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Identifying product and process state drivers in manufacturing systems using supervised machine learning

Author: Thorsten Wuest
Publisher: Cham : Springer, 2015. ©2015
Series: Springer theses.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
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 important process intra- and interrelations. The approach has been evaluated using three scenarios from different manufacturing  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: Printed edition:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Thorsten Wuest
ISBN: 9783319176116 3319176110 3319176102 9783319176109
OCLC Number: 908030519
Notes: "Doctoral these accepted by University of Bremen, Germany."
Description: 1 online resource (xviii, 272 pages) : illustrations (some color).
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.
Series Title: Springer theses.
Responsibility: Thorsten Wuest.

Abstract:

The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. In practice, this method can be used to identify the most  Read more...

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