ISSN:
1433-3015
Keywords:
Group technology
;
Neural networks
;
Part family formation
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
Abstract Most of the part family formation methods are concerned with “how to form” the families as opposed to “how to identify” the families. However, a more appropriate approach would be to identify “naturally occurring” families since these methods are based on the production flow analysis, which uses already implemented routing data. This paper presents a new approach using the memory association of neural networks to identify naturally existing families. The developed system, Feature-Based Memory Association Network (FBMAN), operates by the exhaustive association approach which deals with the difficult problem of exceptional parts. Comparison with the results generated by other methods proves the effectiveness of FBMAN.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01350823
