4 program algorithms
Production and quality
control of products
Production optimization
Each production has its own limitations, when we can effectively influence one or another result. In particular, some cases can be singled out as an example.
Predictive maintenance:
Wear parts requiring maintenance. Diverse operating scenarios are modeled, risks are predicted.
Critical studies:
The algorithm determines which events cause crashes, stops, or alerts.
Process control:
Simulation of data in which some characteristics affect others.
Real-time process monitoring:
Follows the parameters of process-critical components and proactively issues alerts when defined limit values are approached.
Modelling of energy and raw-material consumption:
Optimises the amount of energy and raw materials needed to reach targeted production volumes.
The algorithm combines process analysis data and compares with the calculated analytical data prepared in advance by specialists.
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Quality control
A separate simplified algorithm that collects all analytical information from various sources. Neural Networks build a quality system: possible errors, risks, and successful implementations. The data are compared not only within the production events, but also the applicants for the failure of the goods, the breakdown and its return by the consumers are taken into account.
Logistics, delivery of goods are also audited and are at least the main parameters for the overall assessment of the quality of the product throughout its life cycle.
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