Abstract

For plastic products, one of the crucial decisions made during the preliminary design stage is the selection of an appropriate manufacturing process. In many industries, the selection of the manufacturing process is primarily based on the empirical knowledge and past experience of the manufacturing personnel. This selection procedure may result in inconsistent or poor choices if the manufacturing personnel fail to map correctly the product characteristics with the manufacturing efficacy of various manufacturing processes. This paper presents an intelligent self-organizing map (SOM)/fuzzy-based model to aid designers in the 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 attributes using the self-organizing map 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 determine the process compatibility scores (PCS). The working of the proposed model is demonstrated using an example case.

Department(s)

Engineering Management and Systems Engineering

International Standard Serial Number (ISSN)

0268-3768

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Springer, All rights reserved.

Publication Date

01 Jan 2000

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