Background and activities
Ivanna graduated master in Sustainable Manufacturing at Gjøvik University College. She has a background in engineering (computer-aided manufacturing, risk assessment), manufacturing technologies and vast organizational experience, highly interested in combining technological and organizational innovation to create sustainable manufacturing processes. Nowadays, the research area of study is machine learning for manufacturing (including Additive manufacturing or 3D Printing). She works on control and management of variations in additive manufacturing. The main goal of her research is to develop an intelligent system for quality assurance for additive manufacturing. Machine learning methods are used in order to improve prediction models of the EOS P395 polymer powder bed fusion system. Ivanna is open for collaboration, and she is interested in data from different AM systems.
TØL4012 - Sustainable Manufacturing Technologies
TEK1000 - Introduction to technology
MASG1002 - Introduction to mechanical engineering
Additive Manufacturing/ 3D Printing, Manufacturing Technologies, Sustainable Manufacturing, Machine Learning, Artificial Intelligence, Process Optimization, Predictive Modelling, Statistical Analysis, Data Analysis, Software Engineering.
Python, SQL, LabVIEW, LaTeX, SPSS, Magics, MatLab, Microsoft Office (with VBA programming experience).
Scientific, academic and artistic work
Displaying a selection of activities. See all publications in the database
- (2020) Prediction of geometry deviations in additive manufactured parts: comparison of linear regression with machine learning algorithms. Journal of Intelligent Manufacturing.
- (2020) Challenges and proposed solutions for aluminium in laser powder bed fusion. Procedia CIRP.
- (2020) Extracting shape features from a surface mesh using geometric reasoning. Procedia CIRP. vol. 93.
- (2019) Application of Machine Learning Techniques to Predict the Mechanical Properties of Polyamide 2200 (PA12) in Additive Manufacturing. Applied Sciences. vol. 9 (6).
- (2018) Statistical analysis of dimensional accuracy in additive manufacturing considering STL model properties. The International Journal of Advanced Manufacturing Technology. vol. 97 (5-8).
- (2018) Optimization of Process Parameters for Powder Bed Fusion Additive Manufacturing by Combination of Machine Learning and Finite Element Method: A Conceptual Framework. Procedia CIRP. vol. 67.
- (2016) Human-Machine Interface for Artificial Neural Network Based Machine Tool Process Monitoring. Procedia CIRP. vol. 41.
Part of book/report
- (2019) Application of Machine Learning Methods to Improve Dimensional Accuracy in Additive Manufacturing. Advanced Manufacturing and Automation VIII Proceedings IWAMA 2018.
- (2020) Machine Learning of Quality Assurance in Polymer Powder Bed Fusion Additive Manufacturing. Mapping build layout design to quality of AM products as a part of an intelligent system for quality assurance. Norges teknisk-naturvitenskapelige universitet. 2020. ISBN 9788232645886.
- (2019) Mechanical properties of polyamide 12 parts made by powder bed fusion (additive manufacturing). Nordic Polymer Days 2019 ; Trondheim. 2019-06-05 - 2019-06-07.