Subsystem modelling using neural networks with application to manufacturing systems

Where traditional methods of robust design have their limitations in manufacturing systems, it appears that system modelling can provide advantages. When manufacturing systems can be split into subsystems, subsystem models and continuity and compatibility constraints are required to develop an overa...

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Bibliographic Details
Main Authors: Cooper, P.L., Savage, G.J.
Format: Conference Proceeding
Language:English
Subjects:
Cooling
Costs
Design engineering
Design methodology
Joining processes
Manufacturing processes
Manufacturing systems
Neural networks
Robustness
Systems engineering and theory
Online Access:Request full text
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Summary:Where traditional methods of robust design have their limitations in manufacturing systems, it appears that system modelling can provide advantages. When manufacturing systems can be split into subsystems, subsystem models and continuity and compatibility constraints are required to develop an overall system model. Where physical information is lacking, empirical models can be created. Herein, the radial basis function neural network method for empirical modelling is discussed and procedures for connecting these models with physical system information is demonstrated using a cooling fin problem.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.1998.725130