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Experimental data-set for prediction of tool wear during turning of Al-1061 alloy by high speed steel cutting tools

In this investigation, the dataset presented will give important information to understand the area of cutting tool wear during turning operations, tool nature is the most difficult tasks in manufacturing process, particularly in the locomotive industry. With the view to optimize the cutting paramet...

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Detalles Bibliográficos
Autores principales: Okokpujie, I.P., Ohunakin, O.S., Bolu, C.A., Okokpujie, K.O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997575/
https://www.ncbi.nlm.nih.gov/pubmed/29900294
http://dx.doi.org/10.1016/j.dib.2018.04.003
Descripción
Sumario:In this investigation, the dataset presented will give important information to understand the area of cutting tool wear during turning operations, tool nature is the most difficult tasks in manufacturing process, particularly in the locomotive industry. With the view to optimize the cutting parameters, the tests were carried out to investigate tool wear on high speed steel (HSS) during turning operation of aluminium 1061 alloy and to developed mathematical models using least squares method. The cutting parameters chosen for this investigation are cutting speed, feed rate, and radial depth of cut were used as input parameters in order to predict tool wear. The experiment was designed by using full factorial 3(3) in which 27 samples were run in a Fanuc 0i TC CNC lathe. After each test, scanning electron microscope (SEM) is used to measure the cutting tool in other to determine the tool wear.