Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB

AI/ML-based data analysis

Artificial intelligence (AI) methods, such as machine learning (ML), are already revolutionizing the analysis of production data: Advanced algorithms enable the interpretation of large and complex amounts of data so that insights can be gained and added value generated. Examples include improved quality and minimized waste through quality forecasts and optimized machine parameterization, minimized downtimes through real-time monitoring and maintenance forecasts or increased overall performance through automated decision-making processes.

By using AI in production, companies can thus optimize their use of resources, reduce waste or scrap and promote environmental sustainability. Fraunhofer IOSB develops innovative algorithms specifically for the special challenges of production, promotes economic and ecological goals and creates sustainable competitive advantages.

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AI and ML for industrial production

AI / ML in the industry

AI Systems Engineering

AI also requires a methodical, engineering-like approach if projects are to reach their goal, results are to be put into productive use and solutions, once implemented, are to remain in operation permanently.

AI Systems Engineering in the industry

Karlsruhe research factory for AI-integrated production

Karlsruhe Research Factory
 

HeatSteel

Development of an innovative and energy-efficient tempering line for ultra-thin precision strips

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Machine Learning for Production – ML4P

In the ML4P lighthouse project, six Fraunhofer Institutes, led by the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB in Karlsruhe, are researching the development of a tool-supported process model and the implementation of corresponding interoperable software tools in order to systematically tap the optimization potential in production plants through the use of machine learning methods.

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© Fraunhofer IOSB

Data analysis platform for SMEs: Industry 4.0 MonOpt

Integrated data management and advanced data analysis make it possible to systematically monitor production processes and increase efficiency.  

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© Fraunhofer IOSB

Data-driven fault localization in process engineering

Alarm management helps to detect those process variables that are closest to the cause of the fault. The plant operator's attention can thus be focused on these variables and the cause of the fault can be localized efficiently.

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