Self-adaptive evolving forecast models with incremental PLS space updating for on-line prediction of micro-fluidic chip quality

Self-adaptive evolving forecast models with incremental PLS space updating for on-line prediction of micro-fluidic chip quality

An important predictive maintenance task in modern production systems is to predict the quality of products in order to be able to intervene at an early stage to avoid faults and waste. Here, we address the prediction of the most important quality criteria in micro-fluidics chips: the flatness and c...

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Bibliographic Details
Main Authors: Lughofer, Edwin, Pollak, Robert, Zavoianu, Alexandru-Ciprian, Pratama, Mahardhika, Meyer-Heye, Pauline, Zörrer, Helmut, Eitzinger, Christian, Haim, Julia, Radauer, Thomas
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2020
Subjects:
Engineering::Computer science and engineering
Predictive Maintenance
Time-series-Based Forecast Models
Online Access:https://hdl.handle.net/10356/139705
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Institution: Nanyang Technological University
Language: English

Internet

https://hdl.handle.net/10356/139705

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