Autonomous order dispatching in the semiconductor industry using reinforcement learning

被引:32
作者
Kuhnle, Andreas [1 ]
Roehrig, Nicole [1 ]
Lanza, Gisela [1 ]
机构
[1] Karlsruhe Inst Technol, Wbk Inst Prod Sci, Kaiserstr 12, D-76137 Karlsruhe, Germany
来源
12TH CIRP CONFERENCE ON INTELLIGENT COMPUTATION IN MANUFACTURING ENGINEERING | 2019年 / 79卷
关键词
Production planning; Reinforcement learning; Semiconductor industry;
D O I
10.1016/j.procir.2019.02.101
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cyber Physical Production Systems (CPPS) provide a huge amount of data. Simultaneously, operational decisions are getting ever more complex due to smaller batch sizes, a larger product variety and complex processes in production systems. Production engineers struggle to utilize the recorded data to optimize production processes effectively because of a rising level of complexity. This paper shows the successful implementation of an autonomous order dispatching system that is based on a Reinforcement Learning (RL) algorithm. The real-world use case in the semiconductor industry is a highly suitable example of a cyber physical and digitized production system. (C) 2019 The Authors. Published by Elsevier B. V.
引用
收藏
页码:391 / 396
页数:6
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