Abstract: Providing sufficient provisions to transfer heat from the work-tool interface is a key to improve tool life and surface integrity. With the conventional flood cooling system where the coolant is directed towards the work-tool interface at very low pressure, there are possibilities for the coolant to get heated up and produce vapors which in turn insulates the cutting zone from the coolant. This reduces the purpose of coolant. Supplying coolant at very high pressure and very high velocity may provide the best control to reduce cutting temperature and tool wear and correspondingly increases tool life. This paper deals with an experimental investigation on the effect of high pressure coolant on surface finish in cylindrical turning of AISI 1060 Steel using tungsten carbide turning insert. Surface Roughness values are captured with different cutting speed and feed rates with high pressure and low pressure coolant supply. It is observed that there was a considerable improvement in surface finish with the use of high-pressure coolant (HPC) under various cutting speed and feed rate.
Abstract: Unconventional machining process finds heavy application in aerospace, automobile and in production industries where accuracy is most needed. This process is chosen over other traditional methods because of the advent of composite and high strength materials, multifaceted parts and also because of its elevated precision. Regularly in unconventional machines, trial and error method is used to fix the values of process parameters. An algorithm incorporating Artificial Neural Network (ANN) is proposed to create mathematical model functionally relating process parameters and operating parameters of a wire cut electric discharge machine (WEDM) and copper is the work piece. This is accomplished by training a learning algorithm of feed forward neural network with back propagation. The required data used for training and testing the ANN is obtained by conducting trial runs in wire cut electric discharge machine. Proposed algorithm paves reduction in time for fixing the values for the process parameters and thus reduces the production time along with reduction in cost of machining processes and thereby increases the production as well as the efficiency. The programs for training and testing the neural network are developed, using matlab 7.0.1 package.
Abstract: The generation of heat during machining at the cutting zone adversely affects the surface finish and tool life. The heat at the cutting zone, which plays a negative role due to poor thermal conductivity, resistance to wear, high strength at high temperatures and chemical degradation can be overcome by the use of proper lubrication. Advancements in the field of tribology have led to the use of solid lubricants replacing the conventional flood coolants. This work involves the use of nanoparticulate graphite powder as a lubricant in turning operations whose performance is judged in terms of cutting forces, tool temperature and surface finish of the work piece. The experimentation revealed the increase in cutting forces and the tool temperature when the solid lubricant used is decreased in particle size. The surface finish deteriorated with the decrease in particle size of the lubricant in the nanoregime.
Keywords-Turning, Solid lubricant, Graphite, Minimum Quantity Lubrication, nano–particles,
Weight percentage , Friction coefficient.
Abstract: In this study, the effect of tool wear is correlated with acoustic emission (AE) signal during microendmilling of aluminium alloy (AA 1100). The AE signals were acquired using Kistler make AE sensor and the signal features are analyzed in time domain (root mean square (RMS)) and frequency domain (dominant frequency and amplitude). The dominant frequency of the AE signal shows increasing trend with increase in the tool wear, where as AERMS show uneven trend. The discrete wavelet transformation technique (DWT) has also been carried out by decomposing the required AE signal in different frequency bands. The AERMS and specific AE energy were computed for the decomposed AE signals. From the specific AE energy, it is observed that shearing occurs during microendmilling and also found to be similar that of macro-regieme endmilling. The result demonstrated that the AE signals are potential indicator for tool condition monitoring in microendmilling.
Abstract: In this work, an online acoustic emission (AE) monitoring system is developed, to investigate the effect of tool wear during the microturning of titanium alloy with a tungsten carbide insert of nose radius 0.1 mm. The AE signal parameters were analyzed in time domain, frequency domain and discrete wavelet transformation (DWT) techniques to correlate with the tool wear status. The root mean square (AERMS) and specific AE energies are also computed for the decomposed AE signals, using the DWT. The results demonstrated that dominant frequency and DWT techniques are found to be most suitable for online tool condition monitoring, using AE sensors in the microturning of titanium alloy.
Abstract: This paper investigates the relationship of process parameters in wire electrical discharge machining of titanium alloy with brass wire as tool electrode. Wire electrical discharge machining (WEDM) is used to cut conductive metals of any hardness or that difficult to cut with conventional methods. The process performances such as material removal rate (MRR) and surface finish (Ra) were evaluated by giving specific input parameters which practiced to obtain optimal response. The difficulty in machine tool industry is to predict the expected output performance for the desired input variables by the way of conducting more number of experiments for different machining parameters, which leads to the increase in consumption of electric power, material and time. To overcome this phenomenon, parametric investigation was made on WED machining on titanium alloy by using Taguchi’s method.
Abstract: Titanium is one of the important kinds of material used in different engineering fields. They have very good properties like high strength to weight ratio, superior corrosion resistance and thermal properties. They are very attractive materials and has application aerospace, biomedical and automotive field. they are classified to be “difficult-to-Machine materials” as they posses poor thermal properties, poor machinability, etc.The prime important is with the study of machining characteristics and the optimization of the cutting parameters. In this paper Titanium alloy (Ti-6Al-4V) is taken, the dry turning experiments are carried out in semi-automatic lathe using poly crystalline diamond (PCD) cutting tool insert. The taguchi’s design of L27 orthogonal array is done by four machining factors namely cutting speed, feed, nose radius and depth of cut at three levels. The optimal machining conditions are arrived by Signal-Noise ratio method with respect to surface roughness (Ra). The analysis of variance (ANOVA) and the percentage of contribution of feed, cutting speed, nose radius and depth of cut for better surface roughness is validated using S/N ratio. In this result indicated that the feed is a vital parameter followed by cutting speed, the nose radius and then by depth of cut. The worn out surface of the insert is examined by using scanning electron microscope (SEM).
Abstract: The non-convectional machining processes are those using thermal source of energy for the material removal. Among them Electrical discharge machining (EDM) or spark erosion machining is most important one. The important process parameters in this technique are discharge pulse on time, discharge pulse off time current and gap voltage. The values of these parameters significantly affect such machining outputs as material removal rate. In this paper, an axisymmetric thermo-physical finite element model for the simulation of single sparks machining during electrical discharge machining (EDM) process is exhibited. The model has been solved using ANSYS 11.0 software. A transient thermal analysis assuming a Gaussian distribution heat source with temperature-dependent material properties has been used to investigate the temperature distribution. Material removal rate was calculated for multi-discharge machining by taking into considerations the number of pulses. Comparison, analyzation of the theoretical result and experimental result by considering the same process parameters has been done, and the result is highly agreed between the experimental and theoretical value so the model is validated.
Abstract: Accompanying the development of mechanical industry, the demand for alloy materials having high hardness, toughness and impact strength are increasing. As these materials pose severe difficulty to be machined by conventional methods, Wire-cut Electric Discharge Machining (Wire EDM) machines are employed to machine them. The ultimate requirement of any machining process being fine surface finish, is accurately satisfied by wire-cut EDM process. Hence this project aims at obtaining the best surface finish by optimizing various process parameters affecting the machining conditions. With the assistance of Taguchi quality engineering, various number of experiments will be conducted by varying the process parameters at various levels. The output response variable being surface roughness, will be measured for all the number of experiments conducted. As the lowest value of surface roughness indicates the best surface finish, the optimum parameter level combination would be analyzed which gives desired surface finish. These optimized values of various parameters would then be used in performing machining operation in order to obtain desirable outputs.