Please use this identifier to cite or link to this item:
|Title:||Development of a fuzzy-neuro system for parameter resetting of injection molding|
|Source:||He, W.,Zhang, Y.F.,Lee, K.S.,Liu, T.I. (2001-02). Development of a fuzzy-neuro system for parameter resetting of injection molding. Journal of Manufacturing Science and Engineering, Transactions of the ASME 123 (1) : 110-118. ScholarBank@NUS Repository.|
|Abstract:||An intelligent system has been used for injection molding. Five molded part defects, two mold parameters and the part weight are used as system inputs which are described by fuzzy terms. Twenty process parameter adjusters on an injection molding machine are used as the outputs. A neural network has been trained using the data obtained from test-runs of injection molding. The intelligent system can predict the amount to be adjusted for each parameter towards reducing or eliminating the observed defects. Using this system for the parameter resetting, production time and efforts can be saved drastically. Feasibility studies showed that this intelligent system is capable of reducing the test run time by at least 80 percent.|
|Source Title:||Journal of Manufacturing Science and Engineering, Transactions of the ASME|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 7, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.