Genetic Algorithms for the Optimal Multi-Objective design of simple and progressive cutting and punching dies

• Rolando Esteban Simeón Monet ^[1] ; José Arzola Ruiz ^[2]
  1. [1] Universidad de Holguín

     Universidad de Holguín

     Cuba

     
  2. [2] Technical University of Havana
• Localización: Sinergias en la investigación en STEM / coord. por Ana María Beltrán Custodio, Manuel Félix Ángel, 2021, ISBN 978-84-122093-4-1, págs. 9-12
• Idioma: inglés
• Enlaces
  • Texto Completo Libro (pdf)
• Resumen

  • Traditional CAD systems are design aid tools and make it possible to prepare higherquality decisions in less time than non-automated manual design. However, withoutthe application of optimization and decision-making tools, these systems areconceptually not prepared to carry out designs that approximate the best possiblecompromise between the designer’s efficiency indicators. In the present work, theresults of the application of the Genetic Algorithms Method to the optimal multiobjectivedesign of simple and progressive cutting and punching dies are presented.The designed system pursues the objective of generating die design options thatprovide compromise solutions close to the global optimum for the value of anobjective function.