Knowledge extraction from different data sources, processing, classifications, grouping and providing predictions that enhance the decision-making process.
Computational methods capable of processing enormous amounts of data available in different levels of complexity, being generated in distinct velocities and ambiguities levels. These sorts of data cannot be processed by traditional methods.
Maximization or minimization of objectives (efficiency, revenue, costs...) under specific constraints (budget, laws...) based on decision variables.
A virtual copy of a real-world object or process. Detailed mathematical models that represent physical industrial processes. Digital Twins allow operators to anticipate failures and bottlenecks, generate reliable projections of scenarios, and optimize planning and operation.