
My main research lines focus on the development of Digital Twins in the context of Industry4.0. In particular, I am working on the design of strategies and tools to monitor relevant process/product variables (for instance food quality indicators) and to control and optimize industrial processes, mainly from the food and biotechnological industries.
Mathematical modeling
Mathematical modeling is central in my research lines. The main objective is to derive sets of mathematical equations that describe the evolution of the processes considered. We consider three approaches:
– Mechanistic models derived from fundamental laws (property balances) that are useful to understand the process and to represent all possible scenarios.
– Data-driven models, that are particularly useful when the processes are too complex and a mechanistic model is either difficult to obtain or computationally involved.
– Reduced order models that provide good approximations of the behavior of the process with low computational load.

We combine measurements provided by hardware sensors with mathematical models to develop software sensors able to monitor, in a non invasive way, such relevant process variables.

– Derive and implement advanced control techniques able to drive the plant/process to the desired operating point.
– Compute the best operating conditions (in terms of product quality, resources waste, production time, etc.) of the plant.

– Thermal sterilization of canned food
– Quality deterioration of fresh fish along the food chain
– Modified Atmosphere Packaging of food to increase shelf life
