Computational analysis and optimization in chemical components proportions for improved mechanical properties in unalloyed titanium: a fuzzy-based multi-objective approach.

Identifying the optimal chemical composition for unalloyed titanium is the principal objective of this investigation, which seeks to enhance its mechanical properties. To determine the effect of chemical component proportions on mechanical parameters such as modulus, elongation, tensile strength, and yield strength, a comprehensive linear regression analysis is employed in the first step of the approach. The second step is to determine the optimal proportions for enhancing mechanical performance using a fuzzy-based multi-objective optimization approach. The material's behaviour can be better understood if the significant relationships between mechanical properties and chemical component proportions are identified. The application of linear regression analysis can do this. Since fuzzy-based optimization is adept at dealing with imprecise and ambiguous data, it can help with a complex decision-making process that aims to find a middle ground between competing goals. This study adds to our understanding of the relationship between the proportions of the different chemical components and mechanical properties of unalloyed titanium by integrating linear regression and fuzzy-based multi-objective optimization. In addition, it provides material engineers with a workable framework for improving mechanical performance in a variety of contexts through the optimization of component proportions. [ABSTRACT FROM AUTHOR]