Diagnóstico, simulación y optimización de procesos

To be familiar with the particular factors that affect the production process and the finished product’s properties, making it possible to make decisions in advance.

To efficiently manage all the data and information related to the production process and the product. This is complex due to the variety and quantity. The product is subjected to many unitary processes, and in these, there are different factors that affect the final result.

The key to commercialising products is to understand how they work, anticipate future scenarios when surrounding conditions change, and make early decisions that improve outcomes.

At AINIA we give you value



  • Simulation of hypothetical production scenarios without line stoppage

  • Diagnostics and predictions on process or product behaviour

  • Simulating the effect that line configurations and production parameters may have on product characteristics

  • Data interpretation and information on process and product


Process diagnosis, prediction, simulation and optimisation

We develop customised solutions that allow a better understanding of the production process, simulate possible scenarios and predict events that could happen…

We use Augmented Reality to incorporate data and its analysis close to the point of generation, which contributes to informed decision making.

In the field of Virtual Reality in the food sector, we develop scenarios in which we represent the devices that correspond to the manufacturing plants, as well as 3D models that represent the food properties according to the process information that is available at that moment along the line.

In addition, we are working on developing simulation models in industrial environments (digital twins). We can reproduce and predict the behaviour of a product or matrix, a line or an industrial plant from the massive data analysis of its behaviour. We create virtual processing plants that represent reality and allow the connection of components that represent real equipment. We also address the product or food matrix, so that we can simulate the changing state throughout the processes.

We manage all the collected information and integrate Machine Learning techniques that enable us to make all kinds of diagnoses and predictions about process or product behaviour through predictive multivariate analysis in the context of process statistical analysis.

How can I help you?

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Juan Pablo Lazaro
Information and Communication Technologies

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