The increasing availability of manufacturing data and advanced analysis tools are forcing the demand for data-driven approaches to improve the quality of workpieces and the efficiency of manufacturing processes. The analysis of real manufacturing data is challenging due to frequent changes in production circumstances. In this work, machine learning methods based on the data along the value chain of hydraulic valves are used to predict the leakage results during end-of-line testing. The leakage volume flow measurement results are very sensitive to changes in gap geometry and temperature level in the measurement cross-section. Additional measurements and experiments are required to interpret the systematic influences of the input data ...
The Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams...
One of the significant challenges to designing an emulsion transportation system is predicting frict...
peer reviewedThis paper describes an experimental study carried out on a refrigeration scroll compre...
Advancing digitalization and high computing power are drivers for the progressive use of machine lea...
This paper describes a method for the identification of valves’ failure identification, with the fin...
Machine learning, big data and deep learning are today's catchphrases for how to improve reliability...
During the transition phase of traditional manufacturing companies towards smart factories, they are...
The increased implementation of digitalisation all over the world has led to an exponential growth o...
It is estimated that about 20% of treated drinking water is lost through distribution pipeline leaka...
Prototypes of Trunnion ball valves fitted with Scotch Yoke actuators have been submitted to opening ...
Overpopulation and climate change have direly challenged the freshwater resources, specifically pota...
Water loss from leaking pipes represents a substantial loss of revenue as well as environmental and ...
The application of modern edge computing solutions within machine tools increasingly empowers the re...
This paper investigates the methodology of the machine learning technique, namely the Support Vector...
In an industrial mass production pattern, quality prediction is one of the important processes when ...
The Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams...
One of the significant challenges to designing an emulsion transportation system is predicting frict...
peer reviewedThis paper describes an experimental study carried out on a refrigeration scroll compre...
Advancing digitalization and high computing power are drivers for the progressive use of machine lea...
This paper describes a method for the identification of valves’ failure identification, with the fin...
Machine learning, big data and deep learning are today's catchphrases for how to improve reliability...
During the transition phase of traditional manufacturing companies towards smart factories, they are...
The increased implementation of digitalisation all over the world has led to an exponential growth o...
It is estimated that about 20% of treated drinking water is lost through distribution pipeline leaka...
Prototypes of Trunnion ball valves fitted with Scotch Yoke actuators have been submitted to opening ...
Overpopulation and climate change have direly challenged the freshwater resources, specifically pota...
Water loss from leaking pipes represents a substantial loss of revenue as well as environmental and ...
The application of modern edge computing solutions within machine tools increasingly empowers the re...
This paper investigates the methodology of the machine learning technique, namely the Support Vector...
In an industrial mass production pattern, quality prediction is one of the important processes when ...
The Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams...
One of the significant challenges to designing an emulsion transportation system is predicting frict...
peer reviewedThis paper describes an experimental study carried out on a refrigeration scroll compre...