Background and activities
PhD candidate in the "MegaMould" project. The main R&D activities in the project are related to development of intelligent optimizatoin tools for injection molding of the extra large components of a high quality, as well as use of recycled plastic materials instead of the "virgin" plastics.
My PhD project title is "Intelligent process control for thermoplastics injection molding". The project includes application of machine learning methods, mathematical modelling and the theory of decision making to increase efficiency of the process through finding relations between the set process parameters and the final parts' quality.
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
- (2020) Towards a general application programming interface (API) for injection molding machines. PeerJ Computer Science.
- (2020) Added value of a virtual approach to simulation-based learning in a manufacturing learning factory. Procedia CIRP. vol. 88.
- (2019) Application of feature selection methods for defining critical parameters in thermoplastics injection molding. Procedia CIRP. vol. 81.
- (2018) Monitoring and Control for Thermoplastics Injection Molding A Review. Procedia CIRP. vol. 67.
- (2018) Development of evaluation tools for learning factories in manufacturing education. Procedia Manufacturing. vol. 23.
- (2017) Roller Skis Assembly Line Learning Factory – Development and Learning Outcomes. Procedia Manufacturing. vol. 9.
- (2016) Preconditions for learning factory : a case study. Procedia CIRP. vol. 54.
- (2016) Application of Modern Educational Methods through Implementation of the Ambulance Simulator at a Clinic Laboratory (NTNU Gjøvik). Procedia CIRP. vol. 54.
- (2015) Principles of precision parametric reduction for mathematical models. Математичне та комп’ютерне моделювання. Серія: Технічні науки. vol. 12.
Part of book/report
- (2021) Prediction of Width and Thickness of Injection Molded Parts Using Machine Learning Methods. EcoDesign and Sustainability I.
- (2019) Application of Machine Learning Methods for Prediction of Parts Quality in Thermoplastics Injection Molding. Advanced Manufacturing and Automation VIII Proceedings IWAMA 2018.
- (2017) What is and how to develop sustainable innovation?. Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy - Proceedings of the 2016 International Conference on Leadership, Innovation and Entrepreneurship (ICLIE).