Overall Equipment Effectiveness-related Assembly Pattern Catalogue based on Machine Learning

Using Overall Equipment Effectiveness for Manufacturing System Design

Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition

Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in computational time with increasing data size and number of signals being processed (data dimension). Certain principal machine-learning algorithms are commonly found embedded in larger detection, estimation, or classi...

Improving the performance measurement using overall equipment effectiveness in an automotive industry

Considering the present business competitive scenario, the automotive industry is under pressure to achieve higher productivity. A high level of performance and quality standard could be achieved through improving the Overall Equipment Effectiveness (OEE) of the equipment in an automotive industry. Thus, the aim of this study is to investigate the performance measurement through OEE theory in a...

Machine Learning Pattern Recognition

Introduction These lecture notes were written to provide you with a handy reference to the material that was presented in the Machine Learning: Pattern Recognition course. It is not meant to replace the book of the course [Bishop, 2007], rather, it is meant to illustrate topics that may seem a bit dry or emphasise subjects that are deemed important to this class. It will often repeat what was s...

White paper: Overall Equipment Efficiency

Overall Equipment Efficiency (OEE) by Pepperl+Fuchs GmbH, TE Connectivity, and Software AG The increase in overall equipment effectiveness (OEE) is one of the most important applications of Industrie 4.0. However, retrofitting existing production systems poses major challenges for plant operators. For this reason, Pepperl+Fuchs, TE Connectivity, and Software AG – companies that are technologica...