ABSTRACT
Machining high-strength structural steels often requires challenging processes. It is essential to improve the machinability of such materials, which are frequently needed in industrial manufacturing areas. Recently, it has become necessary to enhance the machinability of such materials using different nanopowders. In this study, different cooling/lubricating (C/L) liquids were prepared with cellulose nanocrystal (CNC) nanopowder. The aim was to improve the machinability properties of Dillimax 690T material with the prepared CNC-based cutting fluids. CNC nanopowders were added to 0.5% distilled water by volume, and a new nanofluid was produced. Unlike previous studies, base synthetic oil and CNC-based cutting fluid were sprayed on the cutting area with a double minimum quantity lubrication (MQL) system. Machinability tests were carried out by milling. Two different cutting speeds (Vc = 120-150 m/min), two different feed rates (f = 0.05-0.075 mm/tooth), and four different C/L environments (dry, MQL oil, CNC nanofluid, MQL oil + CNC nanofluid) were used in the experiments. In the study, where a total of 16 experiments were performed, cutting temperature (Tc), surface roughness (Ra), tool wear (Vb), and energy consumption results were analyzed in detail. According to the test results, significant improvements were achieved in the machinability properties of the material in the experiments carried out using CNC nanofluid. In particular, the hybrid C/L environment using MQL oil + CNC nanofluid improved all machinability metrics by over 15% compared to dry machining. In short, using CNC nanopowders offers a good milling process of Dillimax 690T material with effective lubrication and cooling ability.
ABSTRACT
Because of their high thermal conductivity, good corrosion resistance, and great mechanical qualities, copper matrix composites are appealing materials utilized in a variety of industries. This study investigates the mechanical properties of copper-graphite (Cu-Gr) matrix composites reinforced with silicon carbide (SiC) and tungsten carbide (WC) particles by hot pressing using powder metallurgy method. The goal is to investigate the influence of the reinforcement ratio on the mechanical characteristics of copper composite materials generated (density, hardness, flexural strength, and wear resistance). SEM, EDS, and X-RD analysis were used to perform metallographic examinations. The highest relative density with a value of 98.558% was determined in the C3 sample. The findings revealed that when the reinforcement ratio was raised, the hardness rose. The highest hardness value was observed in the C6 sample with an increase of 12.52%. Sample C4 (with the lowest SiC and WC particles ratio) had the highest bending stress (233.18 MPa). Bending stress increased by 35.56% compared to the C1 sample. The lowest specific wear rates were found in the C4 sample, with a decrease of 82.57% compared to the C1 sample. The lowest wear rate (6.853 × 10-7 mm3/Nm) also occurred in the C4 sample. The microstructural analysis showed that the hybrid reinforcement particles exhibited a homogeneous distribution in the copper matrix. X-RD analysis showed that there was no intermediate reaction between the parent matrix and the hybrid reinforcements. A good interfacial bond was observed between the matrix structure and the hybrid reinforcements. The motivation of this research was to utilise the advantages of the unique features of SiC-WC hybrid particles to improve the performance of newly developed Cu-6Gr composites for wear-resistance applications.
ABSTRACT
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.
ABSTRACT
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.
ABSTRACT
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.
