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White paper
Read white paper on digitalization and industry 4.0 in quality control, material development and process engineering.
Artificial Intelligence in the Testing Laboratory
Learn in the white paper:
- The historical development of artificial intelligence and its importance in the testing laboratory
- Current advances and specific applications of AI in quality assurance and materials development
- The role of the digital twin in process optimization and product quality
- Requirements for a successful use of AI in the laboratory
- Specific recommendations for implementing Laboratory 4.0 solutions and AI technologies in your lab
New Case Study
A Case Study on Digital Transformation in the Paints and Coatings Industry
The Seamlessly Digitalized Development Process
Learn in the case study
- The impact of insufficient digitization on paint and coatings R&D labs
- The differences between data management systems and traditional processes such as Excel and paper in formulation development
- Solutions to overcome manual processes
- How companies are benefiting from digitized development
Whitepapers
Artificial Intelligence in the Testing Laboratory
- Current advances and specific applications of AI in quality assurance and materials development
- The role of the digital twin in process optimization and product quality
- Requirements for a successful use of AI in the laboratory
- Specific recommendations for implementing Laboratory 4.0 solutions and AI technologies in your lab
Quality Assurance's big challenges
- 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
