Please use this identifier to cite or link to this item:
Title: An integrated optimization of cutting parameters and tool path generation in ultraprecision raster milling
Authors: Wang, SJ
To, S 
Chen, X
Chen, XD
Ouyang, XB
Keywords: Tool path optimization
Surface roughness
Machining efficiency
Ultraprecision raster milling (UPRM)
Issue Date: 2014
Publisher: Springer
Source: International journal of advanced manufacturing technology, 2014, v. 75, no. 9, p. 1711-1721 How to cite?
Journal: International journal of advanced manufacturing technology 
Abstract: This paper provides a new methodology for the integrated optimization of cutting parameters and tool path generation (TPG) based on the development of prediction models for surface roughness and machining time in ultraprecision raster milling (UPRM). The proposed methodology simultaneously optimizes the cutting feed rate, the path interval, and the entry distance in the feed direction to achieve the best surface quality in a given machining time. Cutting tests are designed to verify the integrated optimization methodology. The experimental results show that, in the fabrication of plane surface, the changing of entry distance improves surface finish about 40 nm (R (a) ) and 200 nm (R (t) ) in vertical cutting and decreases about 8 nm (R (a) ) and 35 nm (R (t) ) in horizontal cutting with less than 2 s spending extra machining time. The optimal shift ratio decreases surface roughness about 7 nm (R (a) ) and 26 nm (R (t) ) in the fabrication of cylinder surfaces, while the total machining time only increases 2.5 s. This infers that the integrated optimization methodology contributes to improve surface quality without decreasing the machining efficiency in ultraprecision milling process.
ISSN: 0268-3768
EISSN: 1433-3015
DOI: 10.1007/s00170-014-6254-0
Appears in Collections:Journal/Magazine Article

View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Aug 13, 2017

Page view(s)

Last Week
Last month
Checked on Aug 13, 2017

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.