▎ 摘　　要

Hardox (R) 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 good surface quality minimizes the occurrence of cracks generating higher fatigue resistance. However, the characteristics of this steel make it difficult 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 difficulties, the paper aims to investigate the performance of multilayer graphene-based nanofluid applied in reduced quantity (NF-RQL) on surface roughness generated by finishing end milling of Hardox (R) 450 when compared to dry and flood machining. The cutting parameters at three levels were combined, randomized and analyzed via Box-Behnken design. The experimental results showed that the lowest roughness on average values was obtained with NF-RQL (R-a = 0.207 mu m), followed by flood machining (R-a = 0.326 mu m). The Abbott-Firestone and amplitude probability distribution statistical analysis indicated a greater uniformity of peaks and valleys in the roughness profile obtained by NF-RQL milling than in the other lubricooling environments. All prediction models demonstrated an excellent ability to estimate the roughness values (R-squared > 85%). After the multivariate optimization, NF-RQL and flood conditions generated similar average roughness values (respectively, 0.106 mu m and 0.115 mu m). However, the material removal rate with NF-RQL (2315 mm(3)/min) is about 83% higher than flood (1266 mm(3)/min), justifying its better performance.