Data Analytics & AI

In our world view, human beings are at the heart and center of production. This is the premise under which we use and research artificial intelligence in production. We assume that companies should not only invest in hardware and software, but also systematically use their production engineers’ so-called domain knowledge. We support our partners in all their AI concerns along the entire process chain – from planning the networked factory and managing it, all the way to the smart product. We always focus on methods of analysis which give industry experts transparent results based on an intelligent combination of human know-how and machine analytics. Visual analytics allows us to explore unknown data and to examine statistical models for plausibility. Our specialized tools support data scientists in their daily work and allow industry experts to apply their knowledge in assessing and interpreting the patterns they find.

Increase of productivity via Data analytics/Machine learning
©Fraunhofer IPK ©CCM-ITA
Cockpit 4.0

Semantic product data for engineering

EIBA

Automated identification of used products

ReLkat

Reinforcement learning for complex automation technology applications

Spot Welding Process

Development of AI models with data responses from resistance welding process

Optimization of production planning and manufacturing processes via AI.
©Fraunhofer IPK ©CCM-ITA
EIBA

Automated identification of used products

Industrie 4.0

Flexible Transparent Manufacturing

Additive Manufacturing 4.0

Mobile App for Quality Assurance

Reduction of production costs through Condition monitoring & predictive maintenance
©Fraunhofer IPK ©CCM-ITA
Lifecycle Monitoring with the Digital Twin

IoT-based services for industrial production

MobiKAM

Measuring and testing with mobile cameras

AMELI 4.0

Condition Monitoring in Industrie 4.0

ReLkat

Reinforcement learning for complex automation technology applications

Development of data-driven business models (smart services)
©Fraunhofer IPK ©CCM-ITA
Smart Service Customization

Utilization of life cycle data through data-driven business models

Data-driven business model

A methodology to develop smart services

Machine vision for optimization of production & logistics
©Fraunhofer IPK ©CCM-ITA
Components identification via app

AI-supported image processing on the smartphone

Logic.Cube

Components identification via app

Automatic optical inspection of glass tubes

Optical inspection for continuous quality assurance

EIBA

Automated identification of used products

TDO 4.0 – Snake Robot for Spot Welding Inspection Activities

Development of an end-effector light and small to promote high volume inspection in complex geometry of automotive body shells for automotive industry