Center for Applied Research on Supply Chain Services at Fraunhofer IIS»Data Science« is defined as an interdisciplinary field of research that enables scientifically sound methods, processes, algorithms and systems for extracting insights and patterns from both structured and unstructured data. The goal is to generate information from large amounts of data and derive recommendations for action that enable a company to operate more efficiently. In logistics, transportation and supply chain management, the use of Data Science in the right places can clearly improve efficiency and competitiveness. Data science mostly uses machine learning methods for this purpose, and is located at the interface between mathematics, statistics and information technology.
Group Data Science
Making the right decisions with forecasts
The group »Data Science« focuses on the development and application of methods for time series analysis, whereby more precise demand forecasts in intralogistics, volume forecasts in transport logistics, raw material price forecasts or conclusions from production parameters on product quality are calculated.
In addition to the forecast itself, the quantification of the forecast uncertainty is also important when it comes to making the right decision, because this tells us with what probability which event will occur.
The special feature of the group's research work is the combination of its own competencies with those of other groups, for example in combining the forecast results with mathematical optimization models for automated and optimal planning decisions.
Competences and methods |