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Modern industrial working environments are characterised by complex production processes, a wide range of exposure scenarios and high standards for the protection of workers. Occupational health prevention plays a central role in this context: it enables potential health risks to be identified early, the implementation of targeted preventive measures and the promotion of safe and sustainable working conditions.
Together with Volkswagen AG, the Department of Occupational, Social and Preventive Medicine at Göttingen University Medical Centre is developing data-driven approaches to further strengthen occupational health prevention in industrial work environments. The projects investigate how existing occupational health, biomonitoring, exposure-related and contextual data can be utilised more effectively to improve preventive care.
A key objective is to investigate how the procedure and frequency of occupational health examinations can be further imporved in a more evidence-based and risk-adapted manner. Methods of feature selection and machine learning help to identify the most meaningful examination parameters, exposure indicators and contextual factors, whilst reducing redundant or less relevant variables.
The projects also address a key challenge in occupational biomonitoring: the confunders of biological measurements.
Welding: biomonitoring and prevention at Volkswagen Kassel
Welding is a key component of industrial production. However, depending on the materials and processes used, welding fumes may contain hazardous substances such as chromium (VI) and nickel compounds. These substances are of concern to occupational health as they can contribute to respiratory tract irritation, chronic lung disease and an increased risk of cancer.
The project which is being carried out in collaboration with Volkswagen Kassel is investigating how occupational health, biomonitoring and exposure-related data can be used to improve prevention at welding-related workplaces.
Battery cell production: biomonitoring and risk assessment at Volkswagen Salzgitter
Battery cell production is a key area of industrial transformation, wich raises new occupational health issues. Particularly in regard to potential exposure to hazardous substances during production processes and in other high-risk areas (including storage and handling).
The project at Volkswagen Salzgitter focuses on assessing exposure to relevant substances throughout the entire production chain and in the development of a bespoke biomonitoring programme for the production facility. This approach aims to strengthen occupational health and safety measures in this emerging industrial sector.
Project lead: Dr. Diego Tapias
Dr Diego Tapias is a data scientist and AI expert at the Department of Occupational, Social and Preventive Medicine at Göttingen University Hospital. His work focuses on the intersection of statistics, data science, artificial intelligence and occupational health research. In particular, he analyses large and heterogeneous datasets from companies, insurance providers and occupational health contexts to support prevention, risk assessment and evidence-based decision-making processes.
Following his PhD in statistical physics, he worked in research, teaching and data analysis projects, specialising in statistical modelling, machine learning, complex systems and network analysis. He also completed further training in data engineering and big data analytics. At the department, he contributes this methodological expertise to projects on digital transformation, prevention and the data-driven advancement of occupational medicine.