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contributor authorKukreja, Aman
contributor authorPande, S. S.
date accessioned2023-11-29T18:55:30Z
date available2023-11-29T18:55:30Z
date copyright12/9/2022 12:00:00 AM
date issued12/9/2022 12:00:00 AM
date issued2022-12-09
identifier issn1530-9827
identifier otherjcise_23_3_031009.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4294465
description abstractThe primary objective of an efficient computer numerical control (CNC) finishing toolpath strategy is to reduce the machining time and maintain desired surface finish (scallop). Among traditional toolpath planning strategies, iso-scallop gives the shortest toolpath while achieving a uniform surface finish. However, it is computationally complex, time-consuming, and sometimes produces topological inconsistencies in regions of high curvature/gradient. This paper presents a novel voxel-based toolpath planning algorithm to address these issues for the three-axis milling of freeform surfaces. Two strategies have been proposed, namely, iso-scallop and hybrid iso-scallop. Gouge-free cutter location (CL) points are initially computed from the voxel-based model, followed by iso-scallop toolpath generation using a binary search algorithm. The hybrid strategy involves region segmentation to generate an adaptive toolpath in high curvature/gradients regions. The overlapping toolpath is stitched and refined to create an efficient iso-scallop-based tool path. The developed system was extensively tested for complex freeform surface parts and was found to be computationally efficient, robust, and accurate in generating a finishing toolpath.
publisherThe American Society of Mechanical Engineers (ASME)
titleAn Efficient Iso-Scallop Toolpath Planning Strategy Using Voxel-Based Computer Aided Design Model
typeJournal Paper
journal volume23
journal issue3
journal titleJournal of Computing and Information Science in Engineering
identifier doi10.1115/1.4055372
journal fristpage31009-1
journal lastpage31009-12
page12
treeJournal of Computing and Information Science in Engineering:;2022:;volume( 023 ):;issue: 003
contenttypeFulltext


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