Woo, W.-S., Curtis, D. orcid.org/0000-0001-6402-6996, Bagni, C. et al. (3 more authors) (2022) Productivity enhancement of aircraft turbine disk using a two-step strategy based on tool-path planning and NC-code optimization. Metals, 12 (4). 567.
Abstract
Most of the parts of an aircraft require the use of lightweight and high-strength materials. Since aircraft parts mainly use mechanical cutting processes, which are the most suitable material removal mechanism, to minimize changes in material properties, it is necessary to develop an optimal cutting tool and cutting solution for each material. This work aims to enhance productivity and reduce the production cost of an aircraft turbine disk through designing a cutting strategy and optimizing the cutting conditions using a simulation approach. The number of tools was reduced from eight to six compared to the existing process conditions for semi-finishing and finishing of a turbine disk, and a new tool path was proposed through simulation. The cycle time was reduced by about 24%. NC-code optimization was performed through feed-rate optimization considering cutting force and chip thickness. As a result, cycle times were reduced by about 14%. Through tool-path optimization and NC-code optimization, it was confirmed that the total cycle time was reduced by about 54%, and tool wear was significantly improved.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | turbine disk; nickel-based superalloy; productivity; tool path; machining accuracy |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > University of Sheffield Research Centres and Institutes > AMRC with Boeing (Sheffield) The University of Sheffield > Advanced Manufacturing Institute (Sheffield) > AMRC with Boeing (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 14 Apr 2022 08:44 |
Last Modified: | 14 Apr 2022 08:44 |
Status: | Published |
Publisher: | MDPI AG |
Refereed: | Yes |
Identification Number: | 10.3390/met12040567 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185702 |