Large volume metrology process model: measurability analysis with integration of metrology classification model and feature-based selection model.
Cheng, Chun Hung and Huo, Dehong and Xhang, Xi and Dai, Wei and Maropoulos, Paul (2010) Large volume metrology process model: measurability analysis with integration of metrology classification model and feature-based selection model. In: Proceedings of the 6th CIRP-Sponsored International Conference on Digital Enterprise Technology. Huang, George and Maropoulos, Paul and Mak, K. L., eds. Advances in Intelligent and Soft Computing (66). Springer, Berlin, pp. 1013-1026. ISBN 9783642104305
Full text is not in this repository.
Aircraft manufacturing industries are looking for solutions in order to increase their productivity. One of the solutions is to apply the metrology systems during the production and assembly processes. Metrology Process Model (MPM) (Maropoulos et al, 2007) has been introduced which emphasises metrology applications with assembly planning, manufacturing processes and product designing. Measurability analysis is part of the MPM and the aim of this analysis is to check the feasibility for measuring the designed large scale components. Measurability Analysis has been integrated in order to provide an efficient matching system. Metrology database is structured by developing the Metrology Classification Model. Furthermore, the feature-based selection model is also explained. By combining two classification models, a novel approach and selection processes for integrated measurability analysis system (MAS) are introduced and such integrated MAS could provide much more meaningful matching results for the operators.
|Item Type:||Book Section|
|Research Areas:||A. Middlesex University Schools and Centres > School of Science and Technology > Science & Technology|
|Deposited On:||12 Apr 2010 15:18|
|Last Modified:||06 Feb 2013 11:35|
Repository staff only: item control page
Full text downloads (NB count will be zero if no full text documents are attached to the record)
Downloads per month over the past year