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The reduction of the space available for students in the classrooms of teaching laboratories, due to the pandemic caused by the SARS-CoV-2, requires the provision of the laboratories with additional equipment, as well as the application of procedures or protocols that guarantee that all students receive practical education with levels of quality similar to those existing in face-to-face classes, prior to the arrival of the coronavirus. This paper describes the methodology and resources used to teach practical classes in one of the Electrical Engineering teaching laboratories, at the Polytechnic University of Valencia. The use of web cameras, complemented with the use of the Microsoft Teams platform, has allowed all students actively attend laboratory classes in real time, within the established schedule, some in person and others in online mode.

The essential aim of Industry 4.0 is to enable industries to be more productive, efficient, and flexible. A predictive maintenance strategy can make a positive contribution to all these things, as it uses industrial IoT technologies to monitor asset health, optimise maintenance schedules, provide real-time alerts about operational risks, and maximise uptime, and can provide digital services to customers based on data from its machines. It improves productivity, improves customer satisfaction, and therefore gives the company a competitive advantage. Nevertheless, decision making in relation to a predictive maintenance strategy is not systematised, and this may lead to some inappropriate decisions, which do not achieve the goal sought. This chapter describes a multicriteria model, designed with the analytic hierarchy process, to systematise decision making with respect to a predictive maintenance strategy.

Condition-based maintenance (CBM) may be considered an essential part of the Industry 4.0 environment because it can improve production processes through the use of the latest digital technologies, which allows improvements to products, processes, and business models. Nonetheless, despite this importance, there are no models or methodologies in the literature to assist in choosing predictive techniques and the level of complexity to be used in a given organization. This chapter describes a model for choosing the most suitable CBM technique to be introduced in a subsidiary of a petrochemical plant. The predictive techniques of vibration analysis, lubricant analysis, and a combination of the two were considered at three technological levels. The model was built using the measuring attractiveness by a categorical based evaluation technique (MACBETH) approach. The present model could avoid failures in these programmes when making decisions about the techniques and technologies most suited to the characteristics of the industrial plant.

Resumen En este artículo se muestra el nivel estratégico que, para las empresas con activos físicos, supone una adecuada gestión del conocimiento en la ingeniería del mantenimiento industrial. Por las peculiaridades propias que se dan normalmente en este tipo de actividad fundamental de la empresa, el conocimiento de los operarios y técnicos que operan en las áreas de mantenimiento está fuertemente basado en su experiencia (fuerte componente tácito), difícil de medir y articular, y sin embargo, en numerosas ocasiones, esta rotura de la información-conocimiento, puede suponer un alto coste para la empresa, muchas veces asumido como algo que afrontar, debido al incremento de tiempos de parada de producción y servicios, perdidas de eficiencia energética, o tiempo de acoplamiento de nuevo personal a estas áreas. Este artículo muestra una reseña sobre dos libros de investigación que tratan sobre este tema, publicados tras una investigación de campo aplicada en empresas industriales reales europeas, que marcan las consecuencias de disponer el conocimiento en islas, así como las mejoras medidas cuando se produce una adecuada gestión del conocimiento.Abstract This article demonstrates the strategic level involving management of knowledge in industrial maintenance engineering for businesses with physical assets. The peculiarities that occur normally in this type of basic activity of the company, knowledge of operators and technicians working in the areas of maintenance is strongly based on your experience (strong tacit component), difficult to measure and articulate, however, on numerous occasions, this break of information-knowledge, can signify a high cost for the companies taken as something to deal with, due to the increase of downtimes of production and services, loss of efficiency, fracarc1@csa.upv.es