信息物理系统
多样性(控制论)
强化学习
生产(经济)
产品(数学)
订单(交换)
工业工程
批量生产
计算机科学
制造工程
工业4.0
工程类
系统工程
人工智能
嵌入式系统
运营管理
业务
财务
经济
数学
宏观经济学
操作系统
几何学
作者
Andreas Kuhnle,Nicole Röhrig,Gisela Lanza
出处
期刊:Procedia CIRP
[Elsevier]
日期:2019-01-01
卷期号:79: 391-396
被引量:56
标识
DOI:10.1016/j.procir.2019.02.101
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.
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