Surface roughness analysis in finishing end milling of Hardox® 450 steel using multilayer graphene-based nanofluid

Abstract

Hardox® 450 is a structural steel commonly used in the mining and agricultural sectors due to its hardness and toughness combined with high abrasion wear resistance. It is widely known that a good surface quality minimizes the occurrence of cracks generating higher fatigue resistance. However, the characteristics of this steel make it di cult to cut, resulting in greater complexity in the choice of process parameters. Additionally, the general industry concern for clean machining encourages the use of lubricooling conditions with less environmental impact. In order to address these di culties, the paper aims to investigate the performance of multilayer graphene-based nano uid applied in reduced quantity (NF-RQL) on surface roughness generated by nishing end milling of Hardox® 450 when compared to dry and ood machining. The cutting parameters at three levels were combined, randomized, and analyzed via Box-Behnken Design. The experimental results showed that the lowest roughness values were obtained with NF-RQL, followed by ood machining. The Abbott-Firestone and Amplitude Distribution statistical analysis indicated a greater uniformity of peaks and valleys in the roughness pro le obtained by NF-RQL milling than in the other lubricooling environments. All prediction models demonstrated excellent ability to estimate the roughness values. The levels of cutting parameters obtained from the multivariate optimization generated similar roughness values for NF-RQL and ood conditions. However, the material removal rate with the rst condition is about 83% higher, justifying its better performance.