Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning
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Published By Springer International Publishing

9783319176109, 9783319176116

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Introduction

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning ◽

10.1007/978-3-319-17611-6_1 ◽

2015 ◽

pp. 1-13

Author(s):

Thorsten Wuest

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Recapitulation

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning ◽

10.1007/978-3-319-17611-6_8 ◽

2015 ◽

pp. 211-214

Author(s):

Thorsten Wuest

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Application of Machine Learning to Identify State Drivers

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning ◽

10.1007/978-3-319-17611-6_5 ◽

2015 ◽

pp. 125-152 ◽

Cited By ~ 1

Author(s):

Thorsten Wuest

Keyword(s):

Machine Learning

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Developments of Manufacturing Systems with a Focus on Product and Process Quality

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning ◽

10.1007/978-3-319-17611-6_2 ◽

2015 ◽

pp. 15-49 ◽

Cited By ~ 1

Author(s):

Thorsten Wuest

Keyword(s):

Manufacturing Systems ◽

Process Quality ◽

Product And Process ◽

Product And Process Quality

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Development of the Product State Concept

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning ◽

10.1007/978-3-319-17611-6_4 ◽

2015 ◽

pp. 69-124

Author(s):

Thorsten Wuest

Keyword(s):

Product State

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Evaluation of the Developed Approach

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning ◽

10.1007/978-3-319-17611-6_7 ◽

2015 ◽

pp. 189-210

Author(s):

Thorsten Wuest

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Application of SVM to Identify Relevant State Drivers

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning ◽

10.1007/978-3-319-17611-6_6 ◽

2015 ◽

pp. 153-188 ◽

Cited By ~ 1

Author(s):

Thorsten Wuest

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Current Approaches with a Focus on Holistic Information Management in Manufacturing

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning ◽

10.1007/978-3-319-17611-6_3 ◽

2015 ◽

pp. 51-67 ◽

Cited By ~ 1

Author(s):

Thorsten Wuest

Keyword(s):

Information Management

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Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine LearningLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Introduction

Recapitulation

Application of Machine Learning to Identify State Drivers

Developments of Manufacturing Systems with a Focus on Product and Process Quality

Development of the Product State Concept

Evaluation of the Developed Approach

Application of SVM to Identify Relevant State Drivers

Current Approaches with a Focus on Holistic Information Management in Manufacturing

Springer Theses - Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning
Latest Publications