Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning
The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. This approach is able to utilize complex, diverse and high-dimensional data sets, which often occur in manufacturing applications, and to integrate the importan...
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| Format: | Electronic eBook |
| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Edition: | 1st ed. 2015. |
| Series: | Springer Theses, Recognizing Outstanding Ph.D. Research,
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-319-17611-6 |
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Table of Contents:
- Introduction
- Developments of manufacturing systems with a focus on product and process quality
- Current approaches with a focus on holistic information management in manufacturing
- Development of the product state concept
- Application of machine learning to identify state drivers
- Application of SVM to identify relevant state drivers
- Evaluation of the developed approach
- Recapitulation.