Optimization of the ingot casting process by minimization of macro segregation and porosity
Reference number | |
Coordinator | SWERIM AB - Swerim AB, Kista |
Funding from Vinnova | SEK 3 000 000 |
Project duration | November 2018 - March 2023 |
Status | Completed |
Venture | The strategic innovation programme for Metallic material |
Call | 2017-05475-en |
Important results from the project
The project has investigated macrosegregations and porosity in the ingot casting process and proposed process changes to increase yield. This could be achieved by deepening the knowledge of the ingot casting process for a selection of molds through comprehensive temperature measurements, ingot quality analysis and characterization of hot top materials. The information was used to develop models for simulating macrosegregations and optimizing the hot top design. The goal to achieve increased yields was found partially achieved in the evaluated optimized hot top designs.
Expected long term effects
The results show that it is possible to optimize the hot top design so that an increased yield can be obtained. The methods used within the project can be used for similar studies and process optimizations for other ingot casting molds at ingot casting companies. Deficiencies have been identified in the used macrosegregation models, which should be further developed to increase precision, to reach their full potential for process optimization. Dissemination of knowledge to other ingot casters will be arranged in a future workshop.
Approach and implementation
The project had a linear implementation with extensive mapping of the ingot casting process initially, followed by the development of models and parameter studies. The project ended with evaluation of proposed hot top designs in plant trials. This arrangement worked well, but during the course of the work minor knowledge gaps emerged that could have been addressed at an earlier stage for better results. The fact that the participating companies had different methods for evaluating ingot quality provided insights that can lead to improvements in future studies.