David Fernández Linares


The growth of energy demand and the continuous technological development of society are surpassing the environmental limits of our planet. Without adequate measures, this situation can lead to serious environmental problems that could cause irreversible damage to the environment and the well-being of humanity.
The industrial sector is the largest energy consumer, with about one-third of global energy demand, which has an evident negative relationship with environmental impact. Therefore, the challenge of mitigating climate change will imply improvements in the energy use in industry, creating great opportunities for energy savings and reducing its environmental impact.
In this sense, it is essential to obtain information derived from research and scientific analysis that allows developing solutions focused on the reduction of energy costs. This thesis has dealt with the particular needs of the production of industrial gases, by creating tools based on mathematical optimization models that allow much more agile and effective operational decision-making as well as the detection of areas for energy improvement. These tools encourage and move towards a more efficient industry that allow a more sustainable future.
Two main contributions are derived from this thesis. On the one hand, it creates a multiperiod optimization tool that allows obtaining the optimal operational configuration (from the economic and energetic points of view) of an industrial gas manufacturing process, taking into account all the variables that affect the system. On the other hand, the Data Envelopment Analysis methodology is used to compare different industrial gas production units, identifying inefficiency sources and making recommendations to adopt the best practices to solve them.
Summarizing, this thesis offers a set of practical and effective tools that support the decision making process in industrial activities and allows the identification of opportunities for energy improvement.