Intelligent Fuzzy-Based Process Selection Methodology for Manufacturing of Plastic Products
Abstract
Plastic products can be made by a variety of manufacturing processes. Traditionally, the selection of the process is primarily based on the empirical knowledge and past experience of the manufacturing personnel. This paper presents an intelligent fuzzy-based methodology to help designers in selection of an appropriate plastic manufacturing process. The plastic part attributes are broadly classified into three main categories: part characteristics, material type, and production requirements. A fuzzy membership function is generated for each of the component attributes using the self-organizing paradigm. Fuzzy Associative Memories (FAMs) are used to perform reasoning on these input fuzzy sets to derive the output fuzzy sets. The output fuzzy sets are then defuzzified to derive process compatibility scores (PCS). A test part is used to demonstrate the working of the proposed methodology.
Recommended Citation
R. Raviwongse et al., "Intelligent Fuzzy-Based Process Selection Methodology for Manufacturing of Plastic Products," Intelligent Engineering Systems Through Artificial Neural Networks, vol. 7, pp. 897 - 902, Dec 1997.
Department(s)
Engineering Management and Systems Engineering
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 The Authors, All rights reserved.
Publication Date
01 Dec 1997
