Multi‐Objective Optimization of a Continuous Amaranth Grain Puffing Process Using Taguchi– GRA Approach

Through a pin-on-disc type wear setup, the dry sliding wear behavior of SiC-reinforced aluminum composites produced using the molten metal mixing method was investigated in this paper. Dry sliding wear tests were carried on SiC-reinforced metal matrix composites (MMCs) and its matrix alloy sliding against a steel counter face. Different contact stresses, reinforcement percentages, sliding distances, and sliding velocities were selected as the control variables, and the responses were selected as the wear volume loss (WVL) and coefficient of friction (COF) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Initially, the optimization of the dry sliding performance of the SiC-reinforced MMCs was performed using grey relational analysis (GRA). Based on the GRA, the optimum level parameters for overall grey relational grade in terms of WVL and COF were identified. Analysis of variance was performed to determine the effect of individual factors on the overall grey relational grade. The results indicated that the sliding velocity was the most effective factor among the control parameters on dry sliding wear, followed by the reinforcement percentage, sliding distance, and contact stress. Finally, the wear surface morphology and wear mechanism of the composites were investigated through scanning electron microscopy.

Purpose Polycarbonate bullet proof (UL-752) glass is highly demanded material in automobile, aerospace and space industries. It is also used in security chambers or buildings, because of its unique properties such as; impact bare capacity, hardness, excellent transparency, higher mechanical strength, good dimensional stability etc. Objective of this research investigation is focused at studying the impact of different input parameters (concentration, abrasive, power rating, grit size, HF acid concentration and tool material) on output responses (material removal rate, tool wear rate and surface roughness) in ultrasonic drilling of polycarbonate bullet proof (UL-752) glass. Design/methodology/approach The experiments have been performed by using Taguchi’s L27 orthogonal array and grey relation analysis has been used for the optimization of multiple responses. To find out the significant factors, analysis of variance is further employed. Abbreviation CUSM: Chemical assisted ultrasonic machining; PBPG: Polycarbonate bullet proof glassHF: Hydrofluoric; MRR: Material removal rate; TWR: Tool wear rate; SR: Surface roughness; DOE: Design of experiment; DOF: Degree of freedom; OA: Orthogonal array; GRA: Grey relation analysis; GRC: Grey relation coefficient; GRG: Grey relation grade; S/N: Signal to noise ratio; ANOVA: Analysis of variance; RSM: Response surface analysis; SEM: Scanning electron microscope

Marble dust and basalt powder are industrial waste generated during the machining of marble stone and basalt rock. This paper presents an approach for the optimization of dry sliding wear parameters of aluminium 7075 reinforced with marble dust and basalt powder hybrid metal matrix composite using Taguchi based grey relational analysis. In this work, the composite is fabricated by stir casting technique and the wear parameters namely load, sliding velocity and sliding distance are optimized with consideration of multi responses such as wear rate and coefficient of friction. Experiments are conducted as per Taguchi's L9 orthogonal array. A grey relational analysis is carried out and grey relational grade is obtained. Based on the grey relational grade, optimum level of wear parameters has been identified by analysis of variance. The test results are validated by conducting the confirmation test. Experimental results have shown that the sliding velocity is the most effective factor among the control parameters on dry sliding wear, followed by the sliding distance and load. Finally, the micro structural investigations on the worn surfaces are performed by scanning electron microscope.

Fused deposition modeling is a most accepted method of additive manufacturing to fabricate complex and customized parts in layer by layer deposition of a material. Several factors affect the mechanical properties, appearance of parts and printing time of parts. Optimization of process parameters of fused deposition modeling (FDM) process is required to improve quality, cost effectiveness, and efficiency of the method to build parts. However, research on optimization of process parameters to improve quality of printed part using PC- ABS with 0.25 % graphene is limited. The main objective of this study is to identify the effect of various process parameters on dimensional accuracy, printing time, and material consumed. This study also determines the optimal setting to achieve better dimensional accuracy with less material consumption in minimum time. Taguchi’s “L27 orthogonal array” was implemented as design of experiment to collect the data. Grey Analysis was used to find the optimal setting to achieve desired outputs. Analysis of Variance (ANOVA) shows that layer thickness is most influential factor for all performance parameters. Grey relational analysis (GRA) is utilized to found optimal setting for all performance parameters as 0.2 mm layer thickness, 40 % infill density, line infill style, 240 oC printing temperature, and 80 mm/sec printing speed.

The multi response optimisation of process parameters like surface roughness (SR) and metal removal rate (MRR) of electrical discharge machining (EDM) of carbon nano tube (CNT) mixed dielectric fluid using grey relational analysis are performed. Experiments are performed with designated EDM conditions obtained using an L9 orthogonal array. Based on the results of the grey relational analysis a set of optimum EDM parameters is obtained. The analysis of variance (ANOVA) approach is used to find the significant parameters influencing the EDM machining process. The results show that the optimum machining conditions determined using grey relational analysis are much better than the original preliminary set of experimental conditions. Atomic force microscope (AFM) is used to analysis the surface characteristics such as surface roughness, micro cracks and topography of CNT-based machining surface. The paper describes the application of a fuzzy logic system to investigate precision and accuracy of EDM process parameters for determining the efficiency of each parameter influencing the machining for with and without using CNT mixed dielectric fluid.

Thin plates with arbitrary shapes and stiffeners find wide usage in construction, aerospace, marine, etc. industries. In the present work a parametric investigation of thin structural steel plates has been carried out. The design parameters considered were the subtended angle and aspect ratio of plates to account for the different shapes of plates used for various applications. Another design parameter that was considered is the stiffener and its different orientation. The impact of varying parameters on the first five modal frequencies and in turn the stiffness was considered as the response. Finite element method (FEM) coupled with Taguchi’s L16 orthogonal array and grey relational analysis was used to maximize the first five natural frequencies simultaneously. The thin plate was subjected to modal analysis when all its sides are in simply supported boundary condition. The optimum combination of design variables predicted by grey relational analysis is a thin plate with 80° subtended angle, 1.75:1 aspect ratio and crossed stiffener orientation for simultaneous maximization of the frequencies. Analysis of variance revealed highest contribution of stiffener type which affects the first 5 natural frequencies simultaneously.

In this paper we developed new grey relational analysis by expanding a range of treatable value. The classical GRA procedure deals with almost whitened values, reference vectors (or sequences), inspected vectors and grey relational grades. The classical GRA is called White-In-White-Out (WIWO) GRA in this paper. We developed two kinds of GRA algorithm based on the topological-based GRA, after defined several new operations of the interval grey number. On the one hand, GRA which provides the grey relational grade a whitened value finally is named Grey-In-White-Out (GIWO) GRA. On the other hand, GRA which provides the grey relational grade the interval grey number is named Grey-In-Grey-Out (GIGO) GRA. Both new GRA procedures deal with the reference vector and inspected vectors as the interval grey number. Three examples are given in this paper; the properties of the grey relational grade given by the proposals are discussed.

Abrasive powder-mixed electrical discharge machining (APM-EDM), a hybrid manufacturing process involving the use of a dielectric fluid mixed with abrasive powder, combines the benefits of mechanical and thermal interactions. The aim of this article is to use a new approach of performance evaluation, gray relational analysis (GRA), to evaluate the effectiveness of optimizing multiple performance characteristics of APM-EDM of 6061Al/Al2O3p/20p aluminum matrix composites (AMCs). The considered process parameter includes the seven control factors namely pulse current (A), pulse ON time (μs), duty cycle (%), gap voltage (V), time interval of tool lift (s), abrasive powder concentration (g/L), abrasive particle size (μm), and a noise factor, aspect ratio (shape of tool electrode). The combination of L18 (21 × 37) orthogonal array design of experiment with GRA enables to determine the optimal parameters for multiple responses. GRA is used to obtain a single performance index, gray relational grade through gray relational coefficient to optimize the APM-EDM process with lower tool wear rate, surface roughness, and higher material removal rate. In addition, analysis of variance (ANOVA) for the GRC is also utilized.

A stock portfolio selection system based on a Grey Relational Analysis (GRA) model, a Fuzzy C-Means (FCM) clustering scheme and Rough Set (RS) theory is proposed. In the proposed approach, 53 financial indices are collected automatically for each stock item every quarter and a GRA model is used to consolidate these indices into six predetermined financial ratios (Grey Relational Grades (GRGs)). The GRGs of the stock items are then clustered using a FCM scheme and the resulting cluster indices are processed using RS theory to identify the lower approximate set within the stock system. The stock items within the lower approximate set are filtered in accordance with established investment principles and the six GRGs of each surviving stock item are then consolidated to a single GRG indicating the overall merit of the corresponding stock item in terms of its ability to maximize the rate of return on the investment portfolio. The validity of the proposed approach is demonstrated using electronic stock data extracted from the financial database maintained by the Taiwan Economic Journal (TEJ). It is shown that the rate of return on the investment portfolio selected using the proposed GRA/FCM/RS system is higher than the average rate of return predicted by the variation in the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) over the same period. Thus, the feasibility of the GRA-based attribute reduction mechanism and the overall viability of the proposed portfolio selection system are confirmed. Introduction

This study presents the optimization of nickel oxide nanoparticles (NiO NPs) synthesized through an environmentally benign route using Sida acuta (SA) leaf extract as a reducing and capping agent. Taguchi-Grey Relational Analysis (TGRA) was employed to optimize the hydrodynamic diameter (HDD) and polydispersity index (PDI) of the synthesized NiO NPs. Key synthesis parameters (extract concentration, reaction temperature, and reaction time) were varied within an L9 orthogonal array. Using Grey Relational Analysis (GRA), a regression-based model was developed to predict the grey relational grade (GRG) for multi-response optimization. The optimal synthesis conditions (60mg/mL extract concentration, 70°C reaction temperature, and 120min reaction time) produced NiO NPs with an HDD of 62.72nm and a PDI of 0.232. ANOVA identified temperature as the dominant factor governing the size and distribution of the NPs. UV-Vis spectroscopy showed a characteristic absorption peak at 284nm, and XRD confirmed a face-centered cubic crystalline structure with an average crystallite size of 5.99nm. SEM, EDS, and TEM analyses indicated well-dispersed polycrystalline NPs with 80% purity. The synthesized NiO NPs possess physicochemical characteristics that position them as promising candidates for catalytic, sensing, and energy-storage applications. This work demonstrates a statistical-experimental framework for tuning nanoparticle properties through sustainable synthesis routes, highlighting a scalable strategy for precision nanomaterial design.

The use of high dielectric permittivity in vertical double gate MOSFET (VDG-MOSFET) can overcome the problem of power dissipation and leakage current. In this paper, we investigated the performance potential of Titanium dioxide (TiO2) which has been deposited on silicon for use as a high-permittivity gate insulator and tungsten silicide (WSi2) for use as metal gate based on 2-D numerical simulations. The analysis and optimization of n-channel VDG-MOSFET is conducted, using a combination of L9 orthogonal array (OA) of Taguchi method and grey relational analysis (GRA). Four process parameters which are VTH implant energy, halo implant dose, source/drain (S/D) implant dose and S/D implant tilt angle are optimized to obtain the desired value of on-current (ION), off-current (IOFF) and subthreshold slope (SS). The design of experiment (DoE) is based on the L9 OA of Taguchi method and then the experimental data for multiple responses are converted into a single unit called grey relational grade (GRG). The most optimal level of four process parameters towards multiple responses are selected based on the highest GRG. Based on the analysis of variance (ANOVA), the most significant factor is observed to be S/D implant dose with 35.6% factor effect on GRG. The optimized value for ION, IOFF and SS after the optimization approach are 1599.3 µA/µm, 865.5 pA/µm and 68.02 mV/dec respectively with 0.8362 of GRG.

Study of the feasibility of mixing Refuse Derived Fuels with wood pellets through the grey and Fuzzy theory

An expert system for automatically selecting stock portfolio is presented. The expert system involved Grey Relational Analysis (GRA) model, the VPRS-index clustering / classification method, and Variable Precision Rough Set (VPRS) theory. The GRA model is applied to consolidate the 53 financial indices into six financial ratios (Grey Relational Grades (GRGs)) for each stock item. The VPRS-index method is used to determine the optimal number of clusters per GRG. VPRS theory is then applied to identify the stocks within the -lower approximate sets. Finally, the GRGs of each candidate stock item are consolidated to a single GRG indicating the ability of the stock item to maximize the rate of return. The validity and effectiveness of the VPRS-index clustering / classification method is first evaluated prior to that of the expert system. After that, results of this study showed that this expert system yields a higher rate of return than those of several existing portfolio selection systems. Key words: Fuzzy C-Means, VPRS, VPRS-index method, classification, stock portfolio.

This paper presents an investigation on the effect and optimization of machining parameters on the kerf (cutting width) and material removal rate (MRR) of titanium alloy (TI-6AL-4V) using wire electrical discharge machining WEDM with a brass wire diameter of 0.5mm. The experimental studies were conducted under varyingpulse-off time, peak current, wire feed and wire tension. The settings of machining parameters were determined by using Taguchi experimental design method. The multiple performance characteristics based on the statistical-based analysis of variance (ANOVA) and grey relational analysis (GRA) was attempted. Analysis of variance was used to study the significance of process parameters on grey relational grade (GRG) which showed the most significant factor. The GRG obtained from the GRA was used to optimize the WEDM process. The optimum process parameters are determined by the GRG as the overall performance index. To validate the findings, confirmation experiment had been carried out at the optimal set of parameters, and the predicted results were found to be in good agreements with experimental findings. Improved machining performance in the WEDM process has been achieved by using this approach.

Grey relational analysis is a useful method in many fields as well known, and is presented variously, since the distinguish coefficient is fixed on using. This paper proposes a new approach for grey relational analysis that is based on topological background, and this proposal method has 3 features: (1) Grey relational matrix is always symmetric, (2) Order relation of with given samples is followed grey relational grade, (3) Distinguish coefficient is able to find an invariable structure of given data set. Two simulation examples are given, such as IRIS data set and WINE data set. This proposal method is compared with traditional grey relational analysis, about metric calculation and grey relational characteristic. In addition, it has obtained the order of given samples more clearly. And three examples are also given to show how to use the proposal method and distinguish coefficient in pattern recognition, information retrieval, and kansei engineering.