To improve development efficiency - Reducing work interruptions while waiting for material test results.
The prediction of material properties using machine learning has finally been realized! "Predictor" is a material property prediction system that achieves high prediction accuracy by using the dataset from the material property database "Horizon" for training. It is the latest solution aimed at material experts.
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basic information
How much time do you spend on material testing? • Each property under conditions such as high temperature, specific heat treatment, and products • Each property when changing the composition of the material It requires significant time and cost to subject all of these to material testing. Additionally, while waiting for test results, material development and design analysis work is interrupted. By reducing the time required for testing, Predictor will enhance the speed of your material development and product design.
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Applications/Examples of results
To the departments of material development, design, analysis, etc.
Detailed information
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Example of actual screen (Model selection for prediction)
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Example of actual screen (Material condition selection)
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Actual screen example (prediction result)
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Company information
Total Materia AG (formerly Key to Metals AG) develops, sells, and supports the materials platform "Total Materia." As a pioneer in this field, we launched the first online database in 1999. Since then, we have focused on expanding the database, developing new features, improving data quality, and enhancing customer support. Currently, "Total Materia" is implemented in over 100 countries worldwide. Our customers utilize it across a wide range of industries, including automotive, railway vehicles, shipbuilding, aerospace, oil, metal processing, heavy industry, steel, healthcare, and education.
![[AI Implementation Case] Predicting Equipment Failures at Company B's Large Manufacturing Plant](https://image.mono.ipros.com/public/product/image/5b5/2000576641/IPROS95778497010685179229.png?w=280&h=280)
