Machine Learning for industrial applications: A comprehensive literature review
Abstract Machine Learning (ML) is a branch of artificial intelligence that studies algorithms
able to learn autonomously, directly from the input data. Over the last decade, ML …
able to learn autonomously, directly from the input data. Over the last decade, ML …
Machine learning in manufacturing: advantages, challenges, and applications
The nature of manufacturing systems faces ever more complex, dynamic and at times even
chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an …
chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an …
An approach to monitoring quality in manufacturing using supervised machine learning on product state data
Increasing market demand towards higher product and process quality and efficiency forces
companies to think of new and innovative ways to optimize their production. In the area of …
companies to think of new and innovative ways to optimize their production. In the area of …
In situ monitoring of FDM machine condition via acoustic emission
H Wu, Y Wang, Z Yu - The International Journal of Advanced …, 2016 - Springer
Fused deposition modeling (FDM) is one of the most popular additive manufacturing
technologies for fabricating prototypes with complex geometry and different materials …
technologies for fabricating prototypes with complex geometry and different materials …
A review of machine learning kernel methods in statistical process monitoring
The complexity of modern problems turns increasingly larger in industrial environments, so
the classical process monitoring techniques have to adapt to deal with those problems. This …
the classical process monitoring techniques have to adapt to deal with those problems. This …
[BOOK][B] Industrial applications of machine learning
Industrial Applications of Machine Learning shows how machine learning can be applied to
address real-world problems in the fourth industrial revolution, and provides the required …
address real-world problems in the fourth industrial revolution, and provides the required …
Using SVM based method for equipment fault detection in a thermal power plant
KY Chen, LS Chen, MC Chen, CL Lee - Computers in industry, 2011 - Elsevier
Due to the growing demand on electricity, how to improve the efficiency of equipment in a
thermal power plant has become one of the critical issues. Reports indicate that efficiency …
thermal power plant has become one of the critical issues. Reports indicate that efficiency …
A survey of control-chart pattern-recognition literature (1991–2010) based on a new conceptual classification scheme
Control Chart Pattern Recognition (CCPR) is a critical task in Statistical Process Control
(SPC). Abnormal patterns exhibited in control charts can be associated with certain …
(SPC). Abnormal patterns exhibited in control charts can be associated with certain …
Application of machine learning in statistical process control charts: A survey and perspective
Over the past decades, control charts, one of the essential tools in Statistical Process Control
(SPC), have been widely implemented in manufacturing industries as an effective approach …
(SPC), have been widely implemented in manufacturing industries as an effective approach …
A weighted support vector machine method for control chart pattern recognition
Manual inspection and evaluation of quality control data is a tedious task that requires the
undistracted attention of specialized personnel. On the other hand, automated monitoring of …
undistracted attention of specialized personnel. On the other hand, automated monitoring of …