TY - JOUR
T1 - Regression analysis of hardness property of laser additive manufactured (LAM) Ti and TiB2metal matrix composite
AU - Aladesanmi, V. I.
AU - Fatoba, O. S.
AU - Akinlabi, E. T.
AU - Ikumapayi, O. M.
N1 - Funding Information:
The authors wish to acknowledge the financial support offered by Pan African University for Life and Earth Sciences Institute (PAULESI), Ibadan, Nigeria for the payment of article publication charges (APC).
PY - 2021/4/27
Y1 - 2021/4/27
N2 - 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.
AB - 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.
KW - Hardness property
KW - Laser additive manufactured
KW - Metal matrix composite
KW - Regression analysis
KW - Titanium alloy
UR - http://www.scopus.com/inward/record.url?scp=85105605599&partnerID=8YFLogxK
U2 - 10.1016/j.matpr.2020.11.252
DO - 10.1016/j.matpr.2020.11.252
M3 - Conference article
AN - SCOPUS:85105605599
VL - 44
SP - 1249
EP - 1253
JO - Materials Today: Proceedings
JF - Materials Today: Proceedings
SN - 2214-7853
IS - Part 1
T2 - 11th International Conference on Materials Processing and Characterization
Y2 - 15 December 2020 through 17 December 2020
ER -