Shi, F., Long, H. orcid.org/0000-0003-1673-1193, Zhan, M. et al. (1 more author) (2014) Uncertainty analysis on process responses of conventional spinning using finite element method. Structural and Multidisciplinary Optimization, 49 (5). pp. 839-850. ISSN 1615-147X
Abstract
Conventional spinning is a widely used metal forming process to manufacture rotationally axis-symmetric and asymmetric products. Considerable efforts have been made to investigate the forming quality of spun parts using the process in recent years. However, inherent uncertainty properties involved in the spinning process are rarely considered in previous studies. In this paper, an uncertainty analysis and process optimisation procedure have been developed and implemented on conventional spinning with 3D Finite Element Method (FEM). Three process variables are randomized by Gaussian distribution to study the probabilistic characteristics of two process responses. Linear and quadratic approximate representations are constructed by Monte Carlo based Response Surface Method (RSM) with Latin Hypercube Sampling (LHS). The Most Probable Point (MPP) method, which has been widely used to estimate the failure probability in other applications, is further developed in this paper to obtain the probability distribution of the system responses. Following an evaluation of the system responses conducted by the MPP method, a control variable method is used to reduce the variance of spun part wall thickness and total roller force to satisfy the 3σ quality requirement. This uncertainty analysis and process optimisation procedure can be easily implemented in other metal spinning processes. © 2014 Springer-Verlag Berlin Heidelberg.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer-Verlag Berlin Heidelberg 2014. This is an author produced version of a paper subsequently published in Structural and Multidisciplinary Optimization. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Aug 2016 09:35 |
Last Modified: | 22 Mar 2018 18:51 |
Published Version: | http://dx.doi.org/10.1007/s00158-014-1061-7 |
Status: | Published |
Publisher: | Springer |
Refereed: | Yes |
Identification Number: | 10.1007/s00158-014-1061-7 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:103635 |