You might also like

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

• Book details
• Synopsis
• Trending among others

You get 249 loyalty points

Book synopsis

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 domains (aviation, chemical and semiconductor). The results, which are reported in detail in this book, confirmed that it is possible to incorporate implicit process intra- and interrelations on both a process and programme level by applying SVM-based feature ranking. In practice, this method can be used to identify the most important process parameters and state characteristics, the so-called state drivers, of a manufacturing system. Given the increasing availability of data and information, this selection support can be directly utilized in, e.g., quality monitoring and advanced process control. Importantly, the method is neither limited to specific products, manufacturing processes or systems, nor by specific quality concepts.

Book details

Book category Books in English Economics, finance, business & management Business & management Management & management techniques

• Full title: Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning
• Author: Thorsten Wuest
• Language: English
• Binding: Paperback
• Number of pages: 272
• EAN: 9783319386980
• ISBN: 3319386980
• ID: 15194632
• Publisher: Springer International Publishing AG
• Weight: 4453 g
• Dimensions: 235 × 155 × 16 mm
• Date of publishing: 17. October 2016

Trending among others

---

---

---