In the context of supply chain management, supplier selection can be defined as the process by which organizations score and evaluate a range of alternative suppliers to choose the best possible one who can provide superior quality of raw materials at cheaper rate and lesser lead time. It is a decision making process with multiple trade-offs between various conflicting criteria which in turn helps the organizations identify the suitable suppliers that would establish a robust supply chain assisting in maintaining a competitive edge. The main objective of supplier selection is thus focused on reducing purchase risk, maximizing overall value to the organization, and developing closeness and long-term relationships between the suppliers and the organization. In this paper, while selecting the most suitable supplier for gearboxes in an Indian iron and steel industry, assessments of three decision makers on the performance of five candidate suppliers with respect to five evaluation criteria are first aggregated using rough numbers. The definitive distances of those rough numbers are then treated as the inputs to a 25 full-factorial design plan with the corresponding multi-attributive border approximation area comparison (MABAC) scores as the output variables. Finally, a design of experiments (DoE)-based metamodel is formulated to interlink the computed MABAC scores with the considered criteria. The competing suppliers are ranked based on this rough-MABAC-DoE-based metamodel, which also easies out the computational steps when new suppliers are included in the decision making process.

Purpose The purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes. Design/methodology/approach In this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance. Findings The derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes. Practical implications This grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values. Originality/value The adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values.

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High measurement values often show on average a spontaneous decrease when remeasured under stationary study conditions. This effect is known as “regression to the mean”, a phenomenon widely met in biomedical research. In this paper a general formula is derived, which shows that this effect should be better called “regression to the mode”. Further it is shown that this effect may depend on the time‐spacing of repeated measurements in a stationary population.

Das, P. & Chatterjee, P. (2013). Urban-rural contrasts in motor fitness components of youngster footballers in West Bengal, India. J. Hum. Sport Exerc., 8(3), pp.797-805. In the present world sport and exercise should be well-matched with the surroundings and public healthiness. This study aims to examine whether urban-rural environment have any impact on motor fitness components of footballers as well as sedentary boys of the age group 14 to 16 years. The sample consisted of 60 football players (30 urban and 30 rural) and 160 sedentary boys (80 urban and 80 rural). The parameters included height, weight, body surface area (BSA) and body mass Index (BMI), agility, flexibility, leg muscle power (LMP), speed, hand grip strength (HGS). Standard techniques and procedures were followed for all the tests. Results were expressed as mean ± SD and independent samples T test was conducted to compare between the groups. Results of the study revealed that agility, flexibility, LMP, speed and HGS were significantly higher in rural boys including both of footballer (p<0.05) and sedentary (p<0.01) group compared with urban boys. From the study, it might be concluded that rural boys showed greater motor fitness comparing to their urban counterparts. However, regular training can reduce this urban-rural difference in motor fitness and lifestyle, habitual activities, living environment had great impact on motor fitness that was clearly understood from control group (sedentary boys).

The study findings suggest that air pollution could have negative effects on the hematological profile of boys and longitudinal studies may be carried out for assessing its clinical importance.

Conclusion:The results of limits of agreement analysis suggest that the application of the present form of the 20-m MST may be justified in the studied population. However, for better prediction of VO 2 max, a new equation has been computed based on the present data to be used for female college students of Nepal.

Purpose To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers. Design/methodology/approach In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores. Findings For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time. Practical implications As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers. Originality/value This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.