Combination Of Process Variables Research Articles

Comparative Study on EDM Parameter Optimization for Adsorbed Si3N4–TiN using TOPSIS and GRA Coupled with TLBO Algorithm

Electrical discharge machining is a thermo-physical-based material removal technique. 25 combinations of process variables were formulated with the aid of Taguchi technique for EDM of adsorbed Si3N4–TiN. Machining variables like pulse current, pulse-on time, pulse-off time, dielectric pressure, and spark gap voltage varied, and impact of each variables on the performance metrics (MRR, EWR, SR, ROC, θ, CIR, and CYL) was assessed. MCDM strategies like grey relational analysis and TOPSIS are utilized to find out the ideal arrangement of machining parameters to achieve most acute productivity of the multitude of reactions. Likewise, metaheuristic algorithm in particular GRA combined with teaching-learning-based optimization algorithm is utilized for getting global optimized input factors. Important factors like pulse current, pulse-on time, and spark gap voltage characteristically affect the outputs. It is recognized that the pulse-on time and the pulse current are the most significant input factors than others. The ideal machining parameters in view of GRA and TOPSIS techniques for acquiring better output factors are I, 12 amps; PON, 7 μsec; POFF, 4 μsec; DP, 12 kg/cm2; and SV, 36 volts.

Prediction of quality attributes (mechanical strength, disintegration behavior and drug release) of tablets on the basis of characteristics of granules prepared by high shear wet granulation.

High shear wet granulation is commonly applied technique for commercial manufacturing of tablets. Granulation process for tablets manufacturing is generally optimized by hit and trial which involves preparation of granules under different processing parameters, compression of granules and evaluation of the resultant tablets; and adjustment is made in granulation process on the basis of characteristics of tablets. Objective of the study was to optimize the process of high shear wet granulation and prediction of characteristics of tablets on the basis of properties of granules. Atenolol granules were prepared by high shear wet granulation method, using aqueous solution of polyvinyl pyrrolidone (PVP k-30) as binder. Concentration of binder solution and granulation time were taken as process variables, both studied at three levels. Different combinations of process variables were determined by Design Expert software. Granules were evaluated for different parameters on the basis of SeDeM-ODT (Sediment Delivery Model-Oro Dispersible Tablets) expert system. Granules from all the trials were compressed using round (10.5 mm) flat faced punches at compression weight of 250 mg/tablet. Tablets were evaluated of different quality control parameters as per USP. Results showed that both the process variables had positive effect on mechanical strength of tablets and negative effect on disintegration and dissolution rate. Granule prepared with highest level of binder concentration (15%) and highest granulation time (60 sec) resulted in tablets with highest crushing strength (11.8 kg), specific crushing strength (0.328 kg/mm2), tensile strength (0.208 kg/mm2), lowest value of friability (0.19%) and highest disintegration time (10.9 min), as predicted from granules characteristics on the basis of SeDeM-ODT expert system. Drug release from Trial-13 (processed under highest level of both process parameters) was also lower than rest of the trials. It is concluded from the study that quality characteristics of tablets can be predicted from granules characteristics using SeDeM-ODT expert system. Furthermore, SeDeM-ODT expert system can also be used for optimization of the process of high shear wet granulation.

Effect of process variables on imiquimod micronization using a supercritical antisolvent (SAS) precipitation technique

This study aimed to promote the micronization of imiquimod, a poorly water-soluble immunostimulant drug, using the supercritical antisolvent (SAS) process. The effect of temperature, pressure and drug concentration on drug particle formation, size and yield was evaluated. Increasing pressure tends to increase size and decrease yield. Increasing concentration results in raises in size and yield. Increasing temperature leads to size reduction and increase in yield. The combination of process variables shows that increase in pressure and concentration leads to an increase in size and a reduction in yield, and that pressure and temperature combined, as well as the combination of temperature and concentration, leads to reduction in size and yield. The micronization process was not capable of promoting improvement in drug dissolution rate or limit. However, a significant gain was observed in data reproducibility, which can contribute considerably to the quality control of formulations containing imiquimod.

Study on Thermal Comfort Properties of Eri Silk Knitted Fabrics for Sportswear Application

ABSTRACT The main focus of this study was to develop the different types of single jersey Eri silk knitted fabrics. This study also aimed to measure the effect of knitting process parameters on the dimensional, physical, and thermal comfort properties of the fabrics, which are the essential properties to be considered for active sportswear applications. Single Jersey (SJ), Single Pique (SP), and Honeycomb (HC) knitted structures were produced using Eri silk spun yarns of three different counts (25 Tex, 17.78Tex, and 14.26Tex) and two different stitch lengths. Eighteen different Eri silk single jersey fabric samples were developed. It was found that the Eri silk single knit fabrics structures had better dimensional, physical, and thermal comfort properties with reference to sport textiles. Statistical analysis indicated that the yarn linear density and stitch length significantly influenced the thermal conductivity, thermal resistance, air permeability, and water vapor permeability of the fabrics. Finally, a suitable combination of process variables was found for the production of Eri silk knitted fabric that was suitable for sportswear application

Modelling using dimensional analysis and optimization with grey-taguchi based fuzzy approach in s-eddg of skd-11 steel

The SKD-11 steel was machined by the hybrid surface-electro discharge diamond grinding (S-EDDG) machining process with an aim to determine the optimum setting of process parameters for multi-output optimization and thereafter developed the mathematical-models of material-removal-rate (MRR), and surface-roughness (Ra) through the Dimensional Analysis method. In this research work, Grey-Taguchi based Fuzzy method is utilized for multi-output optimization of process parameters. The various process-variables selected in this research work are current, voltage, wheel speed, pulse-on-time, duty-cycle, and nozzle flushing aid. Total 18 experiments have been conducted on S-EDDG set-up according to Taguchi’s L18 orthogonal array. The response table and Analysis of Variance investigation are used to determine the optimum setting of process control-parameters and further help to determine the impact of these control-factors on the multi-output performance index (MPI). In this research work, the Dimensional Analysis method is utilized for the development of mathematical models of MRR, and Ra. The experimental results and predicted estimation of values from the developed models were compared and showed satisfactory matching between them. The optimum combination of process variables suggested by the hybrid optimization method was validated through confirmation experiment whose result depicts that aimed MPI is significantly improved by 0.435. The suggested optimum setting of process variables helps the production engineer to set-up the economical-cum-efficient process.

Modeling of Electric Discharge Wire Cut of Aviation Grade Alloy Using Fuzzy Technique

Fuzzy modeling technique is obtaining a huge revelation as prospective modeling for solving and modeling of manufacturing issues. In this research paper, fuzzy modeling technique is applied for analyzing and predicting the MRR, SR and CR during machining of aviation-grade aluminum alloy. Pulse-on time ([Formula: see text]), pulse-off time ([Formula: see text]), peak-current ([Formula: see text]) and servo-voltage ([Formula: see text]) are used as process variables. The different combinations of process variables for experimentation are designed using Box–Behnken design (BBD) of Response Surface Methodology (RSM). Results showed that [Formula: see text] is the most significant parameter for CR, MRR and SR, followed by [Formula: see text] and [Formula: see text]. It is observed that [Formula: see text] has less significance in response parameters. The confirmation experiments have also been carried out to justify the result procured by the fuzzy model. The root mean square error (RMSE) of CR, MRR and SR is 3.633, 3.586 and 3.366, respectively. Additionally, microstructure variations of machined surface are evaluated by scanning electron microscope (SEM). Micro-cracks, wire tool marks, craters and lump of debris are seen on WEDMed surfaces.

Multi response optimization of PMEDM of Ti6Al4V using Al2O3 and SiC powder added de-ionized water as dielectric medium using grey relational analysis

In the present work, surface characteristics of powder mixed electro-discharge machining (PMEDM) process are investigated using alumina and carborundum abrasive powder added dielectric fluid for titanium alloy Ti6Al4V. Deionized water is utilized as dielectric to accomplish an environmentally safe machining climate, and limit the emanation of harmful substances. Pulse ON/OFF time (TON/TOFF), discharge current (IP), and powder concentration (PC) are selected as process variables to reconnoiter characteristics of performance like surface finish, rate of material removal, and tool wear. The multi-response optimization has been performed using grey relational analysis (GRA) to establish the optimal parametric combination of process variables that gives the finest surface quality and minutest tool wear. The investigation results divulge that discharge current (IP) and powder concentration (PC) have the most significant effect on material removal rate (MRR), tool wear rate (TWR), and surface finish. The surface characteristics were evaluated by scanning electron microscope for the optimal parameters combination. The minutest value of surface roughness and tool wear rate is achieved at IP: 06 amps, TON: 05 µS, TOFF: 96 µS, and PC: 0.50 g/L. The optimized set of parameters would help process engineers to attain improved machining performance of PMEDM, economically along with desired surface characteristics.

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

This research aims to obtain optimal value for the surface roughness of the material AISI P20 on the Electrical Discharge Machining (EDM) Sinking process. In the present research, the Taguchi method is used to investigate the significant influence of process variables on the machining performance and determine the combination of process variables on the EDM process. Orthogonal array L18 (21 × 33) based on the Taguchi method is chosen for the design of experiment. The experiment is replicated twice to finding out the influence of four process variables such as type of electrode, voltage gap, on-time, and off-time on the response performance. Machining performance is evaluated by surface roughness as a response variable that had quality characteristics, smaller is better. These experimental data were analyzed using the Signal-to-noise ratio and Analysis of Variance. The analysis results show that the surface roughness is influenced by the type of electrode and on time. Combination of process variables to obtain optimal surface roughness are using graphite electrodes, and setting values of gap voltage 40 volt, on-time 250 μs, and off-time 20 μs. This combination of process variables can be applied to the manufacturing process using EDM sinking in order to produce a good quality product that determined based on the surface roughness value.

Experimental investigation and optimization of wall deflection and material removal rate in milling thin-wall parts

The selection of optimal process parameters is essential while machining thin-wall parts since it influences the quality of the product and affects productivity. Dimensional accuracy affects the product quality, whereas the material removal rate alters the process productivity. Therefore, the study investigated the effect of tool diameter, feed per tooth, axial and radial depth of cut on wall deflection, and material removal rate. The selected process parameters were found to significantly influence the in-process deflection and thickness deviation due to the generation of unfavorable cutting forces. Further, an increase in the material removal rate resulted in chatter, thus adversely affecting the surface quality during the final stages of machining. Considering the conflicting nature of the two performance measures, Non-dominated Sorting Genetic Algorithm-II was adopted to solve the multi-objective optimization problem. The developed model could predict the optimal combination of process variables needed to lower the in-process wall deflection and maintain a superior surface finish while maintaining a steady material removal rate.

Evolutionary Algorithm On Cold Metal Transfer Process For Feature Extraction

In order to achieve the desired bead geometry in a welding operation it is of prime importance to select suitable process parameters. In this research, pulsed MIG welding of 316L austenitic stainless steel is perforated and its bead geometry is studied, such as penetration depth bead width and height of reinforcement. The optimization approach based on the Genetic Algorithm (GA) is implemented to ensure the optimal combination of process variables and bead geometry. Regression model are initially generated by using experimental data. GA is then generated to optimize the parameters of the method and bead geometry parameters by minimizing the objective function based on the least square error. Pulsed MIG welded parameters was experimentally tested by microscopic analysis and EDAX analysis for three sample sets. The finding suggest that expected and experimental values are close in agreement. Finally, the effect of the welding current on the elemental composition is seen. The research shows that in the GA based method, the rate of convergence is faster.

Parameter Optimization of ASSAB XW 42 Tool Steel on End Milling Process with MQCL Using Taguchi-WPCA

Determination of a combination of process variables that are not appropriate in the end milling process will result in high surface roughness and can reduce the metal removal rate. Therefore, it is necessary to adjust the end milling process variables with the appropriate minimum quantity cooling lubrication. This study aims to obtain a combination of end milling process variables on ASSAB XW-42 material using the Taguchi-WPCA method to minimize arithmetic roughness (Ra), quadratic roughness average (Rq), and average roughness from peak to valley (Rz), and maximize metal removal rate (MRR) simultaneously. The cooling fluid method used is the minimum quantity of cooling lubrication (MQCL). The end milling process variable that is varied is the cutting fluid (soluble oil and vegetable oil), spindle speed (178 rpm, 310 rpm, and 570 rpm), feed rate (33.5 mm / minute, 59.4 mm / minute and 111.9 mm / minute) and the cutting depth (0.125 mm, 0.25 mm and 0.5 mm). The cutting tool used in this study is solid carbide end mill having four cutting edges with a diameter of 10 mm. The experimental design of the L18 orthogonal array was used in this study. The results showed that the optimal roughness of the workpiece surface and metal removal rate (MRR) was given by vegetable oil cutting fluid, 570 rpm of spindle speed, 33.5 mm / minute of feed rate, and 0.25 mm of the cutting depth. The Cutting fluid, spindle speed, and feed rate have a significant effect on the response variables observed simultaneously.

Semi-empirical model for depth of cut in abrasive waterjet machining of metal matrix composites

Abrasive waterjet machining (AWJM) is one of the versatile unconventional machining processes presently followed in several industries in the machining of variety of engineering materials. Achieving maximum depth of penetration is a prime requirement to achieve higher productivity. As the AWJM involves several process variables, selecting the right combinations of process variables to achieve maximum depth of cut (h) is a cumbersome and time-consuming process. Thus, scientific way of choosing process variables is being attempted by many researchers through suitable modeling techniques. This paper focuses on the development of semi-empirical model using Buckingham’s π theorem to predict the depth of cut (h) during AWJM of unreinforced and reinforced aluminum metal matrix composites (MMCs) and is compared with regression model and experimental data. Experiments were designed according to Box–Behnken method, and cutting trials were performed on unreinforced aluminum and 5%, 10% and 15% volume fraction of boron carbide (B4C)-reinforced 6063 aluminum alloys, MMCs by keeping the process parameters of water pressure (p), mesh size (ms), mass flow rate (ma) and traverse speed (u) each at three levels. The experimental results of depth of cut (h) at different levels of process parameters were analyzed through ANOVA. Based on the experimental results, the combinations such as #80 mesh size, 340 g/min mass flow rate, 200 MPa water pressure and 60 mm/min traverse speed, resulted in higher depth of cut (h). The experimental, semi-empirical and regression models were compared. The models’ predictions are in good agreement with the experimental data under the corresponding conditions.

Multi objective optimization of wire electrical discharge machining on Inconel 718 using Taguchi grey relational analysis

Inconel 718 one of the Superalloy which is a high performance material that possess special features such as better mechanical properties, creep strength, oxidation and corrosion resistance and thermal resistance and considered as a difficult to machine material because of its poor machinability by traditional machining methods due to its low thermal diffusivity and high strength. To overcome such kind of shortcomings, nontraditional approach of material removal processes have been developed and expected to be a suitable substitute method for traditional methods of machining. Wire Electrical Discharge Machining (WEDM) is one of the variant developed from the perception of Electrical Discharge Machining (EDM) process that is predominantly employed for machining of hard materials and also for making complex shaped components. In this present work, the machinability study on WEDM of Inconel 718 has been discussed with special attention on parametric optimization by Taguchi’s single response approach. The experimental runs are planned by Taguchi’s DoE approach. The experiments have been performed by considering the process variables such as pulse on time, pulse off time and peak current at three various levels. The ascendency of process variables are determined by ANOVA analysis. Taguchi - Grey methodology has been adopted for the WEDM process and combination of process variables are determined for accomplishing improved multi performance characteristics.

Estimation of optimal cutting conditions during machining of CP-Ti grade 2 in fuzzy–VIKOR context

PurposeTo explore a hybrid approach in order to attain optimal cutting conditions proficient of generating adequate dimensional accuracy in combination with virtuous surface finish during turning of commercially pure titanium (CP-Ti) grade 2.Design/methodology/approachIn the present paper, an application of the hybrid fuzzy–VIKOR method has been proposed to estimate an optimal combination of process variables during turning of commercially pure titanium (CP-Ti) grade 2. Three distinct input factors, namely, cutting speed, feed rate and depth of cut, were selected, each varied at three levels. Thus, a series of experiments were performed based on Taguchi's 3-factor-3-level (L27) orthogonal array. The major attention was given to acquire minimum cutting force and flank wear along with good surface finish. The adequacy of the proposed methodology was verified with the help of ANOVA test.FindingsThe results of the investigation revealed that the suggested hybrid technique is quite effective, easily understandable and time-saving approach, which can be successfully implemented to solve various problems either of similar or of different kinds.Originality/valueIncreasing demand of qualitative as well as low cost products is identified as the main challenging task in the current competitive market. Therefore, estimation and selection of the most suitable machining environment are of paramount importance in a real-time manufacturing system. Machining process involves both qualitative and quantitative factors, may be conflicting in nature, all to be considered together. Consequently, an appropriate combination of the machining variables is evidently desirable to meet the aforesaid challenges effectively.

Analysis of Surface Characteristics for Al–SiC Metal Matrix Composites Machined by Wire Electrical Discharge Machining (WEDM)

Objectives: The application of light weight products used for automobile needs to require the use of Al metal matrix composites (MMCs). The optimized combination of process variables has been found to accomplish for better machining. Methods/statistical analysis: There is different type of machining methods used for machining of MMC but it is not so easy to machine these materials with full efficiency and desired output responses because of difficult to machine these materials as compared to other unreinforced materials like alloys and smart materials. The main reason behind hardness of aluminum MMCs is heterogeneous structure which makes its surface layer with high fatigue strength, smooth, and tough. L9 orthogonal array has been used to perform the experiments. Findings: The effect of parameters has been calculated and analyzed for response analysis. The effect of various machining parameters like wire diameter, current, voltage, pulse on time, and pulse off time is observed and analyzed on surface properties of the Al–SiC MMCs. As a result of compressive residual stress on the surface that is a plus point for material to use it for tough work, but along with this it will cause high tool wear and surface imperfections while machining, so these are some reasons for the recommendation of non-conventional machining methods to machine aluminum matrix composites. So, several new techniques were added in some past few years of research which is explained in this research article. Application/improvements: Wire electrical discharge machining (WEDM) which is an advanced machining method which is used for manufacture difficult shapes conductive work piece materials. Experimental work will be done on the WEDM of Al–SiC MMC. Keywords: Aluminium Metal Matrix Composite Al–SiC, Surface Roughness, Wire Electrical Discharge Machining (WEDM), Surface Integrity, Taguchi’s Method, Response and Regression Analysis.

An investigation on the effect of different coated electrodes on the surface quality of WEDM by varying discharge energy level

The quality of WEDM surface is still a concern to the researcher. Due to the uneven spark, the energy discharge transferred to the workpiece surface is not accurate for high-quality machining. Such energy is mainly controlled by process variables and electrode parameters. The selection of proper wire electrode and the proper combination of process variables can extend the surface quality into a much higher limit. In the present investigation, machining quality of brass wire, silver-coated brass wire, and zinc-coated brass wire is compared at different discharge energy levels. The quality of machining is measured in terms of average roughness, maximum roughness, kerf width, recast layer thickness, workpiece surface, and elemental inclusions in both wire and workpiece surface. The surface morphologies of the wire have also been investigated. The research material has been carefully chosen as one of the expensive grades of steel named maraging steel 300 due to its wide applicability in the aerospace and automobile industries. From the investigation, it has found that a minor coating of silver over plain brass significantly improves the surface quality. It has also found that, for better quality machining, discharge energy should be kept in a lower limit. Zinc coating over brass improves the strength of the wire as well as machining rate but simultaneously is responsible for the poor quality of surface. Brass wire is neither a good choice for high surface quality machining nor good for high-speed machining. The majority of copper and some zinc elements have been flush out from wire and adhered to the workpiece surface.

Influence of aeration, agitation and process duration on fungal inulinase production from paneer whey in a stirred tank reactor

In present study, inulinase production was carried out from paneer whey using Penicillium oxalicum BGPUP-4 in a stirred tank bioreactor. In preliminary experimentation in shake-flask fermentations, maximum (38.58 IU/mL) inulinase production was obtained from clarified paneer whey. Therefore, it was selected for inulinase production at bioreactor level. Probabilistic tool was used to optimise process variables for inulinase production in bioreactor. At optimal combination of process variables (agitation 180 rpm, aeration 0.98 vvm and fermentation time 5 days), maximum inulinase production obtained in stirred tank reactor was 80.2 IU/mL. Approximately 2-fold increase in inulinase production was obtained in comparison to shake-flask fermentations. A statistical evaluation of designed model predicted it significant. The findings of the present study show paneer whey as cost-effective substrate for the production of inulinase by P. oxalicum BGPUP-4 in a stirred tank reactor. Literature survey reveals, this is first report on inulinase production from paneer whey based medium.

Application potential of combined fuzzy-TOPSIS approach in minimization of surface roughness, cutting force and tool wear during machining of CP-Ti grade II

Titanium and its alloys possess numerous inherent qualities such as high corrosion resistance, temperature resistance, bio-compatibility and high strength-to-weight ratio. These alloys are extensively used in widespread areas viz. spacecraft, aerospace, marine, medical, oil and gas, chemical processing industries, etc. around the globe. In spite of the aforesaid popularity, machining of titanium alloys is very costly and difficult due to their poor thermal conductivity and high chemical affinity. Low thermal conductivity causes rapid tool wear owing to excessive machining zone temperature. Tool failure at its pre-mature stage considerably curtails the surface quality of the end product. This situation necessitates an appropriate set of machining variables so that one can achieve high productivity without compromising the quality. Keeping these facts in mind, the present paper proposes fuzzy coupled with TOPSIS method to identify an optimal combination of process variables during turning of commercially pure titanium. Spindle speed, feed and depth of cut were selected as three input parameters, whereas surface roughness (Ra), cutting force (Fc) and flank wear (VBc) were the major responses. Experiments were performed according to Taguchi’s L27 orthogonal array. Analysis of variance (ANOVA) test was performed to identify the most significant machining parameter and to verify the potential application of the proposed methodology. The results indicated that the fuzzy-TOPSIS method is capable of deal with both qualitative and quantitative criteria to reach at the best parametric combination during turning operation.

Investigation for obtaining the optimal solution for improving the performance of WEDM of super alloy Udimet-L605 using particle swarm optimization

The purpose of the current study is to increase the productivity, accuracy and reduce the cost of wire electric discharge machining of super alloy Udimet-L605. The pulse-on time, pulse-off time, peak current, wire tension, spark gap voltage, and wire feed rate have been considered as input variables in the experimental work on the wire electric discharge machining. The experimental work is planned on the basis of Taguchi’s L27 orthogonal array and obtained the optimal combination of process variables for high cutting speed and lowest dimensional deviation and wire wear ratio, individually. The linear regression model is used to describe the interplay amid the input and output variables. After that, the PSO algorithm is applied to the developed model to obtain the global best solution for the desirable consequences of cutting speed, dimensional deviation and wire wear ratio. It has been observed that pulse-on time have a momentous effect on the cutting speed, dimensional deviation and wire wear ratio. The SEM and EDX are used to observe the erosion and compositional changes occurred during WEDM.

Optimising the Production Process of Rieter Air Jet Spun Yarns and a Model for Prediction of their Strength

In this study, the effect of yarn linear density, delivery speed and nozzle pressure on Rieter air jet spun yarn strength was investigated. A multiple regression model was used to study the combined effect of these parameters and response surfaces were obtained. Results showed that by increasing the nozzle pressure, the yarn tensile strength improves till a specific limit, then it deteriorates afterwards. Based on the different combinations of processing variables, optimal running conditions were obtained. Along with the experiment, a mathematical model that predicts air jet spun yarn strength at a short gauge length has been presented. Fibre parameters in addition to yarn structural parameters were used to obtain the theoretical yarn strength. The results showed a satisfactory agreement between the experimental and theoretical results.