Bibliographic citations
Barboza, L., (2022). Automatización de la optimización del diseño de elementos mecánicos mediante algoritmo genético aplicando ingeniería del conocimiento [Pontificia Universidad Católica del Perú]. http://hdl.handle.net/20.500.12404/23460
Barboza, L., Automatización de la optimización del diseño de elementos mecánicos mediante algoritmo genético aplicando ingeniería del conocimiento []. PE: Pontificia Universidad Católica del Perú; 2022. http://hdl.handle.net/20.500.12404/23460
@mastersthesis{renati/531231,
title = "Automatización de la optimización del diseño de elementos mecánicos mediante algoritmo genético aplicando ingeniería del conocimiento",
author = "Barboza Usco, Linder Oskar Jesús",
publisher = "Pontificia Universidad Católica del Perú",
year = "2022"
}
The objective of this study is to develop a tool that allows to streamline and generalize the mechanical design process of a specific component, taking into consideration that the design stage is one of the most important within the production process of a piece, because that is where they can be generated the greatest economic savings through the qualities of the product (ergonomics, weight, volume, quality, etc.). In that sense, finding a way to develop this process in a personalized way and with the ability to adapt it to the working conditions of the company that seeks to use it, will improve its performance. In order to be able to implement this tool, three concepts had to be linked: the mechanical design itself, which are the technical definitions, parametric formulas and mechanical criteria that are used when designing a mechanical element; knowledge engineering, which is the branch of engineering that will give us the basic concepts of how to extract the information embodied within a process and transfer it to a workflow; and finally, the bio-inspired algorithms, specifically, the genetic algorithm, which is the one that will optimize the design process based on the input data that will be previously captured.
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