Search results

The purpose of this paper is to test Shattock’s legacy reputation thesis that non-leading universities in the UK face insuperable resource barriers to entering the leading group.

Employing regression analysis, the authors examine whether prioritizing research performance is a viable strategy for non-leading UK universities aiming to improve their organizational effectiveness. The dependent variable, organizational effectiveness, is measured by the annual Guardian rankings of universities. The main independent variable, research performance, is measured using “research power” (“RP”). RP is derived from the UK Research Excellence Framework.

For 2008-2014, the authors find that changes in research performance impacted university rankings. However, the authors also find that changes to the rankings are largely confined to non-leading universities and have not led to these institutions breaking into the group of leading universities. Therefore, Shattock’s thesis is supported.

Failing to maintain research performance can have significant negative consequences for the rankings of non-leading universities.

This is the first study that examines the relationship between the research performance of universities in the UK with a measure of their overall organizational effectiveness.

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.

This 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.

Taguchi 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.

The 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.

The study demonstrates that the process parameters of any dimple sheet manufacturing industry can be optimized, and the effect of process parameters can be identified.

The 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.

It is seen that little amount of work on optimization of mechanical properties taking into consideration the combined effect of design variables such as stacking angle, stacking sequence, different resins and thickness of composite laminates has been carried out. The focus of this research work is on the optimization of the design variables like stacking angle, stacking sequence, different resins and thickness of composite laminates which affect the mechanical properties of hybrid composites. For this purpose, the Taguchi technique and the method of gray relational analysis (GRA) are used to identify the optimum combination of design variables. In this case, the effect of the abovementioned design variables, particularly of the newly developed resin (NDR) on mechanical properties of hybrid composites has been investigated.

The Taguchi method is used for design of experiments and with gray relational grade (GRG) approach, the optimization is done.

From the experimental analysis and optimization study, it was seen that the NDR gives excellent bonding strength of fibers resulting in enhanced mechanical properties of hybrid composite laminates. With the GRA method, the initial setting (A3B2C4D2) was having GRG 0.866. It was increased by using a new optimum combination (A2B2C4D1) to 0.878. It means that there is an increment in the grade by 1.366%. Therefore, using the GRA approach of analysis, design variables have been successfully optimized to achieve enhanced mechanical properties of hybrid composite laminates.

This is an original research work.

This study aims to utilize the mean–variance optimization framework of Markowitz (1952) and the generalized reduced gradient (GRG) nonlinear algorithm to find the optimal portfolio that maximizes return while keeping risk at minimum.

This study applies the portfolio optimization concept of Markowitz (1952) and the GRG nonlinear algorithm to a portfolio consisting of the 30 leading stocks from the three different sectors in Amman Stock Exchange over the period from 2009 to 2013.

The selected portfolios achieve a monthly return of 5 per cent whilst keeping risk at minimum. However, if the short-selling constraint is relaxed, the monthly return will be 9 per cent. Moreover, the GRG nonlinear algorithm enables to construct a portfolio with a Sharpe ratio of 7.4.

The results of this study are vital to both academics and practitioners, specifically the Arab and Jordanian investors.

To the best of the author’s knowledge, this is the first study in Jordan and in the Arab world that constructs optimum portfolios based on the mean–variance optimization framework of Markowitz (1952) and the GRG nonlinear algorithm.

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.

Friction stir welding (FSW) is considered an environmentally sound process compared to traditional fusion welding processes. It is a complex process in which various parameters influence weld strength. Therefore, it is essential to identify the best parameter settings for achieving the desired weld quality. This paper aims to investigate the multi-response optimization of process parameters of the FSWed 6061-T6 aluminum (Al) alloy.

The input process parameters related to FSW have been sorted out from a detailed literature survey. The properties of weldments such as yield strength, ultimate tensile strength, percentage elongation and microhardness have been used to evaluate weld quality. The process parameters have been optimized using the Taguchi-based grey relational analysis (GRA) methodology. Taguchi L16 orthogonal array has been considered to design the experiments. The effect of input parameters on output responses was also determined by the analysis of variance (ANOVA) method. Finally, to corroborate the results, a confirmatory experiment was carried out using the optimized parameters from the study.

The ANOVA result indicates that the tool rotation speed was the most significant parameter followed by tool pin profile and welding speed. From the confirmation test, it was observed that the optimum FSW process parameters predicted by the Taguchi method improved the grey relational grade by 13.52%. The experimental result also revealed that the Taguchi-based GRA method is feasible in finding solutions to multi-response optimization problems in the FSW process.

The present study is unique in the multi-response optimization of FSWed 6061-T6 Al alloy using the Taguchi and GRA methodology. The weld material having better mechanical properties is essential for the material industry.

The purpose of this paper is to find the impact of various design variables on the composite shaft, and also the effect of newly developed resin (NDR) on the strength of the fibers of the composite shaft.

The Taguchi method is used to optimize the design variables. Also, GRG approach is used to validate the result.

NDR improves the bonding strength of fiber than the epoxy resin. With the grey relational analysis (GRA) method, the initial setting (A1B4C4D1) was having grey relational grade 0.957. It was enhanced by using a new optimum combination (A2B2C4D2) to 0.965. It indicates that there is an enhancement in the grade by 0.829 percent. Thus, using the GRA approach of analysis, design variables have been successfully optimized to achieve improved dynamic properties of hybrid composite shaft.

The findings of this research are helping to optimize the design variables for the composite shaft. Also, the NDR gives the good bonding strength of carbon/glass fibers in dynamic loading condition than the epoxy resin.

The purpose of the study is to fabricate a joint between two aluminium metal matrix composites using microwave hybrid heating (MHH).

Taguchi design of experiments was applied to conduct the experimental study. The mechanical properties such as ultimate tensile strength, micro-hardness and porosity were studied. Grey Relational Analysis was applied to understand the significance of fabrication parameters of best performing sample. The dominant factor of fabrication was analysed using ANOVA. The best performance sample was further characterised using X-ray diffraction and field emission scanning electron microscopy. Energy dispersive X-ray was used to analyse the elemental composition of the sample.

The Aluminium Metal Matrix Composite (AMMC) joint was successfully fabricated using MHH. The mechanical properties were mainly influenced by the fabrication factor of exposure time.

The formation of AMMC joint using MHH might explore the way for the industries in the field of joining.

This study aims to explore the effects of the COVID-19 outbreak on exports of goods and services, logistics performance, environmental management system (ISO 14001) certification and quality management system (ISO 9001) certification in top affected Asian countries of India, Iran, Indonesia, Philippines, Bangladesh and Pakistan.

A novel grey relational analysis models’ approach is used to examine the inter-relationship between COVID-19 economic growth and environmental performance. Moreover, the authors applied a conservative (maximin) model to investigate which countries have the least intensifying affected among all of the top affected COVID-19 Asian countries based on the SS degree of grey relation values. The data used in this study was collected from multiple databases during 2020 for analysis.

Results indicate that the severity of COVID-19 shows a strong negative association and influence of COVID-19 on the exportation of goods and services, logistics performance, ISO 9001 and ISO 14001 certifications in all the six highly affected countries during a pandemic outbreak. Although the adverse effects of COVID-19 in exporting countries persisted until December 31, 2020, their magnitude decreased over time in Indonesia and Pakistan. During the COVID-19 outbreak, Pakistan showed comparatively better performance among the six top highly affected Asian countries due to its smart locked down strategy and prevents its economy from severe damages. While India and Iran export drastically go down due to a rapid increase in the number of COVID-19 cases and deaths.

The research findings produce much-required policy suggestions for leaders, world agencies and governments to take corrective measures on an emergent basis to prevent the economies from more damages and improve their logistics, environmental and quality performance during the pandemic of COVID-19.

This study develops a framework and investigates the intensifying effects of COVID-19 effects on economic growth, logistics performance, environmental performance and quality production processes.