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dc.contributor.authorLe, Khoe-Qui
dc.contributor.authorWu, Yu-Ren
dc.contributor.authorLuu, Trong-Thuan
dc.date.accessioned2024-12-24T19:11:39Z
dc.date.available2024-12-24T19:11:39Z
dc.date.copyright7/5/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.issn1087-1357
dc.identifier.othermanu_146_9_091007.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4303468
dc.description.abstractCurrently, numerous studies have applied gear skiving processes to produce face gear. However, there remains a significant challenge in achieving a flexible computing model for manufacturing a precise tooth surface for face gear. This study proposes a novel mathematical model that combines the cutter modification method and computer numerical control (CNC)-axis motion modification methods within a unified “closed-loop optimization.” This approach aims to enhance the tooth surface accuracy of skived helical face gears by determining optimal coefficients. Applying the Levenberg–Marquardt algorithm and sensitivity matrix enables the calculation of new polynomial coefficients, ensuring the attainment of gear surfaces with an accuracy grade of B6 (according to the ANSI/AGMA 2009-B01 standard) for each target surface. The proposed methodology involves the generation of a helical skiving cutter using a corrected rack. Subsequently, the cutting path on the CNC machine is optimized by incorporating additional motions expressed in polynomials. A comprehensive skiving simulation is conducted to achieve the desired face-gear surface, which is corrected by specified polynomial coefficients. The proposed model is validated through numerical and machining simulations using vericut software. The results affirm the practicality and efficacy of our approach in achieving the desired accuracy in producing helical face gears through power skiving processes.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleA Mathematical Modeling of Computer Numerical Control Skiving Process for Manufacturing Helical Face Gears Using Sensitivity Matrix Combined With Levenberg–Marquardt Algorithm
dc.typeJournal Paper
dc.journal.volume146
dc.journal.issue9
dc.journal.titleJournal of Manufacturing Science and Engineering
dc.identifier.doi10.1115/1.4065725
dc.journal.fristpage91007-1
dc.journal.lastpage91007-11
dc.page11
dc.treeJournal of Manufacturing Science and Engineering:;2024:;volume( 146 ):;issue: 009
dc.contenttypeFulltext


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