Últimos artículos

“Hemos renovado nuestra misión y visión, pero mantenemos inalterados nuestros valores”

En este trabajo se analizan las posibles vías de gestión de los residuos ganaderos, en particular residuos de granjas porcinas.

La implementación de un programa de mejoras en el tratamiento del agua de un ciclo de agua vapor de una industria papelera ubicada en el sur de Francia, derivadas de una exhaustiva asesoría técnica, permitió corregir las tendencias observadas en el sistema, claramente afectado por fenómenos de corrosión acelerada por flujo (FAC).

Entendiendo por valorización primaria de emisiones aquella que obtiene un aprovechamiento directo, in situ y sin variar la naturaleza de las mismas, se verifica el análisis en particular del estado del arte para las de SO2 y NOx de centrales térmicas.

Se realiza un repaso de las diferentes fuentes de contaminación atmosférica y de cómo tal contaminación puede incidir sobre suelos y/o plantas. Se muestra un caso práctico de investigación en este campo, y de cómo el suelo puede comportarse como un ente depurador de la contaminación atmosférica.

Since we began manufacturing industrial boilers of thermal oil at INNERGY 50 years ago, this thermal fluid has not stopped evolving and specializing, offering users considerable advantages in its different applications, compared to other heat transfer media. These improvements not only affect the technical and operational part, but also the economic and profitability of the plant.

The new biorefinery concept, which provides the framework of this project, marks a clear step forward in that it overcomes problems arising from the generation of residues by giving them new value. Valor Plus project´s aim is to develop an integrated closed loop biorefineries, minimizing waste and generating added value products.

This article reflects on the tools designed to ensure safety in industrial facilities, with the aim of reducing the likelihood of accidents and achieving the safety of people and the environment, as well as meeting the production and profitability requirements of their investments.

The recent and remarkable use of Artificial Intelligence (AI) techniques, and particularly, of data mining, allows the improvement of industrial processes through pattern analysis. These tools become very useful when considering condition-based maintenance (CBM) processes, where it is necessary to detect the inflection point in normal operation conditions. In this paper, a novel methodology for CBM is proposed, consisting of 3 data mining techniques: Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Random Forests (RF). Initial analysis of the experiment outcomes suggests that it is recommended to continue the researching efforts in this field because of the improvement obtained in predictive maintenance.

An Asset Health Index (AHI) is a tool that processes data about asset’s condition. That index is intended to explore if alterations can be generated in the health of the asset along its life cycle. These data can be obtained during the asset’s operation, but they can also come from other information sources such as geographical information systems, supplier’s reliability records, relevant external agent´s records, etc. The tool (AHI) provides an objective point of view in order to justify, for instance, the extension of an asset useful life, or in order to identify which assets from a fleet are candidates for an early replacement as a consequence of a premature aging.