M4 Industrial Competitiveness
Efficient management is crucial for the competitiveness of the industrial sector in a global economic scenario. In particular, the optimization of processes and strategies is the area where Mathematics can provide a substantial contribution. Some of the challenges in this area are the optimal management, operation and design of energy distribution networks; finding solutions for optimal planning and operation of industrial processing plants or efficient management and redeployment of warehouses.
We will distribute these objectives in the following PIs.
PI Mathematical modeling for industry: Many processes found in the industrial sector involve complex and often dynamic phenomena. Mathematical modeling allows us to propose models that represent the most relevant phenomena involved in industrial processes. Modeling techniques combined with experimentation to achieve a better view of the process, reduce the number of sensors needed to monitor it, virtually optimize the process and evaluate its performance. In the financial sector, the large amount of market data requires the use of statistical techniques and "big data" to incorporate the data into the models and predict the evolution of the main factors of the economy and financial markets.
PI Algorithms and high-performance computing: Industrial applications lead to great complexity in their respective model equations, being their resolution a difficult task. In addition, on certain occasions, numerical simulations must be carried out in a very short time and possibly involve a large number of parameters that could be modified even when the simulation is in progress, even in real time, or they must be run on machines with low computational capabilities. In this case, special techniques and optimized programming must be applied.
PI Efficient production and management: Many of the processes in the industrial sector are susceptible to improvements in many aspects. However, the cost of their implementation and the uncertainty about the percentage of improvement make companies reluctant to make changes. The combination of modeling, simulation and optimization (often called MSO) allows companies to propose efficient solutions to improve processes and estimate the percentage of improvement obtained after implementation.