The complex structure of turning aggravates obtaining the desired results in terms of tool wear and surface roughness. The existence of high temperature and pressure make difficult to reach and observe the cutting area. In-direct tool condition, monitoring systems provide tracking the condition of cutting tool via several released or converted energy types, namely, heat, acoustic emission, vibration, cutting forces and motor current. Tool wear inevitably progresses during metal cutting and has a relationship with these energy types. Indirect tool condition monitoring systems use sensors situated around the cutting area to state the wear condition of the cutting tool without intervention to cutting zone. In this study, sensors mostly used in indirect tool condition monitoring systems and their correlations between tool wear are reviewed to summarize the literature survey in this field for the last two decades. The reviews about tool condition monitoring systems in turning are very limited, and relationship between measured variables such as tool wear and vibration require a detailed analysis. In this work, the main aim is to discuss the effect of sensorial data on tool wear by considering previous published papers. As a computer aided electronic and mechanical support system, tool condition monitoring paves the way for machining industry and the future and development of Industry 4.0.

Tribological properties of engineering components are a key issue due to their effect on the operational performance factors such as wear, surface characteristics, service life and in situ behavior. Thus, for better component quality, process parameters have major importance, especially for metal matrix composites (MMCs), which are a special class of materials used in a wide range of engineering applications including but not limited to structural, automotive and aeronautics. This paper deals with the tribological behavior of Cu-B-CrC composites (Cu-main matrix, B-CrC-reinforcement by 0, 2.5, 5 and 7.5 wt.%). The tribological characteristics investigated in this study are the coefficient of friction, wear rate and weight loss. For this purpose, four levels of sliding distance (1000, 1500, 2000 and 2500 m) and four levels of applied load (10, 15, 20 and 25 N) were used. In addition, two levels of sliding velocity (1 and 1.5 m/s), two levels of sintering time (1 and 2 h) and two sintering temperatures (1000 and 1050 °C) were used. Taguchi’s L16 orthogonal array was used to statistically analyze the aforementioned input parameters and to determine their best levels which give the desired values for the analyzed tribological characteristics. The results were analyzed by statistical analysis, optimization and 3D surface plots. Accordingly, it was determined that the most effective factor for wear rate, weight loss and friction coefficients is the contribution rate. According to signal-to-noise ratios, optimum solutions can be sorted as: the highest levels of parameters except for applied load and reinforcement ratio (2500 m, 10 N, 1.5 m/s, 2 h, 1050 °C and 0 wt.%) for wear rate, certain levels of all parameters (1000 m, 10 N, 1.5 m/s, 2 h, 1050 °C and 2.5 wt.%) for weight loss and 1000 m, 15 N, 1 m/s, 1 h, 1000 °C and 0 wt.% for the coefficient of friction. The comprehensive analysis of findings has practical significance and provides valuable information for a composite material from the production phase to the actual working conditions.

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The aim of this study was to determine the effect of different ratios Cr particle reinforcement on the hardness and wear resistance of Cu matrix composites produced by using (P/M) method. Cr particles were added at different weight ratios of 5, 10 and 15%, in pure Cu dust. The prepared mixtures were shaped under a pressure of 400 MPa. The shaped pieces were sintered at 900°C for 30 min. The success of the sintering process was evaluated by examining the intensity and SEM images. Microscope studies were performed using scanning electron microscopy (SEM). Hardness measurement method was used for determining hardness. In the SEM analysis, it was observed that the Cr phase was uniformly distributed in the Cu matrix composed of coaxial grains. In addition, an increase in the hardness was observed depending on the increase in the Cr ratio. The wear behaviors of the composite materials produced were investigated by pin-on-disk wear test. As the disk, a surface-hardened AISI 1050 steel was used. As a result of this examination, composite materials; depth of wear, losses in the weight, variation of friction coefficient, variation of wear diameters at 0.4 m/s shear rate and 1500 m shear distance were investigated by applying 50 N and 75 N loads. As a result of these investigations, it has been found that as the Cr particle reinforcement ratio in the Cu matrix composites increases, hardness and the wear resistance were increased positively.

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The features of composite materials such as production flexibility, lightness, and excellent strength put them in the class of materials that attract attention in various critical areas, i.e., aerospace, defense, automotive, and shipbuilding. However, the machining of composite materials displays challenges due to the difficulty in obtaining structural integrity. In this study, Cu/Mo-SiCP composite materials were produced by powder metallurgy with varied reinforcement ratios and then their machinability was investigated. In machinability experiments, the process parameters were selected as cutting speed (vC), feed rate (f), depth of cut (aP), and reinforcement ratio (RR). Two levels of these parameters were taken as per the Taguchi’s L8 orthogonal array, and response surface methodology (RSM) is employed for parametric optimization. As a result, the outcomes demonstrated that RR = 5%, f = 0.25 mm/rev, aP = 0.25 mm, vC = 200 m/min for surface roughness, RR = 0%, f = 0.25 mm/rev and aP = 0.25 mm and vC = 200 m/min for flank wear and RR = 0%, f = 0.25 mm/rev, aP = 0.25 mm, vC = 150 m/min for cutting temperature for cutting temperature and flank wear should be selected for the desired results. In addition, ANOVA results indicate that reinforcement ratio is the dominant factor on all response parameters. Microscope images showed that the prominent failure modes on the cutting tool are flank wear, built up edge, and crater wear depending on reinforcement ratio.