Please use this identifier to cite or link to this item: https://doi.org/10.1023/A:1008904108676
Title: Towards intelligent setting of process parameters for layered manufacturing
Authors: Wang, W.L.
Conley, J.G.
Yan, Y.N.
Fuh, J.Y.H. 
Issue Date: 2000
Citation: Wang, W.L., Conley, J.G., Yan, Y.N., Fuh, J.Y.H. (2000). Towards intelligent setting of process parameters for layered manufacturing. Journal of Intelligent Manufacturing 11 (1) : 65-74. ScholarBank@NUS Repository. https://doi.org/10.1023/A:1008904108676
Abstract: The performance of a layered manufacturing (LM) process is determined by the appropriate setting of process parameters. The study of the relationship between performance and process parameters is therefore an important area of LM process planning research. The trend in modern industry is to move from conventional automation to intelligent automation. LM technology is essentially an automated manufacturing technology that is evolving towards an intelligent automation technology. Slicing solid manufacturing (SSM) is a LM technique using paper as the working material and a CO2 laser as the cutting tool. In this manuscript, a back propagation (BP) learning algorithm of an artificial neural network (ANN) is used to determine appropriate process parameters for the SSM method. Key process parameters affecting accuracy are investigated. Quantitative relationships between the input parameters and output accuracy are established by developing the BP neural network.
Source Title: Journal of Intelligent Manufacturing
URI: http://scholarbank.nus.edu.sg/handle/10635/92809
ISSN: 09565515
DOI: 10.1023/A:1008904108676
Appears in Collections:Staff Publications

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