What we offer?
Smart Foundry implements artificial intelligence systems in three core areas:
- Smart Maintanance
- Smart Production
- Smart Quality
Smart Maintance makes it possible to avoid unplanned machine downtime due to breakdowns, wear and tear of parts by developing an artificial intelligence model with the help of which it is possible to predict the occurrence of breakdowns, when to carry out maintenance work, replacement of parts. Most machines are automated and controlled by a PLC - Programmable Logic Controller, which can record machine parameters. With the help of various artificial intelligence algorithms, it is possible to build a model that can predict in advance the wear and tear of a part or an unplanned stop, i.e. a breakdown.
Smart Production makes it possible to increase production efficiency by improving quality and reducing cycle time especially for pressure machines in HPDC - High Pressure Die Casting and LPDC - Low Pressure Die Casting processes. In order to develop a model for increasing production efficiency by reducing production cycle time, we need to build a set of production data combined with quality parameters such as leakage tests. This set also includes the times of each step, and combined with the quality of the casting, a model can be developed to reduce the machine cycle time with high 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 Maintanance/Production/Quality systems, 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.
These three areas are optimized by the systems outlined above:
- Availability - > Smart Maintanance
- Performance - > Smart Production
- Quality - > Smart Quality
By implementing these systems 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 (ERP type system).
- Access to casting quality parameters linked to the production process (casting marking)
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 (casting marking)
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.
DetailsPredictive maintanance
Requirements:
- Access to machine parameters
Predictive machine maintenance benefits by preventing unplanned machine stops. Based on the collected historical data, the model predicts when a machine failure may occur, so maintenance work, replacement of parts, etc. can be carried out in good time.
We 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.
Optimization of core production
Requirements:
- Access to process parameters via the PLC of the pressure machine
- Access to casting quality parameters linked to the production process (casting marking)
Casting core production is a process that can be optimized using artificial intelligence tools. The artificial intelligence system reduces the number of defective cores, improves product quality and the efficiency of the production process.
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.