Innovation Catalogue
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Q-IDSA
The Q-IDSA is a remotely accessible infrastructure, where the interoperability of pre-commercial components could be tested in a production-like scenario. TypesConnector Websitewww.sqs.es
Q-Ontology Enabler
Q-Ontology Enabler is a set of python scripts which ease the migration to the QU4LITY relational database performing a ETL processes on existing on-premises infrastructures. Programming LanguagePython TypesOntology
QARMA Quantitative Association Rules for RUL
QARMA Quantitative Association Rules for RUL ia a new highly parallel algorithm suitable for running in elastic compute environments, for mining all interesting quantitative association rules, that is, non–dominated rules having support above a minimum support...
QU4LITY Cloud Bridge
QU4LITY Cloud Bridge provides a seamless solution to exchange data using the QU4LITY Ontology Model (based on R-MPFQ), enabling a semantic enriched data exchange from on-premise data lake to QU4LITY-enabled storage using a time-based approach. SupportREST API...
QU4LITY Domain ontology
The ontology is an application-level ontology, which is the lowest ontological level which aims to represent specific application cases with highly specialized classes and individuals, such as a device, a part, a component, an equipment etc. of the assembly line....
QU4LITY simulation library for assembly processes
The simulation library facilitates and accelerates the creation of the simulations from the initial concept steps and design phases. The library is usable for any user but provides open interfaces for simulation experts to extend its functionalities....
Qu4lity Trend Cockpit
The Qu4lity trend cockpit aims at speeding up management team decisions on improving the quality of manufacturing products and assembling processes. It is based on MPFQ methodology, an innovative method to describes the dependences of materials/components, processes,...
Quality Control Data Analysis
High Performance Metrological Software for detecting deviation trends on quality control. AnalyseData ControlQuality Process TrendZDM TypesPlatform...
Quality Prediction Model via Data analytics and machine learning
The Quality Prediction Model is used to improve the overall product quality rate as well as to increase the testing efficiency. Therefore, a prediction model trained by Machine Learning Algorithms will be set up and applied to analyse product and process data.
Real time data acquisition, visualization and processing environment (CPC software)
Software suite that integrates industrial hardware (such as: highspeed-cameras; IR-cameras, Photodiodes; FPGAs; frame grabbers) for real-time multi source data acquisition, visualization and process control.
