This research work is focused on examining the turning behavior of Incoloy 800H superalloy by varying important cutting parameters. Incoloy 800H is an Iron- Nickel-Chromium based superalloy; it can withstand high temperature (810°C), high oxidization and corrosion resistance. But, it is difficult to turn in conventional machines and hence the present work was carried out and investigated. Experiments were conducted based on the standard L27 orthogonal array using uncoated tungsten inserts. The cutting force components, namely, feed force (Fx), thrust force (Fy) and cutting force (Fz); surface roughness (Ra) and specific cutting pressure (SCPR) were measured as responses and optimized using Taguchi-Grey approach. The main effects plots and analysis of mean (ANOM) were performed to check the effect of turning parameters and their significance on responses of cutting forces in all the direction (FX, FY, FZ), the surface roughness (Ra) and specific cutting pressure (SCPR). The tool wear and machined surfaces were also investigated using white light interferometer and SEM.
Grain refining and modification are common foundry practice for improving properties of cast Al-Si alloys. In general, these types of treatments provide better fluidity, decreased porosity, higher yield strength and ductility. However, in practice, there are still some discrepancies on the reproducibility of the results from grain refining and effect of the refiner’s additions. Several factors include the fading effect of grain refinement and modifiers, inhomogeneous dendritic structure and non-uniform eutectic modification. In this study, standard ALCAN test was used by considering Taguchi’s experimental design techniques to evaluate grain refinement and modification efficiency. The effects of five casting parameters on the grain size have been investigated for A357 casting alloy. The results showed that the addition of the grain refiner was the most effective factor on the grain size. It was found that holding time, casting temperature, alloy type and modification with Sr were less effective over grain refinement.
This work depicts the effects of deep cryogenically treated high-speed steel on machining. In recent research, cryogenic treatment has been acknowledged for improving the life or performance of tool materials. Hence, tool materials such as the molybdenum-based high-speed tool steel are frequently used in the industry at present. Therefore, it is necessary to observe the tool performance in machining; the present research used medium carbon steel (AISI 1045) under dry turning based on the L9 orthogonal array. The effect of untreated and deep cryogenically treated tools on the turning of medium carbon steel is analyzed using the multi-input-multi-output fuzzy inference system with the Taguchi approach. The cutting speed, feed rate and depth of cut were the selected process parameters with an effect on surface roughness and the cutting tool edge temperature was also observed. The results reveal that surface roughness decreases and cutting tool edge temperature increases on increasing the cutting speed. This is followed by the feed rate and depth of cut. The deep cryogenically treated tool caused a reduction in surface roughness of about 11% while the cutting tool edge temperature reduction was about 23.76% higher than for an untreated tool. It was thus proved that the deep cryogenically treated tool achieved better performance on selected levels of the turning parameters.
During the machining processes, heat gets generated as a result of plastic deformation of metal and friction along the tool–chip and tool–work piece interface. In materials having high thermal conductivity, like aluminium alloys, large amount of this heat is absorbed by the work piece. This results in the rise in the temperature of the work piece, which may lead to dimensional inaccuracies, surface damage and deformation. So, it is needed to control rise in the temperature of the work piece. This paper focuses on the measurement, analysis and prediction of work piece temperature rise during the dry end milling operation of Al 6063. The control factors used for experimentation were number of flutes, spindle speed, depth of cut and feed rate. The Taguchi method was employed for the planning of experimentation and L18 orthogonal array was selected. The temperature rise of the work piece was measured with the help of K-type thermocouple embedded in the work piece. Signal to noise (S/N) ratio analysis was carried out using the lower-the-better quality characteristics. Depth of cut was identified as the most significant factor affecting the work piece temperature rise, followed by spindle speed. Analysis of variance (ANOVA) was employed to find out the significant parameters affecting the work piece temperature rise. ANOVA results were found to be in line with the S/N ratio analysis. Regression analysis was used for developing empirical equation of temperature rise. The temperature rise of the work piece was calculated using the regression equation and was found to be in good agreement with the measured values. Finally, confirmation tests were carried out to verify the results obtained. From the confirmation test it was found that the Taguchi method is an effective method to determine optimised parameters for minimization of work piece temperature.
The machinability and the process parameter optimization of turning operation for 15-5 Precipitation Hardening (PH) stainless steel have been investigated based on the Taguchi based grey approach and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). An L27 orthogonal array was selected for planning the experiment. Cutting speed, depth of cut and feed rate were considered as input process parameters. Cutting force (Fz) and surface roughness (Ra) were considered as the performance measures. These performance measures were optimized for the improvement of machinability quality of product. A comparison is made between the multi-criteria decision making tools. Grey Relational Analysis (GRA) and TOPSIS are used to confirm and prove the similarity. To determine the influence of process parameters, Analysis of Variance (ANOVA) is employed. The end results of experimental investigation proved that the machining performance can be enhanced effectively with the assistance of the proposed approaches.
Aluminum alloys are widely used today in plastic injection molds in the automotive and aerospace industries due to their high strength and weight ratio, good corrosion and fatigue resistance as well as high feed rates. The 5754 aluminum alloy has high corrosion resistance and a structure suitable for cold forming. In this study, an AA 5754-H111 tempered aluminum alloy with the dimensions of 80×80×30 mm was used, and some of the materials were cryogenically heat treated. For the milling operations, ϕ12 mm diameter 76 mm height uncoated as well as TiCN and TiAlN coated end mills were used. Different levels of cutting depth (1.25, 2.0, 2.5 mm), cutting speed (50, 80, 100 m/ min), feed rate (265, 425, 530 m/ min) and machining pattern (concentric, back and forth and inward helical) were used. The number of experiments was reduced from 486 to 54 using the Taguchi L54 orthogonal array. The values obtained at the end of the experiments were evaluated using the signal-to-noise ratio, ANOVA, three-dimensional graphs and the regression method. Based on the result of the verification experiments, the processing accuracy for surface roughness was improved from 3.20 μm to 0.90 μm, with performance increase of 71.88%.
In this study, Taguchi method is used to find out the effect of micro alloying elements like vanadium, niobium and titanium on the hardness and tensile strength of the normalized cast steel. Based on this method, plan of experiments were made by using orthogonal arrays to acquire the data on hardness and tensile strength. The signal to noise ratio and analysis of variance (ANOVA) are used to investigate the effect of these micro alloying elements on these two mechanical properties of the micro alloyed normalized cast steel. The results indicated that in the micro alloyed normalized cast steel both these properties increases when compared to non-micro-alloyed normalized cast steel. The effect of niobium addition was found to be significantly higher to obtain higher hardness and tensile strength when compared to other micro alloying elements. The maximum hardness of 200HV and the maximum tensile strength of 780 N/mm2 were obtained in 0.05%Nb addition micro alloyed normalized cast steel. Micro-alloyed with niobium normalized cast steel have the finest and uniform microstructure and fine pearlite colonies distributed uniformly in the ferrite. The optimum condition to obtain higher hardness and tensile strength were determined. The results were verified with experiments.
The presence of nanoparticles in heat exchangers ascertained increment in heat transfer. The present work focuses on heat transfer in a longitudinal finned tube heat exchanger. Experimentation is done on longitudinal finned tube heat exchanger with pure water as working fluid and the outcome is compared numerically using computational fluid dynamics (CFD) package based on finite volume method for different flow rates. Further 0.8% volume fraction of aluminum oxide (Al2O3) nanofluid is considered on shell side. The simulated nanofluid analysis has been carried out using single phase approach in CFD by updating the user-defined functions and expressions with thermophysical properties of the selected nanofluid. These results are thereafter compared against the results obtained for pure water as shell side fluid. Entropy generated due to heat transfer and fluid flow is calculated for the nanofluid. Analysis of entropy generation is carried out using the Taguchi technique. Analysis of variance (ANOVA) results show that the inlet temperature on shell side has more pronounced effect on entropy generation.
Flank wear of multilayer coated carbide (TiN/TiCN/Al2O3/TiN) insert in dry hard turning is studied. Machining under wet condition is also performed and flank wear is measured. A novel micro-channel is devised in the insert to deliver the cutting fluid directly at the tool-chip interface. Lower levels of cutting parameters yield the minimum flank wear which is significantly affected by cutting speed and feed rate. In comparison to dry and wet machining, insert with micro-channel reduces the flank wear by 48.87% and 3.04% respectively. The tool with micro-channel provides saving of about 87.5% in the consumption of volume of cutting fluid and energy.
Variation in final casting dimensions is a major challenge in the investment casting industry. Additional correction operations such as die tool reworking as well as coining operations affect foundry productivity significantly. In this paper influence of basic parameters such as wax material, mould material, number of ceramic coats and feed location on the dimensional accuracy of stainless-steel casting has been investigated. Two levels of each factor were chosen for experimental study. Taguchi approach has been used to design the experiment and to identify the optimal condition of each parameter for reduced dimensional deviation. Analysis of variance has been carried out to determine the contribution of each process parameter. The result reports that selected parameters have significant effect on the dimensional variability of investment casting. Mould material is the dominant parameter with the largest contribution followed by number of ceramic coats and wax material whereas feed location is having negligible contribution.
In the calculations presented in the article, an artificial immune system (AIS) was used to plan the routes of the fleet of delivery vehicles supplying food products to customers waiting for the delivery within a specified, short time, in such a manner so as to avoid delays and minimize the number of delivery vehicles. This type of task is classified as an open vehicle routing problem with time windows (OVRPWT). It comes down to the task of a traveling salesman, which belongs to NP-hard problems. The use of the AIS to solve this problem proved effective. The paper compares the results of AIS with two other varieties of artificial intelligence: genetic algorithms (GA) and simulated annealing (SA). The presented methods are controlled by sets of parameters, which were adjusted using the Taguchi method. Finally, the results were compared, which allowed for the evaluation of all these methods. The results obtained using AIS proved to be the best.
The dry sliding wear behavior of heat-treated super duplex stainless steel AISI 2507 was examined by taking pin-on-disc type of wear-test rig. Independent parameters, namely applied load, sliding distance, and sliding speed, influence mainly the wear rate of super duplex stainless steel. The said material was heat treated to a temperature of 850°C for 1 hour followed by water quenching. The heat treatment was carried out to precipitate the secondary sigma phase formation. Experiments were conducted to study the influence of independent parameters set at three factor levels using the L27 orthogonal array of the Taguchi experimental design on the wear rate. Statistical significance of both individual and combined factor effects was determined for specific wear rate. Surface plots were drawn to explain the behavior of independent variables on the measured wear rate. Statistically, the models were validated using the analysis of variance test. Multiple non-linear regression equations were derived for wear rate expressed as non-linear functions of independent variables. Further, the prediction accuracy of the developed regression equation was tested with the actual experiments. The independent parameters responsible for the desired minimum wear rate were determined by using the desirability function approach. The worn-out surface characteristics obtained for the minimum wear rate was examined using the scanning electron microscope. The desired smooth surface was obtained for the determined optimal condition by desirability function approach.
Throughout the casting process, mold filling plays a very significant role in the casting quality control. It is important to study the effect of gating system design on ingate velocity of the metal which affects the mechanical properties of casting. The effect of varying the design of four gating system elements namely pouring cup, sprue height, runner and ingate design on the multiple responses like tensile strength and percentage elongation is studied using a Taguchi’s L9 OA. The Taguchi technique was coupled with a Grey Relational Analysis (GRA) to obtain a Grey Relational Grade (GRG) for evaluating multiple responses. ANOVA has been applied to identify the significance of different parameters and it was found that the pouring cup design and the runner cross-section along its length collectively contributed above 76% of the total GRG value. Finally, the confirmation tests were performed to validate the predicted optimized results and it established an improvement of 9.90% from the initial design.
In order to optimize the stope structure parameters in broken rock conditions, a novel method for the optimization of stope structure parameters is described. The method is based on the field investigation, laboratory tests and numerical simulation. The grey relational analysis (GRA) is applied to the optimization of the stope structure parameters in broken rock conditions with multiple performance characteristics. The influencing factors include stope height, pillar diameter, pillar spacing and pillar array pitch, the performance characteristics include maximum tensile strength, maximum compressive strength and ore recovery rate. The setting of influencing factors is accomplished using the four factors four levels Taguchi experiment design method, and 16 experiments are done by numerical simulation. Analysis of the grey relational grade indicates the first effect value of 0.219 is the pillar array pitch. In addition, the optimal stope structure parameters are as follows: the height of the stope is 3.5 m, the pillar diameter is 3.5 m, the pillar spacing is 3 m and the pillar array pitch is 5 m. In-situ measurement shows that all of the pillars can basically remain stable, ore recovery rate can be ensured to be more than 82%. This study indicates that the GRA method can efficiently applied to the optimization of stope structure parameters.