Estudio, análisis y desarrollo de estrategias de mantenimiento en maquinaria y sistemas industriales. Evaluación de riesgos, fiabilidad y disponibilidad

Resumen

The development and implementation of multistage machines (MTSM) in the industrial environment is an increasingly present reality in the market. In order to meet the production objectives, it is necessary to establish the appropriate maintenance strategy. In multi-stage machines, the maintenance strategy is based on the control of the state of the components, since, if a component of a stage fails, this fail will cause the stoppage of whole the machine, with the loss of the manufacturing in progress. The object of this thesis is the developing preventive and predictive maintenance strategies for this type of machines, based on an experimental test with an industrial Multistage Thermoforming Machine. In the first work, Corrective Maintenance (CM) Preventive Programmed (PPM) Improved Preventive Programmed (IPPM) are defined and only preventives are studied. The comparative results between both preventive strategies indicates improvements in availability and efficiency. Also, is defined and studied a Predictive strategy (PdM) based on the distribution of sensors throughout the machine and algorithms that work with their values constantly. With the same distribution of sensors, two algorithms are proposed, Algorithm Life Optimization (ALOP) and Digital Behaviour Twin (DBT) The results show that both strategies allow to detect possible failures in components before a final unexpected failure. In a second work, preventive maintenance strategies are further explored, determining a Global Operating Condition (GOC) for each component, together with the establishment of two performance indicators (KPI) for each component. This study proposes a matrix to adoptthe adequate preventive maintenance strategy for each component.