient attention to the geometry of the object, insufficient calculation of the thickness of the walls and details. An algorithm for analyzing the manufacturability of parts before the start of production can help avoid many problems. Determining the optimal print direction, support placement, and heat distribution are key steps that help ensure the highest manufacturing quality. It is also important to emphasize the use of mathematical calculations during design. Calculating the amount of material required, optimizing geometry to minimize weight and maximize strength are just a few examples of how math can facilitate the process. Careful advance planning and the use of advanced analytical methods can significantly improve product quality and reduce production errors. Recommendations provided at various stages of design and production create an opportunity for engineers to avoid common problems and ensure the successful implementation of projects in the field of additive manufacturing.

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3D Model Quality Assessment Algorithm for Additive Manufacturing

  • 会议论文

  • 发表日期：

    2025年

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  • Viktor Marchuk,
  • Yurii Tulashvili,
  • Iurii Lukianchuk,
  • Serhii Bazyl,
  • Vasyl Kovalchuk,
  • Oleksandr Derevyanchuk,
  • Roman Horbatiuk

摘要

In modern production, problems arise when modeling 3D objects using the FDM method. Among the common mistakes are insufficient attention to the geometry of the object, insufficient calculation of the thickness of the walls and details. An algorithm for analyzing the manufacturability of parts before the start of production can help avoid many problems. Determining the optimal print direction, support placement, and heat distribution are key steps that help ensure the highest manufacturing quality. It is also important to emphasize the use of mathematical calculations during design. Calculating the amount of material required, optimizing geometry to minimize weight and maximize strength are just a few examples of how math can facilitate the process. Careful advance planning and the use of advanced analytical methods can significantly improve product quality and reduce production errors. Recommendations provided at various stages of design and production create an opportunity for engineers to avoid common problems and ensure the successful implementation of projects in the field of additive manufacturing.