The University of Southampton
University of Southampton Institutional Repository

Efficient robust design for manufacturing process capability

Kumar, A., Keane, A.J., Nair, P.B. and Shaphar, S. (2006) Efficient robust design for manufacturing process capability At 6th ASMO-UK/ISSMO International Conference on Engineering Design Opimization. 03 - 04 Jul 2006. 8 pp, pp. 242-250.

Record type: Conference or Workshop Item (Paper)


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.

PDF kuma_06b.pdf - Accepted Manuscript
Download (2MB)

More information

Published date: 2006
Venue - Dates: 6th ASMO-UK/ISSMO International Conference on Engineering Design Opimization, 2006-07-03 - 2006-07-04
Keywords: robust design, bayesian monte carlo, manufacturing variations, process capability, compressor blades


Local EPrints ID: 41999
PURE UUID: 47c0bf28-4cec-453b-8af3-048a6f07f464

Catalogue record

Date deposited: 27 Oct 2006
Last modified: 17 Jul 2017 15:25

Export record


Author: A. Kumar
Author: A.J. Keane
Author: P.B. Nair
Author: S. Shaphar

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.