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This study focused on determining the residual stress of SAE 52100 hard-turned steel. The objective was to evaluate and compare the effects of the cutting-edge geometry and cutting parameters (cutting speed, feed rate, and cutting depth) on the residual stresses of three different conventional inserts: S-WNGA08 0408S01020A 7025, T-WNGA08 0408T01020A 7025, and S-WNGA432S0330A 7025. Tests were performed on 60 samples of SAE 52100 hardened steel with an average hardness of 58.5 HRC. The circumferential residual stresses of the samples were measured by X-ray diffraction. A full factorial design of experiments with three factors and two levels each with two central points and a replicate was used for a statistical analysis. The most significant results were as follows: For all inserts, the measured residual stresses were compressive, which extended the tool lifespan. The residual stresses of the Type-S inserts were significantly influenced by the cutting speed and depth, and those of the Type-T insert were significantly influenced by the feed rate and cutting depth. In addition, the residual stresses of the insert 3 were more compressive than those of the other two types of inserts. In other words, residual stresses are more compressive for inserts with larger chamfer angles even as the principal residual stress profiles were all compressive. This work has also shown that it is possible to determine a significant statistical relationship between cutting forces and residual stresses, allowing force measurements to predict the residual stress without any information on process parameters.

This work studies the influence of machining parameters, such as cutting speed and forces, feed rate, cutting depth, and tool flank wear, on the generation of surface residual stresses in DIN 100Cr6 steel conical bearing rings submitted to a hard turning process. A complete factorial planning was used to perform the tests and projected measurement. Cutting forces were measured by a piezoelectric dynamometer and residual stresses were determined by the hole-drilling method using strain gage. Results showed that after 2000 m of tool machining, phase transformations had been observed on sample surfaces, with white layer formation, and deeper, a dark layer whose thickness varied depending on the severity level of turning and the tool wear (in machined distance). Increase in tool wear generated minor values of compressive residual stresses and the surface roughness presented almost the same values in all experiments, except when the bigger parameters were used.

This paper presents a study of the Ti-6Al-4V alloy milling under different lubrication conditions, using the minimum quantity lubrication approach. The chosen material is widely used in the industry due to its properties, although they present difficulties in terms of their machinability. A minimum quantity lubrication (MQL) prototype valve was built for this purpose, and machining followed a previously defined experimental design with three lubrication strategies. Speed, feed rate, and the depth of cut were considered as independent variables. As design-dependent variables, cutting forces, torque, and roughness were considered. The desirability optimization function was used in order to obtain the best input data indications, in order to minimize cutting and roughness efforts. Supervised artificial neural networks of the multilayer perceptron type were created and tested, and their responses were compared statistically to the results of the factorial design. It was noted that the variables that most influenced the machining-dependent variables were the feed rate and the depth of cut. A lower roughness value was achieved with MQL only with the use of cutting fluid with graphite. Statistical analysis demonstrated that artificial neural network and the experimental design predict similar results.

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This work was based on the surface integrity analysis of hardened steel, AISI 4317 case carburized, quenched and tempered with 58 HRC, obtained by a turning operation executed with CBN (cubic boron nitride) tool, varying three basic cutting parameters (cutting speed, feed rate and cutting depth). The surface integrity characterization was conducted analyzing the behavior of the surface roughness R a , residual stresses and with layer presence after turning. Also, the cutting forces were measured. The experimental planning used was a central composite design. The results and data were statistically treated by the Statistica software, enabling the generation of a mathematical model, relating the dependent variables with the independent variables. The roughness values R a obtained after the experiments ranged from 0.31 to 2.8 µm, providing an indication that is possible to replace grinding process by hard turning using CBN tools that could reduce machining time and costs. The hard turning process generated compressive residual stresses profiles and white layer formation, from 1.1 to 5.1 µm, on the surface of the samples. The penetration force showed the highest values for the turning forces measurements. The lowest values for the cutting parameters represented the optimized surface integrity of the AISI 4317 steel.