Authors
Keiji Kamei*, [email protected]
Department of Production Systems, Nishinippon Institute of Technology,
1-11 Aratsu, Kanda, Miyakogun, Fukuoka 800-0394, Japan†
Takafumi Arai
Nissan Motor Kyushu Co. Ltd., 1-3 Shinhama-cho, Kanda, Miyakogun, Fukuoka
800-0395, Japan
www.nishitech.ac.jp/~kamei/
*
In 2007 he obtained his PhD at the Department of Brain Science and Engineering,
Kyushu Institute of Technology. From April, 2007 to March, 2014, he was
a lecturer. Since April, 2014, he has been an associate professor, Nishinippon
Institute of Technology.
Available Online 30 September 2018.
DOI
https://doi.org/10.2991/jrnal.2018.5.2.13
Keywords
Constrained Genetic Algorithm; Plant Optimization; Industrial Application;
Car manufacturing
Abstract
Recently, improvement of production efficiency on cars manufacturers is
required. However, that improvements under existing circumstances are depending
on experience and intuition by workers. We propose to objectively and efficiently
improve a production line based on a GA. The difficulty of applying a GA
is the number of racks and boxes is predetermined, and so we apply constrained
GA. The results of simulation for virtual production line show that our
proposal succeeded in reducing about 10 seconds per a car compared with
random positioning.
Copyright
Copyright © 2018, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).