What we offer?
Smart Foundry implements artificial intelligence systems for foundry industry:
- Smart Quality
Smart Quality makes it possible to optimize casting quality by developing an artificial intelligence system based on machine learning or deep learning algorithms (neural networks). In order to develop such a model, it is necessary to monitor the production process and monitor the quality parameters of the casting, for example, through leakage tests. It is necessary to integrate a casting marking system into the production line in order to link quality with process parameters. The developed model should be periodically retrained as new production data is provided. The model developed in this way will be packaged in a dedicated web-based system meeting all security standards provided in the cloud or deployed at the customer's site.
By implementing Smart Quality system, KPIs - Key Performance Indicators - can be actively optimized using artificial intelligence. One of the main indicators in the production process is OEE - Overall Equipment Effectiveness.
OEE = Availability * Performance * Quality.
- Availability
- Performance
- Quality
By implementing SMART QUALITY into the production process, we can actively optimize metrics including OEE, rather than just monitoring them.
Optimization of production processes for cast iron, steel, non-ferrous metals
Requirements:
- Access to production parameters of the process
- Access to casting quality parameters linked to the production process
Having a set of production parameters linked to product quality can optimize the production process by using machine learning and/or deep learning algorithms. Optimizing the process will reduce scrap, improve casting quality and increase production efficiency. Optimizing production processes increases a company's competitiveness and generates higher profits.
DetailsHPDC, LPDC process optimization
Requirements:
- Access to process parameters via the PLC of the pressure machine
- Access to casting quality parameters linked to the production process
Once production process parameters can be linked to casting quality, process optimization can be applied by using machine learning and/or deep learning algorithms. Optimization of product quality in pressure processes brings very large savings in the form of higher product quality, fewer defective castings, which directly translates into energy savings, time savings, which affects productivity and competitiveness of the company.
DetailsWe develop strategies for implementing artificial intelligence in the company in various areas
First, we audit the company and look for possible areas where artificial intelligence can be implemented for decision support. The next step is to develop a report and present an offer to the partner. Then we agree with the partner on the terms of cooperation and the areas where we will implement artificial intelligence systems
Reduction of cycle time in HPDC, LPDC processes while maintaining high product quality
Reducing cycle time while maintaining high casting quality in HPDC and LPDC processes enables increased production efficiency by making castings in less time so more can be made.
Creation of new materials with specific properties
Based on the customer's results (chemical composition of the alloy, parameters of the modification process, heat treatment parameters, mechanical properties, electrical properties, etc.), we create a dedicated solution for creating new materials with very specific properties expected by the customer.
Other areas where artificial intelligence can be applied
The areas of implementation of artificial intelligence systems listed above are not exhaustive. We develop dedicated solutions at the client's request.