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.