- Tytuł:
- Diagnosis of Missed Ductile Iron Melts with Process Modelling
- Autorzy:
-
Perzyk, M.
Werlaty, M. - Powiązania:
- https://bibliotekanauki.pl/articles/382916.pdf
- Data publikacji:
- 2017
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
quality management
information technology
foundry industry
process fault diagnosis
ductile iron melting
data driven model
zarządzanie jakością
technologia informacyjna
przemysł odlewniczy
diagnostyka uszkodzeń
topienie żeliwa - Opis:
- The paper presents an application of advanced data-driven (soft) models in finding the most probable particular causes of missed ductile iron melts. The proposed methodology was tested using real foundry data set containing 1020 records with contents of 9 chemical elements in the iron as the process input variables and the ductile iron grade as the output. This dependent variable was of discrete (nominal) type with four possible values: ‘400/18’, ‘500/07’, ‘500/07 special’ and ‘non-classified’, i.e. the missed melt. Several types of classification models were built and tested: MLP-type Artificial Neural Network, Support Vector Machine and two versions of Classification Trees. The best accuracy of predictions was achieved by one of the Classification Tree model, which was then used in the simulations leading to conversion of the missed melts to the expected grades. Two strategies of changing the input values (chemical composition) were tried: content of a single element at a time and simultaneous changes of a selected pair of elements. It was found that in the vast majority of the missed melts the changes of single elements concentrations have led to the change from the non-classified iron to its expected grade. In the case of the three remaining melts the simultaneous changes of pairs of the elements’ concentrations appeared to be successful and that those cases were in agreement with foundry staff expertise. It is concluded that utilizing an advanced data-driven process model can significantly facilitate diagnosis of defective products and out-of-control foundry processes.
- Źródło:
-
Archives of Foundry Engineering; 2017, 17, 4; 123-126
1897-3310
2299-2944 - Pojawia się w:
- Archives of Foundry Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł