Papers by Keyword: S/N Ratio

Abstract: In this work, an attempt is made to reduce Molding defects using Taguchi Method. The input parameters used are Runner Lower Diameter, Runner Upper Diameter, Runner height, In gate height, and Pouring time. The response parameters selected as per the study of molding process requirements of the industry are Product yield(%). The L8 orthogonal array is used as per Taguchi method. The experimentation is conducted and the responses are measured. Significant progress has been made in determining the appropriate values of molding process variables to expand molding quality using diverse techniques during the last few decades. The design of sand-molding process variables has been recognized as one of the most critical aspects of molding quality. This research work focuses on improving the molding quality and yield percentage. The data analysis is made by S/N ratio and ANOVA. The result revealed the optimal setting to minimize the defect.

Abstract: Surface finish plays an important role in making quality products in the manufacturing sector. A turning experiment is conducted by cutting tool of nose radii (1 mm and 0.65 mm) to find its influence on surface roughness. Eight experiments were performed with Taguchi’s Orthogonal Array (OA) technique. The prime objective was to investigate the tool nose radius effects in the prediction of the optimum value of surface roughness. Cutting speed (V), feed (F), depth of cut (D), and tool nose radius (NR) were selected for the experimental work having two levels each. To find out the influential parameters analysis of variance (ANOVA) was carried out. Signal to noise ratio and average performance graph was analyzed to obtain optimum response values. The results concluded that the large nose radius develops a superior finish in comparison to the smaller one.

Abstract: Recently Metal injection molding is selected as a vital process in producing large amount of small part with complex geometry and intricate shape. This process is lead to solve cost effective issue in manufacturing fields. Feedstock composition behavior categorized as one of impact factor in determines the victories in metal injection molding process. Thus this paper is focused on optimizing the strength of green part by applied Taguchi Method L9 (3⁴) as optimization tools during injection process. The composition of feedstock is 55% powder loading (PL) were injected by injection molding machine .Several injection parameter were optimized such as injection temperature (A), barrel temperature (B), injection pressure (C) and Speed (D) The results analyzed by using Signal to Noise Ratio (S/N ratio) terms. The highest green strength is A₂, B₂, C₂, and D₂

Abstract: The objective of the study is to conduct experiments to investigate the performance of Electrochemical Micromachining (EMM) process to drill micro-holes on Copper alloy and analyze the parameters to optimize by Taguchi method. An EMM setup developed in-house is used to conduct the experiments. Copper alloy as workpiece, Stainless Steel needle of sharp conical edge as tool and Sodium Nitrate as electrolyte are used. A Pulse generator is used to supply pulsed current. The input parameters analyzed for optimization are Voltage, Pulse on-time and Electrolyte Concentration. The Material Removal Rate (MRR) and Overcut are taken as output parameters to study the process performance. The experiment was designed according to L9 Orthogonal Array (OA) of Taguchi design. The observations have shown that the MRR increases and the accuracy decreases when the level of input value for any parameter is increased. The process parameters are optimized using Taguchi Analysis.

Abstract: Diesel is a primary source of fuel consumed around the globe. Diesel, being a fossil fuel is expected to get over by 2050. Diesel operated vehicles normally emits high level of poisonous gases like NOx, CO₂, HC etc. During the various researches, it was being found that vegetable oils exhibit the properties closer to diesel. Few changes in the properties of vegetable oils have resulted in efficient results and allowed us to replace diesel. The present work investigates the emission of diesel engine at various parameters, when lemongrass oil is blended with diesel in various proportions at different levels of injection pressure. The diesel engine was tested on load condition of 25%, 50%, 75% and 100%. Whereas ,injection pressure is varied from 200 to 220 bar at an interval of 20 bar with 10BD, 20BD and 30BD blends of biodiesel. Very small amount of nanocatalytic substance (MgO) is being used i.e. 15ppm, 30ppm and 45ppm to enhance the combustion properties of bio-fuel. The results Shows reduction in NOX HC and CO without sacrificing fuel efficiency. These confirmation results proves that good agreement of predicted values.

Abstract: This objective of this article is to present a new technique of nanofluids/MQL in high speed milling by using MWCNTs. In the past, studies have shown the MQL process can improve tool life and surface accuracy in high speed cutting. The purpose of using carbon nanotubes is to increase the thermal conductivity of cutting fluid and to reduce the temperature during the cutting and decrease the thermal wear of tool. The proposed study is to investigate the characterization of the MWCNTs/ nanofluids combined with MQL during the high speed milling of AISI 1050 and AISI P21 experimentally. The Taguchi robust design was also used to optimize the parameters of nozzle with respect to tool feed direction, such as spraying distance, angle of ejection, and relative locations for improving the MWCNTs/MQL cutting effect. Experimental results showed the MWCNTs/ nanofluid had the benefits of improving surface roughness and reducing wear of tool in high speed milling. The results were compared to dry cutting, and wet cutting in detail.

Abstract: Surface roughness has a significant effect on the performance of machined components. In the present study, a total of 49 end milling experiments on AISI H13 steel are conducted. Based on the experimental results, the signal-to-noise (S/N) ratio is employed to study the effects of cutting parameters (axial depth of cut, cutting speed, feed per tooth and radial depth of cut) on surface roughness. An ANN predicting model for surface roughness versus cutting parameters is developed based on the experimental results. The testing results show that the proposed model can be used as a satisfactory prediction for surface roughness.

Abstract: As the population of the world is continuously increasing, the demand of the mechanical manufactured products is also increasing. Machining is the most important process in any mechanical manufacturing, and in machining two factors i.e. Material removal rate (MRR) and Surface roughness (SR) are the most important responses. If the MRR will be high, the product will get desired shape in minimum time so the production rate will be high, but we could not scarify with the surface finishing also because in close tolerance limit parts like in automobile industry if the surface is rough exact fit cannot take place. So here aim is to maximise MRR and minimise surface roughness and process control variable are taken to be transverse speed, standoff distance, abrasive flow rate, and water pressure. Here Grey relational analysis is used to convert multi responses into single response and optimal parameter setting and most significant parameter is found with the help of S/N ratio.

Abstract: Ultrasonic welding (USW) is a solid-state joining process in which the joint is created between the workpieces by the application of high frequency ultrasonic waves under pressure. Poor weld strength is one of the major problem experienced in the application of such weldments. It is mainly due to improper selection of process parameters. In order to achieve satisfactory weld strength optimization of welding process parameters is indeed essential. In this present context, the USW has been carried out to join dissimilar materials like A1100 aluminum alloy and CuZn37 brass plates of thickness 0.1 mm using Taguchi’s L₁₆ orthogonal array design of experiments. The process parameters like amplitude, weld pressure and weld time have been taken into consideration. Taguchi’s S/N ratio concept has been employed to study the effect of different process parameters on the response like tensile strength; and finally, the optimum setting of process parameters has been decided in view of maximizing tensile strength. The predicted result of the optimized tensile strength has been validated by conducting a confirmatory test. This analysis shows that the high quality and efficient joints can be generated by exploring optimized setting of process parameters which is fruitful in mass production as well as off-line quality control of such a welding practice.

Abstract: Electro discharge machining (EDM) is a process that uses an electric sparks to generate the high temperature and melt the workpiece. One of the EDM process is drilling. In EDM drilling, an electro thermal mechanism is introduced between the electrode and work piece to create the hole. The hole size is dependent on the diameters of electrode used during the drilling process. The present study performs Taguchi method to investigate the optimal process parameters for high-speed EDM super drill machine that is used to make a small hole. The workpiece used is made from titanium alloy (Ti-6: ASTM B348 Grade 5) and the copper electrode is 2.0 mm in diameter. In this experiment, the process parameters that were selected to be optimised are: current pulse off, maximum current and standard voltage levels. An orthogonal array L₉ were employed to analyze the hole enlargement and material removal rate (MRR) depending on 2.0 mm diameter hole penetration. The optimum EDM parameters for hole making process was established and verified with the acquired results.