Big Data & Machine Learning

Description

• Analysis, systematization and evaluation of large volumes of technological and production logistics data

• Application and generation of machine learning methods and algorithms for pattern recognition and forecasting in the context of production planning and control

• Example: Derivation or generation and parameterization of production logistics process chains for new products or components based on similarity characteristics and type representatives

Current projects

Collaborative project: Intelligent geodata-based inventory determination in container management for low-value load carriers (GeoBest)

AIMS5.0 - AI-supported electronic systems for sustainable production

Collaborative project: Machine learning to improve the technology route in complex semiconductor production (LOTSE)

Completed projects

AI4BinMan - User support through machine learning methods for container cycle analysis and optimization

SVAT - Swarm behavior of autonomous transport systems