A method of production fine layout planning based on self-organising neural network clustering
| Autor: | Tomaž Berlec, Edvard Govekar, Primož Potočnik, Marko Starbek |
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| Rok vydání: | 2014 |
| Předmět: |
Engineering drawing
Engineering Artificial neural network business.industry Strategy and Management Distributed computing Workspace Management Science and Operations Research Industrial and Manufacturing Engineering Material flow Reduction (complexity) Product (business) Production (economics) business Cluster analysis Batch production |
| Zdroj: | International Journal of Production Research. 52:7209-7222 |
| ISSN: | 1366-588X 0020-7543 |
| DOI: | 10.1080/00207543.2014.910619 |
| Popis: | Organising and optimising production in small and medium enterprises with batch production and many different products can be very difficult due to high complexity of possible solutions. The paper presents a method of fine layout planning that rearranges production resources and minimises work and material flow transfer between production cells. The method is based on self-organising map clustering which organises the production cells into groups sharing similar product properties. The proposed method improves the internal layout of each cell with respect to a material flow diagram and a from-to matrix, and fine workspace positioning also considers various restrictions on placement, specifications and types of transportation. The method is particularly suitable for improving the existing layouts. The method was applied in the Slovenian company KGL d.o.o. and promising results were achieved. A reduction by more than 40% in the total transport length with respect to the current production layout was observed. |
| Databáze: | OpenAIRE |
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