Multi-response Optimization Research Articles

Multi-response optimization of machining parameters of Ti-6Al-2Sn-4Zr-2Mo alloy using EDM process through grey relational analysis

Due to its high corrosion resistance and low density, it is tedious to machine high strength materials such as titanium alloy for the manufacture of engineering products related to aerospace, automobiles, and medical applications. In this study, an attempt was made to consider the impact of tool electrodes in the electrical discharge machining method for successful machinability of titanium alloy. High temperatures are used during electrical discharge machining to melt and vaporise the hard titanium alloy. In the current work, an EDM machining method was used to machine a Ti-6Al-2Sn-4Zr-2Mo alloy while using the input parameters of pulse on time, voltage, and current as process parameters. The experiments were carried out based on the workpiece, and surface morphology was performed on the workpiece surface. The process parameters were optimised using the Multi-Response Grey Relation Analysis method, and a major effects plot was created to see how the factors affected the MRR and surface roughness. Surface finish and MRR have been discovered to be directly correlated with discharge current. These are the best process parameters for machining pulse on time (150 s), voltage (60 V), and discharge current (16 A).

A hybrid approach consisting of multi-objective and multivariate analyses for WAAM specimens

In this study, a combination of multivariate and multi-objective analyses, namely principal component analysis with fuzzy logic, has been proposed to identify the input parameters for ER4043, aluminum alloy in wire arc additive manufacturing. Taguchi L9 orthogonal array was designed with three-factor, three-level input parameters. Mechanical properties such as tensile strength and hardness were used as the output parameters. As the Taguchi optimization is not sufficient for multi-response optimization, observed data for each response were normalized and then principal component analysis was applied. Further, multi-response performance index (MRPI) was identified using fuzzy logic approach so that this hybrid approach could be successfully applied and MRPI could give a combination of input parameters at an optimal level.

Multi response optimization of friction stir welding in air and water by analytic hierachy process and VIKOR method

Multi response optimization of friction stir welding in air and water by analytic hierachy process and VIKOR method

Multi-response optimization in WEDM process of Al–Si alloy using TLBO-graph theory algorithm towards sustainability

Multi-response optimization in WEDM process of Al–Si alloy using TLBO-graph theory algorithm towards sustainability

Multi-response optimization for a low-cost multi-dimpling process

PurposeThis study aims to identify the significant factors of the multi-dimpling process, determine the most influential parameters of multi-dimpling to increase the dimple sheet strength and make a low-cost model of the multi-dimpling for sheet metal industries. To create an empirical expression linking process performance to different input factors, the percentage contribution of these elements is also calculated.Design/methodology/approachTaguchi grey relational analysis is used to apply a new effective strategy to experimental data in order to optimize the dimpling process parameters while taking into account several performance factors and low-cost model. In addition, a statistical method called ANOVA is used to ensure that the results are adequate. The optimal process parameters that generate improved mechanical properties are determined via grey relational analysis (GRA). Every level of the process variables, a response table and a grey relational grade (GRG) has been established.FindingsThe factors created for experiment number 2 with 0.5 mm as the sheet thickness, 2 mm dimple diameter, 0.5 mm dimple depth, 8 mm dimples spacing and the material of SS 304 were allotted rank one, which belonged to the optimal parameter values giving the greatest value of GRG.Practical implicationsThe study demonstrates that the process parameters of any dimple sheet manufacturing industry can be optimized, and the effect of process parameters can be identified.Originality/valueThe proposed low-cost model is relatively economical and readily implementable to small- and large-scale industries using newly developed multi-dimpling multi-punch and die.

Deep Learning Based Multiresponse Optimization Methodology for Dual-Axis MEMS Accelerometer

This paper presents a deep neural network (DNN) based design optimization methodology for dual-axis microelectromechanical systems (MEMS) capacitive accelerometer. The proposed methodology considers the geometric design parameters and operating conditions of the MEMS accelerometer as input parameters and allows to analyze the effect of the individual design parameters on the output responses of the sensor using a single model. Moreover, a DNN-based model allows to simultaneously optimize the multiple output responses of the MEMS accelerometers in an efficient manner. The efficiency of the proposed DNN-based optimization model is compared with the design of the computer experiments (DACE) based multiresponse optimization methodology presented in the Literature, which showed a better performance in terms of two output performance metrics, i.e., mean absolute error (MAE) and root mean squared error (RMSE).

Multiresponse optimization of performance indicators through Taguchi-grey relational analysis in EDM of cemented carbide

Cemented carbide is mostly used in the mold and tool industry due to their high hardness, temperature and wear resistance, and it is very difficult to shape with conventional machining methods. Because, during the machining of certain geometry from these materials, microcracks on surface and flaking at the machined edges due to their brittleness as well as rapid tool wear mostly due to their high hardness occur. In this case, EDM is considered one of the most suitable machining technologies for brittle material such as carbides, as it provides a non-contact shaping with electrical sparks between the tool and the workpiece. This study focused on the simultaneous optimization of the most important performance indicators namely material removal rate, tool wear rate and surface roughness in creating a keyway on WC-15Co material with the die-sinking EDM. As a result of experiments using copper electrode, the impacts on performance indicators of discharge current, pulse time and pulse interval were investigated with 3D surface topography images. It was determined that the peaks and craters formed on the machined surface expanded with the increase of pulse time, and the decreased with the increase in the pulse interval. As a result of the Taguchi-grey relational analysis (TGRA) application, discharge current of 6 A, pulse time of 25 µs and pulse interval of 100 µs were found as optimum parameters. ANOVA results showed that Ip, Ton and Toff affected GRG values by 44.23%, 28.77% and 5.87%, respectively. A 23.95% improvement in performance indicators was achieved thanks to the TGRA multiresponse optimization.

Pulsed laser micro drilling act on Perspex intended for microfluidic devices

An amorphous material with excellent shape memory effect (SME) like Perspex is a versatile material with broad applications in the bio-related field. Moreover, its extravagant properties like biological behavior, antimicrobial capacity, and porosity make it a choice for ophthalmologic devices, drug delivery, and microfluidic-based chromatography. However, its brittleness property and the formation of brittle-ductile transition make it a complex and delicate material for machining processes. A laser beam is an idiosyncratic tool used in engineering to biomedical fields. Compared to other lasers, the CO2 laser has a longer wavelength of 10.6 µm, which makes it the best choice for processing transparent material like Perspex. In this research CO2 laser micro-drilling (CLMD) act has been performed to design micro-holes on Perspex by tailoring the scan tracks of the laser. The movement of scanning tracks was controlled, and the beam functionalities' process windows were handled through adequate parametric settings like scan mode, machining speed, power, and pulsed frequency. The selection of optimal control factors is crucial for the adequate dimensional characteristics of holes, such as circularity and conicity. In continuation, multi-response optimization using RSM was employed to acquire the desired values of CLMD responses. Thus, the current CLMD approach may emanate its proprietary in fabricating micro-holes designed for a microfluidic device as an integrated inlet–outlet connector for fluidic manipulation. The findings of this research may be a worthy contribution to the biomedical field, as the designed holes by the current process on Perspex have not yet been addressed in any articles.

RSM design-based hybrid approach to multi-response optimization in milling Ti-6Al-4 V alloy: A comparative study

The Selection of appropriate process parameters in milling Ti-6Al-4 V alloy to reduce energy and power consumption while maintaining product quality and process stability is challenging. This study aims to optimize process parameters in milling Ti-6Al-4 V alloy with five primary criteria i.e., average cutting force, shear stress, specific cutting energy, power consumption, and average surface roughness. A total of 26 experimental tests was carried out with the variation of process parameters such as cutting speed (m/min), feed rate (mm/min), and depth of cut (mm) based on the Box-Behnken design (BBD) matrix of response surface method (RSM) under dry and high-pressure cooling (HPC). The criteria importance through the inter-criteria correlation (CRITIC) method was used to determine the relative weights of each response. At the same time, the evaluation of optimum process parameters was done by hybrid multi-response optimization (MRO) techniques such as complex proportional assessment (CRITIC-COPRAS), additive ratio assessment (CRITIC-ARAS), combined compromise solution (CRITIC-COCOSO) and technique for order of preference by similarity to ideal solutions (CRITIC-TOPSIS). After the evaluation, a cutting speed of 32 m/min, feed rate of 22 mm/min, and 0.75 mm depth of cut with HPC were selected as the optimum process parameters. Due to the lack of an identical solution, the sensitivity of the used MRO methods was checked out with the weight variation of the selected criteria. TOPSIS was noticed as the most robust MRO method with less sensitivity. Spearman’s Correlation coefficient was used to assess the correlation among the used hybrid MRO methods.

Multi-response and multi-criteria optimization of acid hydrolyzate detoxification of cocoa pod husks: Effect on the content of phenolic compounds and fermentable sugars

Dilute acid hydrolysis is the most common and effective method for converting lignocellulosic substrates into fermentable sugars. However, this hydrolysis partially degrades the lignin into phenolic compounds (PC), inhibiting the fermentation medium by retaining it in the hydrolyzate. Response surface methodology is a modeling and optimization technique used to examine the effect of multiple factors on a given response. In this study, shows the removal of PC from cocoa pod husks hydrolyzate, while preserving a considerable level of reducing sugar (RS). An Alkalinization from pH 11 with NaOH, then readjustment of pH to 6 with H2SO4 were first carried out, while eliminating 89.39% of PC and 13.41% of sugars. Then, an optimization of the activated carbon detoxification of the hydrolyzate was carried out by considering the contact time factors (X1), carbon to hydrolyzate ratio (X2) and the agitation speed (X3) in a Box-Behnken plan. The optimal conditions were 60 min of contact, a carbon to hydrolyzate ratio of 1.984% (w/v), and a stirring speed of 180 revolutions per minute (rpm). 0.153 mg/mL of PC and 6.585 mg/mL of RS remained in the hydrolyzate, corresponding to 95.18% of PC and 28.88% of RS lost.

Optimization of dimensional accuracy and surface roughness in m-SLA using response surface methodology

PurposeThis paper aims to investigate the dimensional accuracy and surface roughness of printed masked stereolithography (m-SLA) parts. The fabricated specimens of photosensitive polymer resin have complex shapes and various features. The influence of four process parameters of m-SLA, including layer height, exposure time, light-off delay and print orientation, is studied on response characteristics.Design/methodology/approachThe Box–Behnken design of response surface methodology is used to examine the effect of process parameters on the shrinkage of various geometrical dimensions like diameter, length, width, and height of different features in a complex shape. Additionally, a multi-response optimization has been carried out using the desirability function to minimize the surface roughness and printing time and maximize the dimensional accuracy.FindingsThe layer height and print orientation influence the surface roughness of parts. An increase in layer height results in increased surface roughness, and the orientation parallel to the z-axis of the machine gives the highest surface roughness. The dimensional accuracy of m-SLA parts is influenced by layer height, exposure time, and print orientation. Although not significant in dimensional accuracy and surface roughness, the light-off delay can affect printing time apart from other parameters like layer height and print orientation.Originality/valueThe effect of layer height and print orientation on dimensional accuracy, printing time, and surface roughness is investigated by researchers using simple shapes in other vat photopolymerization techniques. The present work is focused on studying the effect of these parameters and additional parameters like light-off delay in complicated geometrical parts in m-SLA.

Multi-response optimization on abrasive water jet machining of Aluminum 7075 alloy using Taguchi–DEAR methodology

This research aims to conduct the multi-response optimization for abrasive water jet machining (AWJM) of Aluminum 7075 metal matrix composites. The experiments were conducted with three levels of AWJM factors such as pressure, standoff distance, and traverse speed. The experiments were designed using Taguchi's L9 orthogonal array. The influence of AWJM parameters was assessed by measuring the outcomes like material removal rate, surface roughness, and taper angle. The single response optimization was obtained through Taguchi's signal-to-noise ratio analysis, and multi-response optimization was achieved with Taguchi–data envelopment analysis-based ranking (DEAR). From DEAR, the optimal AWJM parameter 180 MPa of pressure, 3 mm of standoff distance, and 40 mm/min traverse speed was found. After optimization, the surface roughness and taper angle were reduced by 5.44% and 10.92%, respectively. The influence of cutting parameters on the outcomes was examined through the analysis of variance. It was noted that traverse speed had a significant effect and a contribution of 47.79%. After AWJM, the surface was evaluated using SEM analysis, ploughing marks, ductile rupture, and a small crack were observed.

Electrical discharge machining assessment of AA7075/Rice Husk Ash composite using response surface methodology

This study aims to explore electrical discharge machining of green AA7075 composite supplemented with rice husk ash (an agricultural waste) using response surface methodology. Central composite rotatable design for three factors – current, pulse duration and gap voltage – was used for carrying out machining experiments. The effect of these input parameters was evaluated on performance parameters including material removal rate, tool wear rate and surface roughness. Regression models are developed for each response, and model adequacy was checked using the analysis of variance technique. Furthermore, Pareto charts for the standardized effects, normal probability distribution plots, residuals vs fits plots, residual vs order plots, main effect plots and contour plots were also developed for output parameters. Peak current was found to be the major process parameter affecting every response variable. The influence of other linear, squared and interaction effects that are found to be significant for each response are discussed. Multi-response optimization for different process parameters using the composite desirability approach is also highlighted. Confirmatory experiments at optimum process parameters are carried out to analyze variations in predicted values and experimental values. Electrical discharge machined sample was characterized through scanning electron microscopy to study its surface after successive spark discharges.

Multi-response optimisation and performance evaluation of Inconel 625 superalloy machining under cryogenic cooling environment

ABSTRACT The conventional machining of the widely used nickel-based superalloy Inconel 625 is challenging since it exhibits high strength at elevated temperatures. Cryogenic machining is an effective cooling technique to extract the heat developed during machining and enhance the machining performance of superalloys by eliminating the high-temperature related machining obstacles. The maximum machining performance of cryogenic machining can be achieved by optimising the input parameters considered for the study. This work attempts to improve the cryogenic machining performance of Inconel 625 using grey relational analysis. Multiple responses that are having the most significance on the performance of the machining such as main cutting force, tool wear and surface roughness were considered to optimise the process. The experiments were designed on the basis of the orthogonal array. Taguchi’s L9 design with three levels of cutting speed, feed and depth of cut was considered for conducting the experiments. A cutting speed of 60 m/min, feed of 0.05 mm/rev and depth of cut of 0.2 mm were obtained as the optimal parameters. The analysis of modes of wear and morphology of chips was also conducted using SEM imaging to understand the wear mechanisms and machining performance at the optimal level under cryogenic cooling.

Multi-response optimization and machinability research of forging and heat treatment parameters in piston production

Multi-response optimization and machinability research of forging and heat treatment parameters in piston production

Integrated fuzzy AHP and fuzzy TOPSIS for multi response optimization in incremental forming process

Integrated fuzzy AHP and fuzzy TOPSIS for multi response optimization in incremental forming process

Multi-response optimization of process parameters during friction stir welding of AA2014-AA7075 using TOPSIS Approach

In this study, multi-objective optimization for Friction stir welding of dissimilar AA2014-AA7075 has been presented to provide optimum tensile strength, hardness, and % of elongation. The input parameters considered for the analysis are tool rotational speed, feed, and tilt angle. Experiments are designed based on Taguchi L9 orthogonal array. Investigative analysis on the effect of input parameters on the responses is carried out using the MINITAB14 software package. The parametric influence on responses is discussed through the main effects plot. Further, multi-objective optimization is performed with the Technique for order of preference by similarity to ideal solution (TOPSIS). Results demonstrated that tool rotational speed is the most significant factor affecting the response followed by feed and tilt angle. The optimum cutting parameters obtained are tool rotational speed 710 rpm, Feed 30 mm/rev, and Tilt angle 2o.

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.

Multiresponse Optimization of Selective Laser Melting Parameters for the Ni-Cr-Al-Ti-Based Superalloy Using Gray Relational Analysis

The selective laser melting technology is of great interest in the aerospace industry since it allows the implementation of more complex part geometries compared to the traditional technologies. This paper presents the results of studies to determine the optimal technological parameters for scanning a Ni-Cr-Al-Ti-based superalloy. However, due to a large number of factors affecting the quality of the parts obtained by selective laser melting technology, the optimization of the technological parameters of the scanning is a difficult task. In this work, the authors made an attempt to optimize the technological scanning parameters which will simultaneously correspond to the maximum values of the mechanical properties ("More is better") and the minimum values of the dimensions of the microstructure defect ("Less is better"). Gray relational analysis was used to find the optimal technological parameters for scanning. Then, the resulting solutions were compared. As a result of the optimization of the technological parameters of the scanning by the gray relational analysis method, it was found that the maximum values of the mechanical properties were achieved simultaneously with the minimum values of the dimensions of a microstructure defect, at a laser power of 250 W and a scanning speed of 1200 mm/s. The authors present the results of the short-term mechanical tests for the uniaxial tension of the cylindrical samples at room temperature.

Comparative study of nano fluid lubricant in face milling through DFA approach

Material research in industry is a prominent part of their investigation as the customer’s demand kept changing according to their requirement. To process a hard material is always a stimulating charge for the industry. One of such hard material EN31 has been kept under consideration here in this work. The idea in the standing work is to improvise the deduction rate of material and to observe the power consumption rate. These two responses have been focussed under controlled machining environment with or without Nano fluid particles. Thus a comparative analysis provided the significance by exploiting the Nano particles in lubricant along with least amount of lubrication. As there are two output responses, a multi response optimization technique has to be adopted. Hence the multi response system desirability functional analysis (DFA) has been practiced. Depth of cut (DC) analysed as the best affecting input for both environment situations. The experimental array was created using the Taguchi approach. A total of eighteen number of try-outs were executed and on comparing it has been found that no big difference seen in material removal rate (MR) whereas power consumption (PC)gets lower on using Nano fluid particles in minimum quantity lubrication (MQL). For instance, in seventeenth experiment, PC reduced from 965 to 740 W and MR only increases from 420 to 435 mm3/min.