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Future of sharing schedule information in automotive industry supply chains using advanced data analytics

The project intends to contribute to the automotive industry competitiveness and work by developing new solutions for improved delivery schedule quality and value adding information sharing in automotive supply chains. The project will generate a wide description of information sharing and usage in supply chains. It will also generate machine learning-based models for measurement, visualization and prediction of delivery schedule quality. The models will be tested and assessed in field pilots.

The project is organized in six work packages. The first is a survey study of information usage in automotive supply chains. The second conducts data analytics of a large amount of delivery schedule data in order to identify common variations and patterns. The third conducts case studies to explain causes and consequences. The fourth develops new machine learning-based solutions/models for visualization and prediction. The fifth studies implementation and the sixth dissemination

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Delivery schedules, Electronic Data Exchange, Machine Learning, Sales and operations planning, Supply chain, Visualization

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