Efficient robust design for manufacturing process capability
Efficient robust design for manufacturing process capability
The presence of process variations in manufacturing any product is inevitable. Manufacturing variations can result in performance loss, high scrap, rdesign and product failure. This paper proposes a methodology for robust design against manufacturing process variations. The proposed method is employed to seek compressor blade designs which ahve less sensitive aerodynamic performance in presence of manufacturing uncertainties. A novel geometry modeling technique is presented to model the manufacturing uncertainty in compressor blades. A Gaussian Stochastic Process Model is employed as a surrogate to the expensive CFD simulations. The probabilistic performance of each design is evaluated using Bayesian Monte Carlo Simulation. This is combined with a Multiobjective Optimization process to allow explicit trade-off between the mean and standard deviation of the performance. The aim is to provide the designer with a Pareto-Optimal robust design set to choose the design which meets the performance specifications in presence of manufacturing uncertainty.
robust design, bayesian monte carlo, manufacturing variations, process capability, compressor blades
242-250
Kumar, A.
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Keane, A.J.
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Nair, P.B.
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Shaphar, S.
f39c4b9c-b957-4489-baf0-3bcb18888917
2006
Kumar, A.
d5d62c56-87f6-4ae1-ac67-2fb4bf8db422
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Nair, P.B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Shaphar, S.
f39c4b9c-b957-4489-baf0-3bcb18888917
Kumar, A., Keane, A.J., Nair, P.B. and Shaphar, S.
(2006)
Efficient robust design for manufacturing process capability.
6th ASMO-UK/ISSMO International Conference on Engineering Design Opimization, Oxford, UK.
03 - 04 Jul 2006.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The presence of process variations in manufacturing any product is inevitable. Manufacturing variations can result in performance loss, high scrap, rdesign and product failure. This paper proposes a methodology for robust design against manufacturing process variations. The proposed method is employed to seek compressor blade designs which ahve less sensitive aerodynamic performance in presence of manufacturing uncertainties. A novel geometry modeling technique is presented to model the manufacturing uncertainty in compressor blades. A Gaussian Stochastic Process Model is employed as a surrogate to the expensive CFD simulations. The probabilistic performance of each design is evaluated using Bayesian Monte Carlo Simulation. This is combined with a Multiobjective Optimization process to allow explicit trade-off between the mean and standard deviation of the performance. The aim is to provide the designer with a Pareto-Optimal robust design set to choose the design which meets the performance specifications in presence of manufacturing uncertainty.
Text
kuma_06b.pdf
- Accepted Manuscript
More information
Published date: 2006
Venue - Dates:
6th ASMO-UK/ISSMO International Conference on Engineering Design Opimization, Oxford, UK, 2006-07-03 - 2006-07-04
Keywords:
robust design, bayesian monte carlo, manufacturing variations, process capability, compressor blades
Identifiers
Local EPrints ID: 41999
URI: http://eprints.soton.ac.uk/id/eprint/41999
PURE UUID: 47c0bf28-4cec-453b-8af3-048a6f07f464
Catalogue record
Date deposited: 27 Oct 2006
Last modified: 16 Mar 2024 02:53
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Contributors
Author:
A. Kumar
Author:
P.B. Nair
Author:
S. Shaphar
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