Workpiece locating error prediction and compensation in fixtures

Zhu, Shaowei, Ding, Guofu, Ma, Shuwen, Yan, Kaiyin and Qin, Sheng-feng (2013) Workpiece locating error prediction and compensation in fixtures. International Journal of Advanced Manufacturing Technology, 67 (5-8). pp. 1423-1432. ISSN 0268-3768

Full text not available from this repository. (Request a copy)
Official URL: https://doi.org/10.1007/s00170-012-4578-1

Abstract

In machining process, fixture is used to keep the position and orientation of a workpiece with respect to machine tool frame. However, the workpiece always cannot be at its ideal position because of the setup error and geometric inaccuracy of the locators, clamping force, cutting force, and so on. It is necessary to predict and control the workpiece locating error which will result in machining error of parts. This paper presents a prediction model of a workpiece locating error caused by the setup error and geometric inaccuracy of locaters for the fixtures with one locating surface and two locating pins. Error parameters along 6 degrees of freedom can be calculated by the proposed model and then compensated by either using the “frame transformation” function of a numerical control (NC) system or modifying NC codes in post-processing. In addition, machining error caused by the workpiece locating error can be predicted based on a multi-body system and homogeneous transfer matrix. This is meaningful to fixture design and machining process planning. Finally, a cutting test has shown that the proposed method is practicable and effective.

Item Type: Article
Uncontrolled Keywords: Workpiece locating error, machining error, error modeling, error prediction, error compensation
Subjects: W200 Design studies
Department: Faculties > Arts, Design and Social Sciences > Design
Depositing User: Becky Skoyles
Date Deposited: 19 Mar 2014 13:33
Last Modified: 01 Feb 2022 09:54
URI: http://nrl.northumbria.ac.uk/id/eprint/15874

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics