Sustainable Industrial Processes and Efficient Energy Use

Description

This research line focuses on the development of optimization models and advanced tools for the planning and scheduling of highly energy-intensive production systems. The objective is to improve energy efficiency by explicitly integrating the energy vector into operational decision-making, considering costs, resources, and production constraints. This approach enables flexible production management, facilitating the adaptation of energy consumption and contributing both to industrial decarbonization and to the stability of the electrical system through the aggregation of flexibility among different actors.

From a development perspective, the research is oriented towards addressing the complexity arising from the simultaneous integration of production resources and energy through the design of advanced algorithms, including artificial intelligence-based techniques. Work is carried out on improving production scheduling and rescheduling under uncertainty and unforeseen events, as well as on coordination across different levels of the supply chain. In addition, tools are developed to integrate these models into real environments, supporting robust and scalable operational decision-making, with special emphasis on the structural planning of energy and infrastructure systems.

Main projects

• 2025-2028. Energy efficiency and downtime reduction system using AI and optimization techniques for industrial processes
• 2024-2027. Development of simulation models for production processes
• 2024-2027. New Artificial Intelligence-based solutions for industrial production efficiency and flexibility
• 2024-2027. Contract for the research of an algorithm for predictive maintenance task scheduling
• 2022-2025. Industrial Cluster FLEXibility platform for sustainable FACTories to reduce CO2 emissions and to enable the Energy Transition