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Desai, Kaushal A
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Preferred name
Desai, Kaushal A
Alternative Name
Desai, K.
Main Affiliation
ORCID
Scopus Author ID
22940107800
Researcher ID
AAF-6911-2020
Now showing 1 - 2 of 2
- PublicationOptimal Design of a Stewart–Gough Platform for Multidirectional 3-D Printing(2018-01-01)
;Shastry, Shricharana ;Avaneesh, Ritwik; The existing 3-D printing techniques have several disadvantages such as aliasing and difficulty in building around inserts due to limited motions associated with the equipment. The limitation of build direction results in poor surface finish due to aliasing (or layer stair-stepping) and adverse material properties in certain directions which limits use of 3-D printing for many industrial applications. The present study investigates the application of Parallel Kinematic Machines (PKMs) in achieving multidirectional 3-D printing. The proposed architecture addresses some of the limitations of existing Fused Deposition Modelling (FDM)-based 3-D printer by allowing six-axis motions between extruder and platform while building the component. The study explores the application of Stewart–Gough Platform (SGP) further for 3-D printing and illustrates its capability as a viable solution for multi-axis FDM. The design of SGP for multidirectional FDM is realized for optimal dexterity using bulk dexterity index. The study discusses details of the optimization formulation and consequent results associated with the same. A conceptual design of the SGP is subsequently proposed based on the results of the optimization. The proposed SGP-based machine architecture is expected to offer advantages such as improved surface finish and control of directional properties, which signifies push towards freeform fabrication using multidirectional 3-D printing. - PublicationModeling of cutting force, tool deflection, and surface error in micro-milling operation(2018-10-01)
;Moges, Tesfaye M.; Rao, P. V.M.Micro-milling has shown great potential in producing complex miniaturized components over wide range of materials. It can also fabricate micro-products in small batches efficiently and economically. In spite of these advantages, several challenges hinder its ability to produce components with better dimensional accuracy. Among several factors, tool deflection is one of the major sources of surface error on machined parts and features. Therefore, it is necessary to develop accurate and reliable process models to analyze and improve performance of the process. This study presents a methodology to determine cutting forces and surface error in the presence of tool deflections for micro-milling operation. Tool deflections have considerable influence on instantaneous uncut chip thickness. As tool deflection alters tooth trajectories and instantaneous uncut chip thickness, the rigid cutting force model needs to be modified suitably to consider the effect of deflections. This aspect has been incorporated in the model by modifying tool center location and tooth trajectories iteratively. The convergence of an iterative algorithm determining stable chip thickness is obtained by comparing RMS deviation of average chip thickness between two successive tooth passes. The axial variation of surface error due to tool deflections is estimated using surface generation mechanism. The proposed model is implemented in the form of a computational program to predict cutting force and surface error. The results of computational model are substantiated further by conducting machining experiments. It is shown that the proposed model predicts cutting forces fairly well in the presence of tool deflections. A comparison between predicted variation of surface error and 3D images of machined surface captured using optical microscope showed good qualitative agreement in the error profiles.