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<p>The 3D Master method streamlines the transfer of product information from design to production, utilizing 3D model files containing Product Manufacturing Information. This approach facilitates direct access to crucial data like materials, geometric dimensions, and tolerances for each step of the metal additive manufacturing (MAM) of parts. By leveraging this data, the 3D Master method enables the automation of accurate cost evaluation.</p><p>This contribution introduces a&#xa0;method leveraging the 3D Master to automate a&#xa0;precise manufacturing cost calculation for MAM parts using powder-based fusion processes. It proposes a&#xa0;frame based on the quality level of the data provided by the customer to quantify the accuracy of the estimated cost, thanks to a&#xa0;performance index (KPI). A&#xa0;build cost model based on an optimal volumetric energy density calculation achieved through a&#xa0;theoretical and statistical approach is also provided. The study, conducted on 20&#xa0;reference MAM parts of varying geometrical complexities, demonstrates a&#xa0;relative deviation of normalized actual and calculated cost difference below 10%.</p><p>This cost model and the KPI give solid foundations for a&#xa0;service provider to assess the production cost at the early stages of the production process and lay the groundwork for a&#xa0;commercial online service platform offering reliable and adapted quotes for MAM part production within minutes.</p>

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3D Master-based Method for Optimizing the Cost Calculation of PBF-LB/M Manufactured Parts

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月25日

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  • Briac Lanfant,
  • Silvan Lack,
  • Benjamin Meyer,
  • Ahmed Abdulkadir,
  • Thilo Stadelmann,
  • Daniel Schmid

摘要

The 3D Master method streamlines the transfer of product information from design to production, utilizing 3D model files containing Product Manufacturing Information. This approach facilitates direct access to crucial data like materials, geometric dimensions, and tolerances for each step of the metal additive manufacturing (MAM) of parts. By leveraging this data, the 3D Master method enables the automation of accurate cost evaluation.

This contribution introduces a method leveraging the 3D Master to automate a precise manufacturing cost calculation for MAM parts using powder-based fusion processes. It proposes a frame based on the quality level of the data provided by the customer to quantify the accuracy of the estimated cost, thanks to a performance index (KPI). A build cost model based on an optimal volumetric energy density calculation achieved through a theoretical and statistical approach is also provided. The study, conducted on 20 reference MAM parts of varying geometrical complexities, demonstrates a relative deviation of normalized actual and calculated cost difference below 10%.

This cost model and the KPI give solid foundations for a service provider to assess the production cost at the early stages of the production process and lay the groundwork for a commercial online service platform offering reliable and adapted quotes for MAM part production within minutes.