Quality Control
Reduce waste, react faster.
With LabV you save up to 30% processing time and detect material and production errors more quickly.
Without any effort.
Common issues in quality control
Manual data entry
Fragmented data
Lack of a standardized data structure
Lack of overview on data, projects and historical data
The solution - complete integration of devices and IT infrastructure
- Digital twin of each sample thanks to a central database
- Fully inter-connected database - from the analytical results through to test portocols and IT infrastructure
- Efficient management of all test orders
- Ki-assisted evaluation of complex search queries in a comprehensive data pool
“Fewer tests means fewer engineering hours and faster development. With LabV we have a saving of 10% in engineering hours”
Development Manager
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Manufacturer of paints and coatings
The solution - one single database for everything
Our features
- A central database for laboratory and material development
- Efficient communication and collaboration
- Individual connection to devices, MES, ERP and IT infrastructure
- User-friendly interface for company-wide acceptance
- Quick recognition of connections and correlations
- AI-enabled data infrastructure for evaluating complex search queries in a comprehensive data pool
Managing
- Complete and cross-funcitional connection of all devices and the existing IT infrastructure
- Collected data from laboratory and development
- Management of testing orders and analyses
Analyzing
- Fast data evaluation with integrated statistical functions and visualizations
- Centralized material database
- Automated comparison of target values and actual results
- Identification of correlations and relationships
Exploiting
- More insightsacross the entire database
- Comprehensive search function
- AI-enabled data infrastructure for intelligent predictions on product properties and recipes
Example - Trend identification at your fingertips
LabV allows to identify trends and correlations much easier and quicker than ever before, maximizing the utility of the data pool. Detecting anomalies earlier means less waste and more efficiency.
WHITE PAPER
Digitalization - step by step
Learn in the white paper:
- The implications of inadequate digitalization on quality assurance labs
- The differences between LIMS, CAQ and data management systems for materials testing laboratories
- Proposed solutions to overcome Excel and paper and to ensure data integrity
- How companies can systematically start their digitization journey
