Microstructure Alterations of Ti-6Al-4V ELI during Turning by Using Tungsten Carbide Inserts under Dry Cutting Condition

Titanium alloys possesses a hexagonal close packed(h.c.p) structure, called phase to ambient temperature. Thisstructure changes to body center cubic (b.c.c), called phase tothe temperature of 882 C. Machining process that generates hightemperature during machining can affect on microstructures ofmachined surface, which represents as a quality of components.The turning parameters evaluated are cutting speed (55 - 95m/min), feed rate (0.15 - 0.35 mm/rev), depth of cut (0.10 - 0.20mm) and tool grade (uncoated, CVD and PVD). The aims of thispaper are to investigate the effects of machining process onmicrostructures of machined surface and chip were machinedusing tungsten carbide inserts under dry cutting condition. Theresults show that machining at high cutting speed (95 m/min)affected on the microstructure significantly at the end ofmachining. The temperature is the most significant factoraffected on microstructure of the machined surface and chip atshear zone. The changes of microstructure were also affected bythe tool pressure during cutting

The correlation of surface roughness and tool edge condition under sustainable cryogenic machining

This paper investigates the correlation between surface roughness of Inconel 718 and tool edge condition of ball nose inserts when milled at high speed. The cutting parameters were varied as follows; cutting speed: 120–140 m/min, feed rate: 0.15–0.25 mm/tooth, and axial depth of cut: 0.3–0.7 mm. For a sustainable machining approach, the experimental works were carried out under a smooth supply of cryogenic coolant which is a mix of liquid CO2, gas CO2, and compressed air. The experimental results revealed that the range of surface roughness obtained is from 0.114 to 0.197 µm. Along the cutting process, the tool wear patterns such as the abrasion, chipping, and the intermittent build-up-edge near the depth of cut cause the rapid increase of tool wear as well as the roughness of the machined surface with a significant correlation between them. However, the roughness was slowly reduced and became stable with the increase of notch wear. The finding could be used as a prediction reference for monitoring surface roughness and tool wear progress under cryogenic conditions. It also provides foundations for further research on machinability under this sustainable approach

OPTIMIZATION OF INJECTION MOLDING PARAMETERS: IMPROVING MECHANICAL PROPERTIES OF KENAF REINFORCED POLYPROPYLENE COMPOSITES

Natural fiber composites offer significant benefits as alternative material composites in terms of renewable materials. Therefore, natural fibers are commonly used in automotive industries primarily as interior and exterior parts. The manufacturing process of the automotive parts is essential to minimize the defects such as residual stress with better mechanical properties. Hence, this study focused on the employment of rational design of experiment (DOE) to determine the optimized injection molding parameters by improving the mechanical properties of kenaf fibers reinforced polypropylene composites. Taguchi method with L27 (34)orthogonal array applied to optimize the injection molding process parameters, based on the highest response of the strength properties generated by S/N ratio using the larger the better. Moreover, ANOVA analysis was employed to evaluate the most significant parameter including injection temperature, injection pressure, holding pressure and injection rate which affected the mechanical properties. The confirmation test was conducted to verify the predicted range of optimum mechanical properties. Results indicated that the optimum injection molding parameter obtained with the injection temperature at 190 °C, injection pressure at 1300 bar, holding pressure at 1900 bar, and the injection rate at 20 cm³/s. Implementing the optimum parameters is able to fabricate better mechanical properties of kenaf/PP composites where most of the confirmation mechanical strength values are evaluated within the predicted range or lie near the acceptable limits

Machining of titanium alloys with coated and uncoated carbide tools

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Flank wear and I-kaz 3D correlation in ball end milling process of Inconel 718

Tool wear may deteriorate the machine product quality due to high surface roughness, dimension exceeding tolerance and also to machine tool itself. Tool wear monitoring system is vital to be used in machining process to achieve high quality of the machined product and at the same time improve the productivity. Nowadays, many monitoring system developed using various sensor and statistical technique to analyze the signals being used. In this paper, I-kaz 3D method is used to analyze cutting force signal in milling process of Inconel 718 for monitoring the status of tool wear in milling process. The results from analyzing cutting force show that I-kaz 3D coefficient has a correlation with cutting tool condition. Tool wear will generate high value of I-kaz 3D coefficient than the sharp cutting tool. Furthermore, the three dimension graphical representation of I-kaz 3D for all cutting condition shown that the degree of scattering data increases with tool wear progression

Surface roughness prediction model of 6061-T6 aluminium alloy machining using statistical method

This paper explores on the optimization of the surface roughness of milling mould 6061-T6 aluminium alloys with carbide coated inserts. Optimization of the milling is very important to reduce the cost and time for machining mould. The purposes of this study are to develop the predicting model of surface roughness, to investigate the most dominant variables among the cutting speed, feed rate, axial depth and radial depth and to optimize Surface Roughness Prediction Model of 6061-T6 Aluminium Alloy Machining Using Statistical Method the parameters. Response surface method based optimization approach was used in this study. It can be seen from the first order model that the feed rate is the most significantly influencing factor for the surface roughness. Second-order model reveals that there is no interaction between the variables and response

THE EFFECT OF WEDM CUTTING PARAMETER ON INCONEL 718 SUBSURFACE MICROHARDNESS

This paper reports on the effect of wire electrical discharge machine (WEDM) cutting parameter on the subsurface hardness of Inconel 718. The response surface methodology (RSM) using Box-Behnken design was used to conduct the experiment and analyze the relationship between control variables and responses. A total of 8 runs was carried out during the experiment. The Historical Data of Response Surface Methodology (RSM) was used as a tool of design of experiment (DOE). The selected WEDM parameters were Voltage (40-42V), feed rate (6-8V) and current (0.5-1.5 mm/min). The subsurface hardness was measured at the distance of 50 μm, 100 μm, 300 μm, 500 μm beneath the cutting surface. Observation of the results shows that the subsurface hardness is higher at the distance of 50μm than 500 um. The hardness was gradually decreased toward bulk hardness of HV0.1 270. Analysis of variance (ANOVA) was used to identify the significant effect of the factors on the response. Based on the analysis, feed rate and current were found to be the most significant factors in hardness change. Mathematical models were developed for hardness prediction with an average error of 2.7%. The minimum hardness change of HV0.1 30 was obtained by the combination of feed rate = 1.29 mm/min, servo voltage = 40.33 V, current = 7.94 A