Performance optimization logo

Performance optimization using neural networks

By Pablo Martin, Artelnics.

Understanding the behavior of a system enables the company to optimize its performance in order to reduce production costs and increase the production and velocity of production.

In the framework of the Industry 4.0, neural networks are capable of learning about the functioning of a system and produce a mathematical model that can prdict the peaks of production and detect potential problems beforehand. This is done by collecting data from the historical production and form different sensors of the different systems.

Data analytics can make a big difference in prolonging the life of the equipment, reducing costs of production and increase the benefits derived from the activity of the companies.


Identify the peak levels of the production and the deviations from normal production.
Analyze the factors that lead to that peak of production and the factors that make production decrease.
Predict the conditions under which the production is going to be higher.
Use the predictive model to understand how to boost production.

There are a lot of areas to which neural networks can be applied in order to improve their functioning: reduce consumption of an engine, reduce pollution or diminish noise among others.

Engine picture

Neural Designer is a neural network software that is able to take all the information that has been collected from a system and calculate a mathematical model for the optimization of its performance.

In addition, it allows to study correlations between the different variables and the production so that it can be study which are the conditions that boost production at most.

The next image shows a representation of a neural network that could be used for this case. It will take as inputs system information variables, environmental variables, historical production variables and any other variable that may be considered important for the analysis. The response of the neural network will be an estimation of the production.

Neural network

Related solutions:

> Predictive maintenance.
> Fault detection.
> Quality improvement.