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.
| Original language | English |
|---|---|
| Pages (from-to) | 839-850 |
| Number of pages | 12 |
| Journal | Structural and Multidisciplinary Optimization |
| Volume | 49 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 2014 |
Keywords
- Conventional spinning
- Probabilistic modeling
- Uncertainty analysis
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