Today, energy consumption and environmental issues are important topics in all industries around the globe. However, quality is in direct proportion with energy consumption, since better surface finish means more energy consumption. The main objective of this work is minimizing both surface roughness and power consumption by estimating the optimum machining parameters. In this study, turning tests were carried out on three different hardened AISI 1040 steels (10, 15, 20 HRC) at three different depths of cuts (1.2, 2.4, 3.6 mm), feed rates (0.15, 0.25, 0.35 mm × rev−1) and cutting speeds (120, 140, 160 m × min−1) without coolant. The effects of cutting parameters and workpieces hardness on surface roughness, sound level and power consumption were examined. These analyses were conducted using a full factorial experimental design method. The response surface methodology and analysis of variance were also used to determine the effects of input parameters on the response variables. Experimental results showed that an increase in the feed rate value causes an increase in the surface roughness, the sound level, and the power consumption values. The results of the presented work show that feed rate is the most effective machining parameter that affects surface roughness and power consumption. Following feed rate, depth of cut and cutting speed also have an important impact. Thus, decreasing the value of feed rate and depth of cut will reduce the amount of power consumption.

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Recently, hard turning became an interesting method to the manufacturers as an alternative to the grinding process due to its superior features such as good surface quality, good productivity, lower production costs, lower power consumption, and shorter processing time. Despite its considerable benefits, hard turning is a difficult process that needs advanced cutting inserts such as ceramics and cubic boron nitride. However, these cutting inserts are costly and should be used properly by choosing appropriate machining parameters.In the presented work, the hard turning process was performed to investigate the machinability of AISI S1 cold work tool steel using a cubic boron nitride insert. The relation between machining parameters namely, depth of cut, cutting speed, and feed rate on the responses such as power consumption, surface roughness, and machining sound was found using a full factorial orthogonal array of response surface methodology.In addition, analysis of variance was used to identify the most important machining parameters that influence output parameters. Based on the results, surface roughness was dominantly affected by feed rate, whereas, sound and power consumption were influenced by all machining parameters especially cutting speed and feed rate. A good agreement between the experimental and the predicted values were observed.

In recent years, the necessity for energy in the manufacturing industry has become an important problem because fossil fuel reserves are decreasing in order to produce energy. Therefore, the efficient use of energy has become an important research topic. In this study, energy efficiency is investigated in detail for sustainable life and manufacturing. AISI 4140 material with high hardness of 50 HRC hardness has been applied cryogenic process to improve mechanical and machinability properties. In this experiment study, the effects of feed rate (0.04, 0.08, 0.12 mm/rev), cutting speed (140, 160, 180 m/min), depth of cut (0.05, 0.10, 0.15 mm) and tool radius (0.4, 0.8) on energy consumption, surface roughness and sound intensity were investigated. Then, a new mathematical model with high accuracy was developed. Total power consumption was calculated by considering the instantaneous current value and machining time. As a result, it is found that good surface quality obtained when the feed rate is low, and the tool radius is high and the machining time is shortened, the energy consumption is reduced due to the increase in cutting speed, depth of cut and feed rate. Also, it is found that the tool radius has a limited effect on energy consumption, but low feed value increases energy consumption.

In this study, the relationship between the spindle vibration and surface roughness was investigated and the effect of the cutting parameters on surface roughness and spindle vibration during the machining of Aluminum alloy 7075 (Al 7075) were determined. Experimental studies have been carried out on a CNC turning machine using coated cemented carbide cutting tools under dry cutting environment. L64 full factorial design of experiments was used to investigate the optimal machining parameters for spindle vibration and surface roughness. The influences of machining parameters on vibration and surface roughness were evaluated by using analysis of variance (ANOVA) and main effect plots. The results revealed that the feed rate was the most effective cutting parameters on spindle vibration and surface roughness. The machine tool vibration amplitude and surface roughness values were significantly increased with increasing cutting feed. The depth of cut and cutting speed have the least effect on the spindle vibration and indicated an insignificant effect on surface roughness. Mathematical equations were developed to predict the vibration and surface roughness values using the regression analysis.