Optimization of production processes for cast iron, steel, non-ferrous metals

The proposed strategy for optimizing the manufacturing process through the use of artificial intelligence has many advantages. It is an approach that can bring significant benefits to the company, including:

  1. Increased accuracy and precision: Monitoring multiple production process parameters and linking them to casting quality parameters will allow for a better understanding of the process and the identification of potential problems in real time. This, in turn, will enable faster corrective action to be taken, resulting in improved product quality.
  2. Reduction of waste and costs: With the ability to predict casting quality based on process data, the company will be able to minimize defective products and avoid excessive consumption of raw materials. This will help reduce production costs and increase resource efficiency.
  3. Improved competitiveness: Implementing advanced technologies such as artificial intelligence can significantly increase a company's competitiveness by improving the quality, efficiency and flexibility of production. The company will be able to respond faster to market changes and meet customer demands.
  4. Business process optimization: An artificial intelligence system can also support the optimization of other business processes, such as inventory management, production planning and customer service. Integrating different systems into a single platform will enable the entire enterprise to operate more efficiently.
  5. Increased prestige: The use of cutting-edge technologies, such as artificial intelligence, can help increase a company's prestige in the eyes of customers, business partners and potential employees. Demonstrating a commitment to innovation can attract new customers and talent to the company.

Implementing an artificial intelligence system to optimize the production process can therefore bring significant benefits both operationally and strategically for the company.

Optimizing the manufacturing process involves two key tasks:

  1. Monitoring production process parameters along with casting quality parameters, e.g. leakage tests
  2. Developing an artificial intelligence model on the basis of which the quality of manufactured castings can be predicted

To make the optimization process precise, parameters from each stage of production must be monitored: molding sand parameters, melt preparation, pouring process, etc.

The more parameters are monitored, the better (more precise) the artificial intelligence model will be.

Many companies record process parameters using ERP-type systems - Enterprise Resource Planning with a dedicated production module. Building a database of process parameters linked to quality parameters we can use to build an artificial intelligence model based on machine learning algorithms and/or deep learning (neural networks).

In order for the production process parameters to be linked to casting quality parameters, it is necessary to include casting marking in the production process.

The next step will be to develop an artificial intelligence model. This is a complex process consisting of many steps, as a result of which casting quality can be predicted based on new data from the production process. The developed model should be periodically trained to improve its accuracy.

Quality-related production data and the artificial intelligence model will be packaged in a dedicated web-based system hosted in the cloud or at the customer's site

Advantages of implementing an artificial intelligence system to optimize the production process:

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