Kasandra® is the real time simulation software for spheroidal graphite foundry which, incorporating metallurgical quality (that is, thermal analysis and composition parameters) as a variable, provides a REAL TIME PREDICTION of the risk of apparition of contraction defects in critical zones of the components.
In order to perform the most reliable prediction, Kasandra® integrates the following data from the manufacturing process in actual time:
- Model geometry
- Filling process simulation
- Mold characteristics
- Feeding adjustment
- Isolated volumes analysis
- Metallurgical quaility of every casting
- Solidification process thermal risk
- Real time production process control
Applications
Know whether the quality of the melt will lead to defects apparition and their expected location. Adjust metallurgical features and feeding systems to ensure a quality outcome.
Exceed simulations based on standard parameters, incorporating the specific characteristics of your foundry and the quality of your melt.
In real time, you will be able to implement corrective actions depending on the risk of critical defects aparition detected.
Save costs and improve yield by optimizing the feeding capacity and the features of the melt.
During engineering phase, Kasandra engine is a powerful tool that outperforms other simulation tools by integrating metallurgical features for prediction and provides the keys to design and adjust metallurgical features and feeding systems:
- High yield designs and reduction in the number of risers applied.
- Considering graphite formation stages and composition needs.
- Reliable tool to perform feasibility studies and quotation (RFQ).
In production process, Kasandra lite interface makes it possible to clear every melt, ladder by ladder, before being poured into the molds:
- In real time, determines the risk of metallurgical quality of the melt to provoke the apparition of defects in parts.
- Favors the implementation of corrective action by acting over the features of the metal, casting by casting.
- Reduces final inspections and controls.
Results exploitation
Understanding the most relevanta data
to assure a defect free production
- Detailed metal temperatures are obtained.
- The starting conditions for the solidification simulation are set by the temperature map obtained at the end of the filling process.
Result of the solidification simulation for liquid fraction 0, such that the observed surface corresponds to a 99.9% solid metal and the internal fractions represent fractions in earlier transformation states or liquids.
This fraction conditions the primary feed from the riser and, therefore, determines the isolated volumes.
- The final isolated volumes represent the solidification process of the metal whose feed from the riser has been cut off and are, therefore, risk zones for the component’s soundness.
- Based on the thermal conditions (modulus, liquid fractions and hot spot) and the metallurgical quality, these isolated volumes represent the analysis units for the modelling of the contraction-expansion balance that ultimately allow the prediction of the appearance of defects.
Thermal Modulus in internal areas of the part is visualized by layered cuts.
Methodology for analyzing the thermal module in the hot spot of the part and the riser, to ensure correct feeding.
These study is essential to understand the risks of defects appearing in the neck of the riser.
Thermal analysis curves can be loaded to get porosity prediction (the video shows an example for 3 metallurgical quality grades).
System features
- Compatible with Windows.
- Different user interfaces adapted to use environments: Kasandra engine for engineering phase and Kasandra lite for production plant.
To incorporate metallurgical quality into the fill simulation, Kasandra® needs to incorporate a thermal analysis system. Although the standard configuration of the system offered by AZTERLAN contemplates the application of Thermolan®, the Kasandra® system can be configured with other thermal analysis tools on the market.
Related solutions
“The Foundry of the Future is that of connected processes that is able to take advantage of the knowledge generated inside the company at the same time that it keeps learning from its manufacturing and market experience.
Along with a deep knowledge of metallurgy, Industry 4.0 technologies, advanced data management systems and machine learning technologies have landed in this industry to transform the way castings are conceived”.
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