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In recent years, companies in the rocket and space industry have been actively transitioning to a customized production approach, where production parameters can be adjusted to meet specific orders. This is associated with the rapid development of additive manufacturing technologies, which enable the production of metal parts with complex shapes and allow for the control of the metal microstructure by adjusting the process parameters. This makes it possible to produce products with unique mechanical properties and complex internal microstructure at a reduced time and cost. The application of advanced additive manufacturing technologies involves establishing a set of parameters for each subprocess that will impact the quality of the final product. The paper analyzes the main parameters affecting the quality of the final product in additive manufacturing and discusses a binary multicriteria mathematical model for selecting an optimal parameter vector based on the chosen additive technologies.

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Modeling the Optimal Vector of Technological Parameters in the Context of Rocket and Space Industry Production

  • 会议论文

  • 发表日期：

    2026年

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  • Andrey V. Smirnov,
  • Ivan D. Sidelnikov,
  • Alla E. Brom

摘要

In recent years, companies in the rocket and space industry have been actively transitioning to a customized production approach, where production parameters can be adjusted to meet specific orders. This is associated with the rapid development of additive manufacturing technologies, which enable the production of metal parts with complex shapes and allow for the control of the metal microstructure by adjusting the process parameters. This makes it possible to produce products with unique mechanical properties and complex internal microstructure at a reduced time and cost. The application of advanced additive manufacturing technologies involves establishing a set of parameters for each subprocess that will impact the quality of the final product. The paper analyzes the main parameters affecting the quality of the final product in additive manufacturing and discusses a binary multicriteria mathematical model for selecting an optimal parameter vector based on the chosen additive technologies.