Predictive process monitoring based on distributed sensor data

被引：1

作者：

Wiegand, Mario ^{[1
]}

Stolpe, Marco ^{[2
]}

Deuse, Jochen ^{[1
]}

Morik, Katharina ^{[2
]}

机构：

[1] TU Dortmund, IPS, Leonhard Euler Str 5, D-44227 Dortmund, Germany

[2] TU Dortmund, Lehrstuhl Knstliche Intelligenz LS VIII, Otto Hahn Str 12, D-44227 Dortmund, Germany

来源：

AT-AUTOMATISIERUNGSTECHNIK | 2016年 / 64卷 / 07期

关键词：

Sensor data; process monitoring; process control; time series; machine learning; SOFT SENSOR; COMPONENT ANALYSIS; QUALITY ESTIMATION; MODEL; MACHINE;

D O I：

10.1515/auto-2016-0013

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a concept for predictive process monitoring based on real-time analysis of distributed sensor data with means of machine learning. To that end the paper proposes a systematic procedure for data preparation and analysis allowing for the prediction of final product quality.

引用

页码：521 / 533

页数：13

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