In the steel industry, the development of new production methods is potentially very costly. Thanks to Savantic’s simulation models, a number of heavy industry companies have been able to shorten the times required for testing new methods and saving vast amounts of money on development and materials costs, in a production environment that is becoming more and more digital. Optimisations and digital twins are some of the solutions we have delivered to our industry customers.
In order to optimise productivity and quality, AGA needed a model for simulating what is going on inside the large furnaces used for instance within the steel industry.
The conditions in the furnaces are dynamic; many parameters influence the final result. The code controlling the furnaces was not flexible enough and some customers experienced elements of chance in the way the furnaces worked.
We first built a model for simulating what was going on inside the furnaces, and only then could we improve the code. This led to better energy efficiency and higher quality.
Read more about our AGA project here.
Savantic have built a simulator for operator training at Uddeholm. It is a digital twin of the actual operator’s pulpit, offering the same experience as being in the actual working situation.
Thanks to the simulator, Uddeholm now saves large amounts of time and material waste during the training period, and the simulator also offers the opportunity for many more to try working as an operator, which facilitates work rotation and career development.
Our competence in this area is part of a number of solutions for digital vehicles – we know sensor technology, cameras, data fusion and algorithms for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD).
We also develop algorithms for route planning and vehicle fleet optimisation, based on real-time traffic data.
Savantic were commisssioned by SL to investigate trespassing alarms, which has led to giving Trafikförvaltningen a better view of the safety conditions around the Metro tracks. This, in turn, has led to the County Council deciding on introducing platform doors in the Stockholm Metro.
We develop solutions for automatic or computer-assisted diagnostics, based on images or other medical information. We do that by using sensors and hardware-related applications, in addition to standard image analysis methods, modern deep learning methods, or a combination of the two.
We also build solutions for optimising health care workflows – where we contribute with our extensive experience in data analysis, scheduling and data driven algorithm development.
Savantic have been working together with Elekta in developing and improving Gamma knives for radio surgery. The project was a joint research effort between Savantic and Elekta. Savantic helped to introduce Monte-Carlo simulations as a tool of simulating radiation fields.
For Scibase, Savantic developed a classifier of measurements of the impedance of human skin. This is used for determining if a mole is benign or a malign. The classifier consists of several algorithms, of which some has become patents.
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