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- 저자 : Vaibhav Shivhare (검색결과 2 건)
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Harun Rashid Siddiqui,Vaibhav Shivhare 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.12
This paper shows the study of free vibration analysis of stiffened isotropic plates with orthogonal stiffeners placed eccentrically and concentrically to the plates. In this paper finite element model is developed in ANSYS parametric design language code and discretized using 20 node structural element (SOLID 186) and convergence study of isotropic stiffened plates has been performed and compare the results with related published literature. Effects of various parameters such as boundary conditions, aspect ratios, position of stiffeners eccentrically and concentrically to the stiffened plates has been studied. The vibration analysis of stiffened plate have been studied using Block -Lanczos algorithm. The results of non dimensional frequency of eccentric and concentric isotropic stiffened plate have been compare at different mode shapes, aspect ratio’s, boundary conditions using ANSYS.
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Development of Artificial Intelligence Model for the Prediction of MRR in Turning
Vinay Kumar Chaurasia,Dinesh Kumar Kasdekar,Vaibhav Shivhare 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.2
In machining operations, the extents of important effect of the process parameters like speed, feed, and depth of cut are different for different responses. This paper investigates the effect of process parameters in turning of AA6061 T6 on conventional lathe. The problem appeared owing to selection of parameters increases the deficiency of turning process. Modeling can facilitate the acquisition of a better understanding of such complex process, save the machining time and make the process economic. Thus, the present work clearly defines the development of an artificial neural network (ANN) model for predicting the material removal rate. This study presents a new method to prediction the material removal rate (MRR) on a lathe turning Process. Firstly, Process parameters namely, Spindle speed, depth of cut and feed rate are designed using the Box behnken (DOE) was employed as the experimental strategy. The result shows that the ANN model can predict the material removal rate effectively. This approach helps in economic lathe machining.
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