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).