Abstract
Abstract Additive manufacturing has gained relevance in aerospace components for intricate lattice, cooling channels, complex internal structure, and lightweight strong structures. Additive manufacturing has aided cost saving by reducing part count in expensive materials. Titanium di boride is a hard ceramic with a good oxidation stability with resistance to mechanical wear. It is a hexagonal crystal structured with a non-lustrous grey appearance. It has expressed a high value of strength to density ratio, melting point, and wear resistance. A predictive correlation and relationship between the optimal parameters and the hardness was examined. The data analysis of their relationship was examined in statistical analysis. A predictive mathematical formula was derived, and a linear and quadratic polynomial regression machine learning details of the factors showed correlation.
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