Machine-cell formation through neural network models

DOI10.1080/00207549408957061zbMath0904.90081OpenAlexW2009829744MaRDI QIDQ4394338

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Publication date: 19 January 1999

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207549408957061

zbMATH Keywords

neural networkcellular manufacturing systemsidentification of machine-cells

Mathematics Subject Classification ID

Production models (90B30)

Related Items (11)

A simulated annealing approach for manufacturing cell formation with multiple identical machines. ⋮ Machine-part cell formation in group technology using a modified ART1 method ⋮ A two-phase heuristic algorithm for cell formation problems considering alternative part routes and machine sequences ⋮ An ant colony optimization metaheuristic for machine-part cell formation problems ⋮ Heuristic rules-based logic cell formation algorithm ⋮ On Adapting Neural Network to Cellular Manufacturing ⋮ Group technology by an ant system algorithm ⋮ Incremental cell formation considering alternative machines ⋮ On the use of the asymptotic forms of the Boolean matrix for designing cellular manufacturing systems. -- An improved approach ⋮ Performance of Fuzzy ART neural network and hierarchical clustering for part-machine grouping based on operation sequences ⋮ A bibliography of neural network business applications research: 1994--1998

Cites Work

• A neural network system for shape-based classification and coding of rotational parts
• An ideal seed non-hierarchical clustering algorithm for cellular manufacturing
• ZODIAC—an algorithm for concurrent formation of part-families and machine-cells
• Problem Decomposition and Data Reorganization by a Clustering Technique

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