The present study reports on the application of accelerated cooling environment (ACE) in hard turning of AISI D2 steel (55 ± 1HRC) using mixed ceramic insert (Al2O3 + TiCN) which is rarely being investigated and to address the major problems of brittle fracture of tool tip that arises through cutting forces and friction at tool-work and chip-tool interface. In spraying process, some portion of spraying coolant vaporize due to heat when it reaches to cutting zone where as remaining portion of coolant easily penetrate in cutting zone through capillary action and reduces friction as well as heat in cutting zone. Abrasion and chipping are noticed to be dominant wear mechanism. Cutting speed and depth of cut are significant for flank wear as well as cutting temperature whereas feed is significant for average surface roughness. Serrated chips have been identified at higher cutting speed and higher feeds. Optimal parametric combination is found to be d1-f1-v2 (0.1mm-0.04 m/min-108 m/min) and tool life and machining cost per part are 70 minutes and Rs 76.76 respectively. Investigation shows the worthy of application of ACE in hard turning in industrial sectors ecologically and economically. Empirical models reveal statistically significance due to higher coefficient of correlations.

Inconel 825 is high nickel-chromium-based superalloy which retains its mechanical properties and exhibits good corrosion and oxidation resistance at elevated temperature. Inconel 825 is extensively used for making aircraft engine parts like combustor casing and turbine blades in aero space industry. This research proposed the Response Surface Methodology with GRA to optimize multiple responses during Wire-cut EDM of Inconel 825. At optimum combination of input parameters i.e. A4B1C1D5E4F2, increase in MRR from 36.13 mm2/min to 41.822 mm2/min, decrease in SR from 2.842μm to 2.445μm and decrease in WWR from 0.01832 to 0.01758 was obtained. Experimental results showed that pulse-on time, wire feed, pulse-off time, and peak current significantly affected the MRR, and surface integrity of specimen and electrode with the formation of craters, pockmarks, debris, micro cracks, and recast layer. The optimal parametric combination obtained from the present study will be advantageous for working on high strength; high thermal conductivity and low melting point materials like nickel alloys.

The revolutionary alterations and conversions occurring in information and communication technologies, have triggered an increase in the electronic commerce applications. Airline tickets are one of the most popular items purchased on the internet. The airline websites have become a big distribution channel for the companies to sustain their competitiveness. At this moment, the competition is increasing as airlines try to acquire and retain customers in the airline industry. To acquire and retain customers in such a highly competitive market, it is important for airlines to understand their relative levels of quality in terms of critical elements affecting their competitive advantages. In this study, an integrated two-stage multi-criteria decision-making techniques were used for the measurement of the performance of the airline websites using the Entropy Weight Method and the Grey Relational Analysis approach. The performance of 11 airline companies’ websites operating in Turkey was evaluated in terms of seven criteria. The data of quality website from airlines websites were taken more than 30 trails on various occasions on different periods of times. The data has been taken from 1 December 2016 to 31 December 2016. The weights of the attributes were calculated by Entropy Weight Method, the evaluation of the alternatives using the Grey Relational Analysis method were given ranking of websites.

Selection of the qualified and the most appropriate employee plays crucial role for the success of the businesses. The selection process is complex and contains both subjective and objective criteria to be considered. For this reason, in this paper, Grey Relational Analysis (GRA) is proposed for employee selection. To illustrate the applicability of the proposed method, the most appropriate software engineer is selected for a technology firm. By this way, a scientific multi criteria decision making (MCDM) method is proposed to the firm that determines the best candidate intuitively with traditional methods.

Two sets of nine different silicon carbide particulate (SiCp) reinforced Al 7075 Metal Matrix Composites (MMCs) were fabricated using liquid metallurgy stir casting process. Mean particle size and weight percentage of the reinforcement were varied according to Taguchi L9 Design of Experiments (DOE). One set of the cast composites were then heat treated to T6 condition. Optical micrographs of the MMCs reveal consistent dispersion of reinforcements in the matrix phase. Mechanical properties were determined for both as-cast and heat treated MMCs for comparison of the experimental results. Linear regression models were developed for mechanical properties of the heat treated MMCs using list square method of regression analysis. The fabrication process parameters were then optimized using Taguchi based grey relational analysis for the multiple mechanical properties of the heat treated MMCs. The largest value of mean grey relational grade was obtained for the composite with mean particle size 6.18 µm and 25 weight % of reinforcement. The optimal combination of process parameters were then verified through confirmation experiments, which resulted 42% of improvement in the grey relational grade. Finally, the percentage of contribution of each process parameter on the multiple performance characteristics was calculated through Analysis of Variance (ANOVA).

Turning experiments were carried out on AA 7075/SiC composite workpiece in dry and spray cooling environments based on L16 Taguchi design of experiments. Multiple performance optimization of process parameters was performed using grey relational analysis. The performance characteristics considered were average surface roughness, cutting tool temperature and material removal rate. Uncoated carbide inserts were used for machining the workpiece in a high speed precision lathe. A grey relational grade obtained from grey relational analysis was used to optimize the process parameters. Optimal combination of process parameters was then determined by the Taguchi method using the grey relational grade as the performance index. Experimental results indicated that the turning in spray cooling environment was beneficial compared to that in dry environment for the quality response characteristics under consideration. Analysis of variance showed that feed was the most significant parameter for the multiple performance characteristics during turning in both the environments.

Supplier evaluation and selection play a vital role in establishing an effective supply chain for any firm. The supplier evaluation not only enables the firm to know the performance of suppliers, but also gives an indication of the ability of the firm itself to gain competitive advantage. The appropriate evaluation is the basis for the subsequent selection of the best supplier. This paper presents a hybrid methodology using Data Envelopment Analysis (DEA), Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA) to evaluate suppliers and to identify the best supplier for a firm. In this work, super efficiency and cross efficiency methods of DEA are employed to determine the efficiencies and the performance scores of the suppliers respectively. On the basis of super efficiency and cross efficiency scores, the list of efficient suppliers with high performance is identified and GRA methodology is adopted to identify the best supplier. A case study is presented to demonstrate the proposed hybrid methodology.

In the present work, a multi-response optimization method is used to optimize the machining parameters in turning of glass fiber reinforced polymer (GFRP) composites. Parameters like spindle speed (N), feed rate (f) and depth of cut (d) are taken to obtain the responses such as surface roughness (Ra) and material removal rate (MRR). Taguchi’s L9 orthogonal array has been used for machining the work-piece. Analysis of variance (ANOVA) has been carried out to check the significant process parameter in a single objective performance characteristic. The multiple performance characteristics have been analysed using Grey relational analysis and an appreciable result has been reported with this approach.

Machining of hardened work materials with appropriate levels of process parameters is still a burning issue in manufacturing sectors and challenging. It is because of pressing demand of surface quality which adversely affected by evolution of tool wear. Therefore the present investigation is undertaken to make a decision on parametric optimization of multi-responses such as flank wear and surface roughness during machining hardened AISI 52100 steel (55±1) steel using mixed ceramic insert under dry environment through grey relational analysis combined with Taguchi approach. Also predicted mathematical models of 1st and 2nd order have been developed for responses and checked for its accuracy. Second order mathematical model presented higher R2 value and represents best fit of the model and adequate compared to first order model. Model indicates good correlations between the experimental and predicted results. The proposed grey-based Taguchi methodology has been proved to be efficient for solving multi-attribute decision making problem as a case study in hard machining environment.

This paper discusses the application of the Taguchi method to optimize the machining parameters for machining of GFRP composite in drilling for individual responses such as thrust force and delamination factor. Moreover, a multi-response performance characteristic is used for optimization of process parameters with application of grey relational analysis. An orthogonal array (L9), grey relational generation, grey relational coefficient and grey – fuzzy grade obtained from the grey relational analysis applied as performance index to solve the optimization problem of drilling parameters for GFRP composite. Taguchi orthogonal array, the signal-to-noise ratio, and the analysis of variance are used to investigate the optimal levels of cutting parameters. The confirmation tests are conducted to verify the results and it is observed that grey-fuzzy approach is efficient in determining the optimal cutting parameters.