Doctorate hsnResearch Projects
Development of an ontology for digitizing heterogeneous and isolated material data from bioplastics for data related optimization of the injection molding process

Development of an ontology for digitizing heterogeneous and isolated material data from bioplastics for data related optimization of the injection molding process

Led by:  Supervisor: Prof. Dr.-Ing. Andrea Siebert-Raths, HsH, Institute for Bioplastics and Biocomposites. Co-Supervisor: Prof. Dr. Ulrich Giese, LUH, Institute of Inorganic Chemistry
Team:  Marco Neudecker
Year:  2020

This project deals with the digitization of material and process-related data from bioplastics in the industrially highly relevant application field of injection molding. Among the thermoplastics, bioplastics pose a particular challenge because, compared to conventional petroleum-based plastics, there is often only very limited material data with relevant material parameters and so process step simulations can only be carried out inadequately and with limited precision. This significantly inhibits the application and use of bioplastics. The aim of the project is to process these information gaps with the extensive material data from the research activities of the IfBB in the field of bioplastics production, processing and characterization, to store them in a structured data repository and to make them available for material science. A domain-specific bioplastic ontology is being developed for the semantic description, networking and machine readability of the material and process data. The aim is to developed the data repository and the ontology in coordination with the MaterialDigital innovation platform by establishing links to the platform via interfaces. The quality of the material data is validated and optimized through joint consideration of injection molding simulations and real injection molding tests. The quality of the simulation based on the material data sets that will be available in the future on the MaterialDigital platform should be curable, adaptable and optimizable by users.