Vibration during end milling causes a destructive effect: it produces poor surface finish, accelerates tool wear and reduces tool life. This article presents the use of Taguchi method-based gray relational analysis to optimize the machining parameters such as helix angle of cutting tool, cutting speed, feed rate, axial depth of cut and radial depth of cut for reduced vibration amplitude in end milling operation. L25 Taguchi orthogonal design was employed for conducting the experiments. The experiments were conducted on aluminum Al 6063 by high-speed steel end mill cutter, and acceleration amplitude was measured using fast Fourier transform analyzer. The online signals recorded for vibration amplitude picked by accelerometer at two positions: one fixed in the spindle (channel I) and another fixed in the workpiece fixture (channel II). Signal-to-noise ratio and analysis of variance were employed to determine the optimum levels. Gray relational grade was used to optimize machining parameters by considering both responses at a time.

At present, the entire globe gets engaged in importing and exporting the products for promoting their business in which supply chain management is playing a vital role. The main aspect of any effective supply chain management is the transportation of cargoes. To avoid the damages of cargoes during transportation and for minimizing the cost, the returnable containers are used. The present research deals with an inventory model of Non-Vessel Operating Common Carrier (NVOCC) for returnable containers with price dependent demand under fuzzy environment. In this study, it is presumed that the import of cargoes is less than the export. The Empty Container Repositioning (ECR) and the leasing options are utilized to replace the deficit containers which prevent shortages. The proportion of the used containers returned, the proportion of the repositioned containers and the fraction of repairable from the returned containers are considered as Triangular Fuzzy Numbers [TFNs]. Fuzzy inventory model is framed for the purpose of attaining optimal length of the screening, the repositioning cycle and the leasing cycle which are used to minimize the expected total cost and the proposed model is illustrated with the numerical example. The sensitivity analysis is performed to show the effect of fuzziness of return rate, repositioning rate and repairable percentage along with the changes in parameters.

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