This experimental study is conducted to determine statistical models of cutting forces in hard turning of AISI H11 hot work tool steel (∼ 50 HRC). This steel is free from tungsten on Cr-Mo-V basis, insensitive to temperature changes and having a high wear resistance. It is employed for the manufacture of highly stressed diecasting moulds and inserts with high tool life expectancy, plastic moulds subject to high stress, helicopter rotor blades and forging dies.The workpiece is machined by a mixed ceramic tool (insert CC650 of chemical composition 70%Al 2 O 3 +30%TiC) under dry conditions. Based on 3 3 full factorial design, a total of 27 tests were carried out. The range of each parameter is set at three different levels, namely low, medium and high. Mathematical models were deduced by software Minitab (multiple linear regression and response surface methodology) in order to express the influence degree of the main cutting variables such as cutting speed, feed rate and depth of cut on cutting force components. These models would be helpful in selecting cutting variables for optimization of hard cutting process.The results indicate that the depth of cut is the dominant factor affecting cutting force components. The feed rate influences tangential cutting force more than radial and axial forces. The cutting speed affects radial force more than tangential and axial forces.
The present study, aims to investigate, under turning conditions of hardened AISI H11 (X38CrMoV5-1), the effects of cutting parameters on flank wear (VB) and surface roughness (Ra) using CBN tool. The machining experiments are conducted based on the response surface methodology (RSM). Combined effects of three cutting parameters, namely cutting speed, feed rate and cutting time on the two performance outputs (i.e. VB and Ra), are explored employing the analysis of variance (ANOVA). Optimal cutting conditions for each performance level are established and the relationship between the variables and the technological parameters is determined using a quadratic regression model. The results show that the flank wear is influenced principally by the cutting time and in the second level by the cutting speed. Also, it is that indicated that the feed rate is the dominant factor affecting workpiece surface roughness.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.