Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning

• Main Author: Wuest, Thorsten (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2015.
• Series: Springer Theses, Recognizing Outstanding Ph.D. Research,
• Subjects: Engineering.; Production management.; Computer-aided engineering.; Computational intelligence.; Industrial engineering.; Production engineering.; Industrial and Production Engineering.; Computer-Aided Engineering (CAD, CAE) and Design.; Operations Management.; Computational Intelligence.

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...

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.