Hybrid Artificial Intelligence System for the Design of Highly - Automated Production Systems

被引:12
作者
Hagemann, Simon [1 ]
Suennetcioglu, Atakan [2 ]
Stark, Rainer [1 ,2 ]
机构
[1] Tech Univ Berlin, Dept Ind Informat Technol, Pascalstr 8-9, D-10587 Berlin, Germany
[2] Fraunhofer IPK, Div Virtual Prod Creat, Pascalstr 8-9, D-10587 Berlin, Germany
来源
7TH INTERNATIONAL CONFERENCE ON CHANGEABLE, AGILE, RECONFIGURABLE AND VIRTUAL PRODUCTION (CARV2018) | 2019年 / 28卷
关键词
Artificial Intelligence; Machine Learning; Automotive; Body-in-White; Production System Design; Data Analytics; Pattern Recognition; Process Automatization; Robotics; Industrial Data Quality;
D O I
10.1016/j.promfg.2018.12.026
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The automated design of production systems is a young field of research which has not been widely explored by industry nor research in recent decades. Currently, the effort spent in production system design is increasing significantly in automotive industry due to the number of product variants and product complexity. Intelligent methods can support engineers in repetitive tasks and give them more opportunity to focus on work which requires their core competencies. This paper presents a novel artificial intelligence methodology that automatically generates initial production system configurations based on real industrial scenarios in the automotive field of body-in-white production. The hybrid methodology reacts flexibly against data sets of different content and has been implemented in a software prototype. (C) 2019 The Authors. Published by Elsevier B.V.
引用
收藏
页码:160 / 166
页数:7
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