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The purpose of this paper is to propose an interpretation of the grey relational grade taking into account its variation range on the basis of the error propagation theory.

The paper uses error propagation theory to calculate the uncertainty of the grey relational grade, exploring how errors are propagated through the sequential operations of the grey relational analysis.

The non‐consideration of the error associated to the measurement of the experimental data that is transferred to the grey relational grade may have a potential effect on the interpretation of the grey relational rank. Data uncertainty quantification provides information about how well measurement fits to the value of the measured quantity and determines its validity. Therefore, this might lead one to consider that some sequences are less attractive than other lower‐ranked ones.

The combination of the grey and error propagation theories is a tool to choose the most accurate solution in grey relational grade ranks.

This study provides a new approach to interpret grey relational grade classifications.

The purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite using High-Speed Steel drill bits (5, 10, 15 mm) coated with tungsten carbide by means of statistical reproduction of the delamination factor and machining force using Taguchi–Grey Relational Analysis.

The contemplated process parameters are Feed, Speed and Drill Diameter. The trials were carried out by taking advantage of the L-27 factorial design by Taguchi. Three factors, the three level Taguchi Orthogonal Array design in Grey Relational Analysis was used to carry out the trial study. Video Measuring System was used to identify the damage around the drill region. “Minitab 18” was used to examine the data collected by taking advantage of the various statistical and graphical tools available. Examination of variance is used to legitimize the model in identifying the most notable parameter.

The optimised set of input parameters were found out successfully which are as follows: Feed Rate: 450 mm/min, Cutting Speed: 3,000 rpm and Drill Diameter of 5 mm. When these values are fed in as input the optimised output is being obtained. From ANOVA analysis, it is apparent that the Speed (contribution of 92.6%) is the most influencing parameter on the delamination factor and machining force of the FRP material.

Optimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey Relational Analysis has not been previously explored.

This paper aims to investigate the effect and parametric optimization of process parameters during milling of glass fibre-reinforced plastics (GFRP) composites using grey relational analysis (GRA).

Experiments are conducted using helix angle, spindle speed, feed rate, depth of cut and fibre orientation angle as typical process parameters. GRA is adopted to obtain grey relational grade for the milling process with multiple characteristics, namely, machining force and material removal rate (MRR). Analysis of variance is performed to get the contribution of each parameter on the performance characteristics.

It is observed that helix angle and fibre orientation angle are the most significant process parameters that affect the milling of GFRP composites. The experimental results reveal that the helix angle of 45°, spindle speed of 3000 rpm, feed rate of 1000 mm/min, depth of cut of 2 mm and fibre orientation angle of 15° is the optimum combination of lower machining force and higher MRR. The experimental results for the optimal setting show that there is considerable improvement in the process.

Optimization of process parameters on machining force and MRR during endmilling of GFRP composites using GRA has not been attempted previously.

The purpose of this paper is to present the results of an investigation into the effect of injection molding process parameters on the performance of direct metal laser sintered (DMLS) mold in producing quality Zytel nylon 66 plastic parts with consistency in part shrinkage and shot/part weight.

The injection mold for an industrial component (hub gear) was fabricated in EOS M‐250 machine using bronze‐based material. The effect of four injection molding parameters (injection pressure, melt temperature, speed, and injection time) on part shrinkage and weight were studied experimentally using L₉ orthogonal array. The weight of the part just after ejecting from the cavity, and the average shrinkage measured after cooling, were used in grey relational analysis technique to assess the effect of each molding parameter. Further, surface properties such as surface finish, wear, scratch and corrosion resistance tests were conducted on DMLS mold material samples, in order to evaluate its use in rapid manufacturing applications.

The study found that injection speed and melt temperature have significant influence on part weight and shrinkage. The optimized molding process variables were slightly more in the case of DMLS molds as compared with the parameters suggested in the plastic datasheet. Scanning electro microscope (SEM) analysis of the mold surface after producing 5,000 glass filled Nylon 66 (Zytel) moldings did not indicate any surface degradation, confirming the use of DMLS mold in rapid manufacturing of few thousands of moldings.

The grey relational analysis does not compute the effect of any two or more variables together unlike ANNOVA. Second, this study alone is not enough to estimate life of DMLS mold, although 5,000 glass filled nylon 66 moldings are successfully produced without any damage on mold surface.

This investigation demonstrates a generic approach of using grey relational analysis to quantify the effect of different molding process variables on selected quality parameters. This method can be easily extended for new processes and materials. The preliminary tests on surface finish, scratch, wear and corrosion resistance performed on DMLS mold samples have highlighted the need for improving surface properties to enhance their life. The authors are currently working on hard coating of DMLS molds as one of the solutions.

Use of grey relational analysis is new to the problem of injection molding process optimization. Moreover, effect of injection molding parameters on part weight and shrinkage in DMLS mold has not been studied previously. This study helps while considering DMLS molds for manufacturing few thousands of parts.

The purpose of this paper is to establish the grey relational estimating model of soil pH value based on hyper-spectral data.

As to the uncertainty of the factors affecting the soil pH value estimation based on hyper-spectral, the grey weighted relation estimation model was set up according to the grey system theory. Then the linear regression correction model is established according to the difference and grey relation degree information between the estimated samples and their corresponding pattern. At the same time, the model was applied to Hengshan county of Shanxi province.

The results are convincing: not only that the linear regression correction model of grey relation estimating pattern of soil pH value based on hyper-spectral data is valid, but also the model’s estimating accuracy is higher, which the corrected average relative error is 0.2578 per cent, and the decision coefficient R²=0.9876.

The method proposed in the paper can be used at soil pH value hyper-spectral inversion and even for other similar forecast problem.

The paper succeeds in realising both the soil pH value hyper-spectral grey relation estimating pattern based on the grey relational theory and the correction model of the estimating pattern by using the linear regression.

This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation.

The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done.

The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA.

In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order.

The study presents the case of an automotive component, which illustrates practical relevance.

In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.

Assessing image quality is a difficult task. Different demands need distinct criteria, so it is not realistic to decide which contrast enhancement method is better only through one criterion. The main purpose is to propose an efficient scheme to effectively evaluate image quality. Furthermore, the idea can be applied in other fields.

To objectively and quantitatively assess image quality, the authors integrate four criteria into one composite criterion and use it to evaluate seven existing contrast enhancement methods. The mechanism of integration is through a newly proposed way of computing a grey relational grade (GRGd), called the consistent grey relational grade (CGRGd).

In this paper, the authors propose the CGRGd, which is more efficient and consistent than other existing GRGds. When applied to image quality evaluation, the proposed CGRGd can effectively choose the best method than others. The results also indicate that the proposed CGRGd combined with appropriate criteria can be widely used in the field of multiple criteria.

The proposed CGRGd is a new approach to the problem of multi-criteria evaluation, and its application to the evaluation of image quality is a novel idea. For readers interested in the field of multi-criteria decision-making, the CGRGd provides an efficient and effective alternative.

This study aimed to develop a mathematical model for delamination and surface roughness during end milling by using grey relational analysis (GRA) and to determine how the input parameters (cutting speed, depth of cut, helix angle and feed rate) influence the output response (delamination and surface roughness) in machining of hybrid glass fibre-reinforced plastic (GFRP) (abaca and glass) composite using solid carbide end mill cutter.

The Four factors, three levels Taguchi orthogonal array design in GRA is used to conduct the experimental investigation. The Shop Vision inspection system is used to measure the width of maximum damage of the machined hybrid GFRP composite. The Shop Handysurf E-35A surface roughness tester is used to measure the surface roughness of the machined hybrid GFRP composite. “Minitab 14” is used to analyse the data collected graphically. Analysis of variance is conducted to validate the model in determining the most significant parameter.

The GRA is used to predict the input factors influencing the delamination and surface roughness on the machined surfaces of the hybrid GFRP composite at different cutting conditions with the chosen range of 95 per cent confidence intervals. Analysis on the influences of the entire individual input machining parameters on the delamination and surface roughness has been conducted using GRA.

Effect of milling of the hybrid GFRP composite on delamination and surface roughness with various helix angle solid carbide end mill has not been analysed yet using the GRA technique.

In the presented research work, the authors fabricated the multiple MS plate (Grade: IS 2062) specimens and applied a novel integrated computational TR_IF_MR_G approach with grey relational analysis (GRA) toward solving weld bead optimization problem in MIG welding procedure. The objective of research is to determine the optimum setting between MIG welding input process parameters, e.g. welding current, open circuit voltage and thickness of plate in attaining high tensile strength with weld bead geometry quality characteristics, e.g. bead width, reinforcement, penetration and dilution in investigating define MS specimens.

The Taguchi's L₉ orthogonal array (OA) design is respected to conduct the experiments on MS plate specimens to attain output objectives. Later, the evaluated multiple output objectives are transformed into single response by applying a novel integrated computational TR_IF_MR_G approach with GRA. Thereafter, the outset of signal-to-noise ratio (S/N ratio) accompanied by ANOVA (Analysis of variance) is explored to optimize objective function.

The computed results are confirmed by conducting the experiments on same identical specimens. The outcome of the confirmation tests yielded an improvement of 0.24454, 0.372486, 0.686635 and 0.4106846 in grey relational grade (GRG), overall ratio index, reference grade and full multiplicative index, respectively, after validating the results.

In the presented work, the authors constructed a novel integrated computational TR_IF_MR_G approach via clustering GRA, overall ratio index (ORI), full multiplicative index (FMI) with GRA-reference grade (RG) and tested as well as applied with Taguchi concept to attain objective of the research work.

The purpose of this paper is to propose a multi-criteria decision making method to evaluate factory data collection (FDC) system alternatives.

“Information” in is fundamental resource to the success of any business which is as valuable as capital or people. The factory data (information) collection system (FDC system) consists of the various paper documents, terminals, and automated devices located throughout the plant for collecting data on shop floor operations for compiling and processing the data. In this paper, nine alternatives of FDC methods are evaluated on the basis of eight criteria. The weight of each criterion is determined using Analytic Hierarchy Process, and the same weights are used to evaluate alternatives of FDC system using Grey Relational Analysis – A multi-criterion decision making method.

The methodology facilitates the selection of the best FDC system that will minimize the data entry time and chances of errors. The methodology suggests Radio-Frequency Identification (RFID) system is the most preferred choice (ideal) among the nine alternatives whereas Operation tear strips is the worst solution.

The proposed methodology will provide a useful tool to the decision maker, which may help to eliminate the associated risks during data entry. The selected best FDC system, i.e. RFID is most suitable tool for ERP system to integrate internal (manufacturing) and external (sales and service) management information system.