DocumentCode :
1589053
Title :
Fault-tolerant defect prediction in high-precision foundry
Author :
Salazar, Mikel ; Gallego, David ; Penya, Yoseba K. ; Santos, Igor ; Bringas, Pablo G.
Author_Institution :
S3Lab., Deusto Technol. Found., Bilbao, Spain
fYear :
2010
Firstpage :
373
Lastpage :
378
Abstract :
High-precision foundry production is subjected to rigorous quality controls in order to ensure a proper result. Such exams, however, are extremely expensive and only achieve good results in a posteriori fashion. In previous works, we presented a defect prediction system that achieved a 99% success rate. Still, this approach did not take into account sufficiently the geometry of the casting part models, resulting in higher raw material requirements to guarantee an appropriate outcome. In this paper, we present here a fault-tolerant software solution for casting defect prediction that is able to detect possible defects directly in the design phase by analysing the volume of three-dimensional models. To this end, we propose advanced algorithms to recreate the topology of each foundry part, analyze its volume and simulate the casting procedure, all of them specifically designed for an robust implementation over the latest graphic hardware that ensures an interactive design process.
Keywords :
casting; fault tolerance; foundries; maintenance engineering; production engineering computing; quality control; raw materials; casting defect prediction; casting procedure; fault-tolerant defect prediction; fault-tolerant software solution; high-precision foundry; interactive design process; quality controls; raw material; Algorithm design and analysis; Casting; Fault detection; Fault tolerance; Foundries; Geometry; Production; Quality control; Raw materials; Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Informatics (INDIN), 2010 8th IEEE International Conference on
Conference_Location :
Osaka
Print_ISBN :
978-1-4244-7298-7
Type :
conf
DOI :
10.1109/INDIN.2010.5549392
Filename :
5549392
Link To Document :
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