Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29604
Title: Prediction of surface generation in ultra-precision raster milling of optical freeform surfaces using an Integrated Kinematics Error Model
Authors: Kong, LB
Cheung, CF 
Keywords: Error budget
Homogenous transformation matrix
Kinematics model
Multi-axis machining system
Tool path generation
Ultra-precision raster milling
Issue Date: 2012
Publisher: Elsevier
Source: Advances in engineering software, 2012, v. 45, no. 1, p. 124-136 How to cite?
Journal: Advances in engineering software 
Abstract: Due to the geometrical complexity of optical freeform surfaces, it is still difficult to predict the form errors for ultra-precision multi-axis raster milling of these surfaces with sub-micrometer form accuracy. This paper presents an Integrated Kinematics Error Model (IKEM) for the analysis of form error for ultra-precision raster milling of optical freeform surfaces. It attempts to address the challenges of previous kinematics models which are either too conceptual or too theoretical in which the error components are difficult to determine. As an alternate approach, the components of the machine motion errors are analyzed and the homogenous transformation matrix is employed to build a kinematic machining error model step by step. Considering the difficulties and inconveniences of measuring separate error components, IKEM is proposed on the theory of multi-body kinematics and the surface generation mechanism in ultra-precision machining. A series of experiments have been conducted to further validate the proposed model. The successful development of IKEM makes it more convenient for machining error budgets, and can also be generalized and applicable for other multi-axis machining systems.
URI: http://hdl.handle.net/10397/29604
ISSN: 0965-9978
DOI: 10.1016/j.advengsoft.2011.09.011
Appears in Collections:Journal/Magazine Article

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

SCOPUSTM   
Citations

17
Last Week
0
Last month
1
Citations as of Aug 14, 2017

WEB OF SCIENCETM
Citations

13
Last Week
0
Last month
0
Citations as of Aug 12, 2017

Page view(s)

29
Last Week
2
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



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