Multi-performance Characteristics Optimization Research Articles

Multi-response optimization of TIG dissimilar welding of AISI 1008 mild steel and AISI 316 stainless steel using grey-based Taguchi method

This article presents a reliable method of multi-performance characteristics optimization of TIG dissimilar welding of mild steel and stainless steel. Grey-integrated Taguchi optimization approach was adopted for the optimization of the welding process parameters such as the welding current, the welding voltage and the gas flow rate for multi-performance characteristics such as the ultimate tensile strength, yield strength, percentage elongation and Vickers microhardness of the fusion zone. L9 Taguchi orthogonal array was employed with three process parameters all at three levels. The welding current was the most significant process parameter for the multi-performance characteristics of the weld joint. The optimal setting for the multi-performance characteristics of the weld joint was obtained as welding current at level 1 (110 A), welding voltage at level 1 (11 V) and gas flow rate at level 3 (18 l min−1). The corresponding response variables at the optimal setting were ultimate tensile strength, yield strength, percentage elongation and Vickers microhardness of 493.29 MPa, 395.38 MPa, 31.35% and 390.52 HV respectively. These values are all found to be higher than the values obtained at the initial settings. This shows that grey-integrated Taguchi optimization is an effective method in multi-performance characteristics optimization of dissimilar welded material.

Multi-performance characteristics optimization in near-dry rotary EDM of AlSiC by weighted principal component analysis

In the current study, electrical discharge machining of particle reinforced aluminium matrix composite (AlSiC) using near-dry conditions is investigated. The investigation has been carried out by using de-ionized water as liquid phase and air as gaseous phase of a two-phase dielectric fluid. The gap between the work material and the tool is supplied with a little amount of de-ionized water droplets at a slow, steady pace using a minimum quantity lubrication (MQL) device. The process parameters included in the study are peak current, duty cycle, pulse-on time, tool rotation and air pressure. MRR (Material removal rate), TWR (Tool wear rate) and HT (Hole Taper) were selected as evaluation criteria. L27 (313) orthogonal array was used to conduct the experiments. The experimental results obtained were used in principal component analysis (PCA). The MPI (multi-response performance index), which combines these principal components and weighted principal component analysis (WPCA), is calculated as overall performance index. The approach is capable of forecasting optimal levels of machining factors. Significant factors and their contribution is determined by ANOVA performed for MPI. To validate the optimum parametric settings confirmatory experiment was conducted. Experimental results show that the responses in near dry rotary EDM process can be successfully improved using the suggested method.

Grey-based taguchi method for multi-weld quality optimization of gas metal arc dissimilar joining of mild steel and 316 stainless steel

Welding processes play a significant role in many fabrication and manufacturing industries. Among various welding processes that have been developed over the years, Gas Metal Arc Welding (GMAW) or Metal Inert Gas Welding (MIG) has received a lot of interest due to its ability to weld a variety of metallic materials, easy adaptation for automation, high deposition rate, high efficiency, and low capital requirement. This study focus on the optimization of the multi-performance characteristics of MIG welded butt joint of AISI 1008 mild steel and AISI 316 austenitic stainless steel by hybrid Grey based Taguchi method. L9 Taguchi orthogonal array was adopted for the optimization of the MIG welding current, voltage and gas flow rate. The weld joint integrity has been assessed in terms of the tensile strength, yield strength, percentage elongation and Vickers microhardness of the fusion zone. Welding current of 180 A, voltage of 14 V, and gas flow rate of 19 l/min were obtained as the optimal parameter setting for the MIG welding process. The tensile strength, yield strength, percentage elongation and hardness of 559.25 MPa, 382.22 MPa, 33.34%, and 250.63 HV respectively were obtained at the optimal setting. Voltage was the most significant process parameter with 63.76% contribution for the multi-performance of the weldments. The confirmatory test was performed to validate the optimization process which proved Grey based Taguchi method to be an easy but yet effective method for multi-performance characteristics optimization of welded joints.

Dissimilar Laser Welding of NiTi Alloy with Ferrous and Non-ferrous Material: Optimization of Process Parameters

NiTi Shape Memory Alloy (SMA) is extensively utilized in various high-performance engineering industries such as medical devices, aerospace, air-craft structures, micro-electrical and electronic components, and more, owing to its exceptional properties, including shape memory effect (SME), superelasticity, and biocompatibility. Nonetheless, due to its distinct characteristics, achieving a suitable joint of NiTi alloys is a challenging task. Therefore, scientists have been dedicating significant efforts to the joining of this alloy. This current research explores the weldability of NiTi wires with stainless steel wire and copper wire using Laser. The micro-hardness and the tensile strength of the weld joint are acquired according to Taguchi design of experiment so as to identify the significance of the control factors (laser power, scan speed and focal length). Moreover, simultaneous optimization of multi performance characteristics is also attempted using Utility concept. The results from the confirmation runs showed that the predicted optimal machining parameters has im-proved the individual as well as the multiple performance characteristic.

Abrasive Jet Machining of Incense Stick Ash Filled Luffa-Human Hair Based Sustainable Bio-composite Using Taguchi Based GRA

ABSTRACT In this research, a new class of partially biodegradable epoxy-based sustainable bio-composite is developed in house by using blend of luffa cylindrica (LC) and short human hair (SHH) as fiber and diverse weight proportions (0, 5, 10,15 and 20 wt.%) of incense stick ash (ISA) as filler through the conventional hand lay-up method. The presently developed hybrid natural fiber composites are characterized for their density and porosity and subsequently, investigated for their machinability through abrasive jet machining (AJM) process. Two grits of silicone carbide (SiC, 300 µm and 600 µm) and combination of aluminum oxide (Al2O3) and glass powder (90 µm) are used as the abrasives. The material removal rate (MRR) and surface roughness (Ra) of the machined surface are acquired according to Taguchi design of experiment. The significance of the control factors (type of composite, gas pressure, standoff distance and type of abrasive) is identified through ANOVA and ideal factor setting for optimum individual responses are established. Moreover, simultaneous optimization of multi performance characteristics is also attempted through Grey Relational Analysis (GRA) method. The outcomes from the confirmation runs showed an improvement in the predicted optimal machining parameters for individual as well as the multiple performance characteristic in AJM of the newly developed ISA filled LC-SHH fiber polymer composite.

Multi performance characteristics optimization of end milling parameters on surface quality and Micro-hardness of SS-304

Taguchi and Grey Relational Analysis approaches are used in the present study for optimizing the end milling process parameters of stainless steel 304 (SS-304). The four key input machining parameters i.e., rate of feed presence/absence of coolant, speed is investigated experimentally. An orthogonal Taguchi L18 array was used to perform the trials, which consisted of 18 trials with two coolant levels, three levels for the remaining three parameters. Three performance features for improvement: surface roughness (SR), surface strain (SS), and microhardness (MH) are taken into consideration. Multi performance characteristics were improved using Taguchi with grey relational analysis (GRA), and the data was then analysed using mean response tables and variance analysis i.e., ANOVA. The optimal combination is obtained as A1B3C3D1 i.e., coolant on, feed rate 2500 mm/min, depth of cut 0.4 mm, and cutting speed 1500 rpm. Further, it is also observed that highest contributing parameter is speed with the percentage of 25.75. This approach detects several performances optimum improvements of 3.9615 percent through a confirmation test.

Optimization of Parameters of a Planetary Gearbox Using the Taguchi-Grey Relational Analysis

Optimization of parameters of central gears of a planetary gearbox was performed in this study. Since the optimization of multi-performance characteristics is more complex compared to optimization of a single-performance characteristics, the Taguchi-Grey analysis was used. That approach combines the Taguchi orthogonal array L27 with the Grey relational analysis to determine the influence of the material, module and gear width on the safety coefficient of the planetary gearbox. A Grey relational grade obtained from the Grey relational analysis is used as the performance characteristics in the Taguchi method and Analysis of variance (ANOVA). The optimal combination of parameters for the safety coefficient values was obtained, when the value of the Grey relational grade is 1. Based on the ANOVA analysis, it was established that the most influential parameter is the module, then the gear width and the least influential one is the material.

Multi performance characteristics optimization in cryogenic turning of 17-4 PH stainless steel using Taguchi coupled grey relational analysis

Cryogenic machining is one of the environmental friendly machining techniques offers high productivity in machining of difficult to cut materials. The present article investigates the multi response optimization in turning of 17-4 Precipitation Hardened Stainless Steel (PH SS) under the jetting of cryogenic coolant (liquid nitrogen) on the rake face of the cutting tool using Taguchi coupled grey relational analysis (TGRA). Cutting velocity, feed rate and depth of cut were considered as the controllable process parameters. Cutting force, surface roughness, tool flank wear and material removal rate (MRR) were considered as the performance characteristics. Experiments were performed based on Taguchi L9 orthogonal array. From the TGRA result, it was found that at cutting velocity of 120.89 m/min, feed rate at 0.048 mm/rev and depth of cut 0.4 mm obtained the improved turning process performance characteristics. Scanning electron microscope (SEM) has been used to obtain the tool flank wear and machined surface images at the optimum machining conditions. Further analysis of variance (ANOVA) has been carried out and it was identified that feed rate was most influencing process parameter contributing 53.76% on the multi performance characteristics.

Multi-response optimization of machining characteristics in ultrasonic machining of WC-Co composite through Taguchi method and grey-fuzzy logic

This article addresses the application of grey based fuzzy logic coupled with Taguchi’s approach for optimization of multi performance characteristics in ultrasonic machining of WC-Co composite material. The Taguchi’s L-36 array has been employed to conduct the experimentation and also to observe the influence of different process variables (power rating, cobalt content, tool geometry, thickness of work piece, tool material, abrasive grit size) on machining characteristics. Grey relational fuzzy grade has been computed by converting the multiple responses, i.e., material removal rate and tool wear rate obtained from Taguchi’s approach into a single performance characteristic using grey based fuzzy logic. In addition, analysis of variance (ANOVA) has also been attempted in a view to identify the significant parameters. Results revealed grit size and power rating as leading parameters for optimization of multi performance characteristics. From the microstructure analysis, the mode of material deformation has been observed and the critical parameters (i.e., work material properties, grit size, and power rating) for the deformation mode have been established.

Optimization Of Multi-Performance Characteristics in the Turning Of GFRP(E) Composites using Principle Component Analysis combined with Grey Relational Analysis

Glass Fiber Reinforced Polymers are a successful alternative, having numerous advantages over traditional reinforcement methods; giving complex structures a longer service life. With the upcoming applications of composites in various areas, machining of these materials has become a major concern for the manufacturing industries. The current knowledge and state of art of machining of GFRP composites, unfortunately, is seemed inadequate for its optimal economic utilization. This paper presents an optimization study made on machining of randomly oriented glass fiber reinforced (GFRP) polymer composite rods. The influence of machining parameters on surface roughness parameters such as Ra, Rp, Rq, Rv, Rsm; Force and Material removal rate in turning operation of the glass fiber reinforced composite was the followed during the study. Turning parameters such as tool nose radius, cutting speed, feed rate and depth of cut are optimized with consideration of multiple performance characteristics. 27 experimental runs based on L27 orthogonal arrays were performed to determine the best factor level condition.Carbide inserts of fine grade was used as a cutting insert for machining. PCA (Principle component analysis) in combination with Grey relational analysis was applied for the optimization of chosen responses, which gave the parametric combination of A2B2C3D1 i.e. Tool nose radius at Level 2(0.8mm), cutting speed at Level 2(160mm/min), Feed rate at level 3(0.25mm/rev) and depth of cut at level 1(.6mm)as an optimum combination. The confirmatory experiment at these settings gives maximum value of the OPI (Overall Performance Index), validating the results. Based on the mathematical analysis of the experimental results it was found that the responses depend mainly on the feed rate parameter.

Multi Performance Characteristics Optimization in Wire Electric Discharge Machining of Nitinol Superelastic Alloy

The optimization of wire electric discharge machining (Wire EDM) process parameters for simultaneous maximization of material removal rate and minimization of surface roughness during machining of Nitinol (Nickel-Titanium) superelastic alloy has been carried out. The process variables selected in this study are wire feed, pulse on time, pulse off time and spark gap set voltage. Multi performance characteristics optimization was performed using Taguchi’s utility and Quality loss function. Analysis of means and analysis of variance were performed on signal to noise ratio to determine the optimal parameters. The optimal results reveal that the pulse on time of 115µsec, wire feed of 6m/min and spark gap set voltage of 40V with pulse off time of 25µsec are beneficial for maximizing the material removal rate and minimizing the surface roughness. The results indicate that the wire feed is the most significant parameter that affects the surface roughness and material removal rate.

Modeling and Optimization of Multi-Performance Characteristics of Powder-Mixed EDM of Tungsten Carbide Alloy Using Intelligent Decision-Making Tools

The main aim of this work is to propose a hybrid framework, which makes use of intelligent decision-making tools, that are gray, fuzzy, and ANFIS, to optimize the multi-performance characteristics (MPCs) of powder-mixed electrical discharge machining (PM-EDM) of tungsten carbide (WC). To perform the experimentation, four input parameters: (i) pulse-on time, (ii) current, (iii) powder concentration, and (iv) powder grain size are considered to investigate the MPCs such as material removal rate, tool wear rate, surface roughness, and micro-hardness. The proposed framework uses response surface methodology (RSM) with gray, gray-fuzzy, and gray-ANFIS approaches to obtain optimal solution and also to handle the element of uncertainty or fuzziness associated with the uncertain, multi-input, and discrete data. This method helps to generate the values of gray relational grade (GRG), gray-fuzzy reasoning grade (GFRG), and gray adaptive neuro-fuzzy inference system grade (G-ANFISG) for all the 30 experiments. Analysis of variance (ANOVA) is performed on GRG, GFRG, and G-ANFISG to identify the major contributing input parameters which may affect the MPCs. Finally, the theoretical prediction is done to verify the improvement in the performance characteristics obtained through the proposed approaches. Both the experimental and statistical results clearly demonstrate the success of proposed framework for the optimization of PM-EDM of WC alloy.

Microstructure and mechanical properties of Gas tungsten arc welded High Strength Low Alloy (15CDV6) steel joints

15CDV6 is a high strength low alloy (HSLA) steel being extensively used in aerospace applications, particularly in manufacturing of solid rocket booster motor cases because of its excellent strength to weight ratio and good weldability. The present investigation was carried out by Gas Tungsten Arc Welding (GTAW) process using L9 orthogonal array. The welding trials were conducted with different welding parameters such as current, voltage, welding speed and gas flow rate. The dimensions of the plates used in this work are 150x300x3.7mm. The 8CD12 filler wire of diameter 2.6 mm was used by GTAW process with DCEN polarity. The weld coupons were heat treated for hardening at 975 °C followed by air quenching and tempering at 650 °C. Bead geometry (Reinforcement, bead width) and hardness were measured as performance characteristics. Technique for Order Preference by Similarity to Ideal Solution Method (TOPSIS) was used for the optimization of multi performance characteristics. ANOVA was used to predict the influence of welding parameters on the multi performance characteristics. The metallurgical characterization of optimized weld is discussed briefly.

Metallurgical Aspects and Optimisation of Yb: YAG Laser Welded NiTinol Shape Memory Alloy

This article presents a study on optimization of multi performance characteristics using grey relational analysis (GRA) in laser welding of NiTinol shape memory alloys. Bead on plate welding was done on NiTinol plates of 1 mm thickness using Ytterbium: Yttrium aluminium garnet (Yb: YAG) laser welding process. The experiment was carried out on the basis of Taguchi L9 Design with welding speed, Shielding gas blown distance, focal position and power as input parameters. Bead geometry (Depth of penetration, bead width) and microhardness were measured as performance characteristics. Analysis of variance (ANOVA) was utilized for calculating individual parameter percentage contribution on the multi performance characteristics. It was found that welding speed as the most influential parameter on the multi performance characteristics followed by shielding gas blown distance, power and focal position. The metallurgical aspects of the optimized weld are also discussed with help of microstructure.

Parameter Design And Analysis In Laser Welding Of NiTinol Shape Memory Alloy

This article presents a study on Ytterbium: Yttrium aluminium garnet (Yb: YAG) laser welding of NiTinol shape memory alloys. NiTinol belongs to a class of smart materials. In recent days, due to its unique properties namely shape memory effect, biocompatibility and superelasticity it is finding wide range of applications in the field of automotive, aerospace, fashion, and biomedical industries. Bead on plate welding was done on NiTinol sheets based on L9 taguchi design with welding speed, laser power, focal position and shielding gas blown angle as input parameters. Bead geometry (Bead width, depth of penetration), hardness were measured as performance characteristics. Technique for order of preference by ideal solution (TOPSIS) was employed for multi performance characteristics optimization and metallurgical aspects of the weld with highest relative closeness value are also discussed.

Multiple performance optimization of electrochemical drilling of Inconel 625 using Taguchi based Grey Relational Analysis

In this present investigation, a multi performance characteristics optimization based on Taguchi approach with Grey Relational Analysis (GRA) is proposed for Electrochemical Drilling process on Inconel 625 material which is used for marine, nuclear, aerospace applications, especially in corrosive environments. Experimental runs have been planned as per Taguchi’s principle with three input machining variables such as feed rate, flow rate of electrolyte and concentration of electrolyte. Besides the material removal rate and surface roughness, the geometric measures such as overcut, form and orientation tolerance are included as performance measures in this investigation. Outcomes of the analysis show that the feed rate is the predominant variable for the desired performance characteristics. On establishing the desired performance measures and multiple regression models are developed to be used as predictive tools. The confirmation test also conducted to validate the results attained by GRA approach and affirmed that there is considerable improvement with the help of proposed approach.

Optimization of Multi-Performance Characteristics for a Hybrid Process of EDM and AJM Using Grey Relational Analysis

The aim of this study is to optimize the process variables of a novel hybrid process of electrical discharge machining (EDM) and abrasive jet machining (AJM) using grey relational analysis. The multi-performance characteristics associated with the developed hybrid process such as the material removal rate (MRR), electrode wear rate (EWR), and surface roughness (SR) were explored through an experimental study according to an L18 orthogonal array based on the Taguchi experimental design method. The experimental results confirmed the multi-performance characteristics of the developed hybrid process would clearly be improved through optimizing the process variables using grey relational analysis.

Simultaneous Optimization of Multi Performance Characteristics in Dry Turning of Inconel 718 Using NSGA-II

The conventional methods of optimization are unable to handle non differentiable or discontinues functions. Evolutionary Algorithms (EA) are efficient in handling non differential or discontinues functions. Non Dominated Sorting Genetic Algorithm-II (NSGA-II) is an efficient method for solving Multi-Objective optimization problems. Super alloy Inconel 718 is a high temperature alloy capable of having high creep rupture strength at high temperatures to about 650°C to 750°C. It is a difficult to cut material and is widely used in manufacturing of aircraft parts such as turbine disks, turbine blades, etc. A Multi Objective Optimization technique, NSGA-II has been used to predict the optimum values of process variables (Cutting speed, Depth of cut and Feed-rate) in high speed dry turning of Inconel 718 with PVD coated carbide tool by considering Material Removal Rate and Surface Roughness as Multi performance characteristics. According to NSGA-II's Pareto Optimal solutions, the best MRR obtained was 7462.42 mm3/min and the best surface roughness was found to be 0.375μm.

Optimization of Multi-performance Characteristics During Drilling of GFRP (Epoxy) Composites by Harmony Search Algorithm

In this article, drilling experiments were performed on GFRP composite plates using CNC drilling machine. The drilling parameters mainly drill speed, feed rate and drill diameter were chosen to analyze their effects on thrust force, torque and surface roughness. Drilling experiments on GFRP have been carried out using L16 orthogonal array based on Taguchi's philosophy with four levels for each process parameters. In order to simultaneous optimization of aforesaid performance characteristics, fuzzy inference system (FIS) has been applied. FIS converts the multi responses into single objective response i.e. MPCI. The study implemented nonlinear regression analysis to derive a mathematical relationship for MPCI in terms of process parameters. Relative average error has been computed to check the efficiency of this predicted model. This mathematical model is treated as objective function in harmony search algorithm to obtain the favorable machining condition.

Application of NSGA II for Optimization of Multi-performance Characteristics During Machining of GFRP (epoxy) Composites

Present research explores NSGA II for the selection of optimal process parameters during machining (turning) of GFRP (epoxy) composites. Experiments have been conducted on GFRP composites under different conditions of process parameters. L9 OA based on Taguchi's philosophy has been adopted for experimentation to assess the effect of spindle speed, feed rate and depth of cut on the machining performance characteristics such as surface roughness and tool tip temperature. A non-linear regression analysis has been carried out to establish relationship for aforementioned machining responses as a function of process variables. In order to achieve multi-response optimization, NSGA has been adopted. The set of optimal non-dominated solutions have been evaluated using NSGA II which gives the manufacturer more flexibility in decision making in machining process.