A method of production fine layout planning based on self-organising neural network clustering

被引:5
|
作者
Berlec, Tomaz [1 ]
Potocnik, Primoz [1 ]
Govekar, Edvard [1 ]
Starbek, Marko [1 ]
机构
[1] Univ Ljubljana, Fac Mech Engn, Ljubljana 61000, Slovenia
关键词
SOM neural network; self-organised cell formation; fine layout planning; material flow improvement; GROUP-TECHNOLOGY; CELL-FORMATION; MODELS;
D O I
10.1080/00207543.2014.910619
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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.
引用
收藏
页码:7209 / 7222
页数:14
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