Data mining and simulation processes as useful tools for industrial processes

The most common goal of the factory owner is to achieve better quality in the final product by means of an improved process control. The significance and relevance of optimizing the existing control models is even greater in the open-loop control systems or in those governed by computational methods dependent on adjustable parameters. This talk reviews some typical industrial environments and focuses on some parts of them in order to show the real interest of these improvements. We will identify some difficulties in obtaining these improvements and show how the optimal control model for the manufacturing process can be obtained from data provided by sensors. We will also discuss some technical problems that are related to the main goal, and will identify some topics concerning outliers, density and topology. Also, we will show how these techniques can be applied as an instrumental toolbox in addressing some environmental problems.