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Development of ergonomic user interfaces for the human integration in cyber-physical systems

Publication . Cachada, Ana; Barbosa, José; Leitão, Paulo; Deusdado, Leonel; Costa, Jacinta Casimiro da; Teixeira, João Manuel; Teixeira, Carlos; Romero, Luís; Moreira, Pedro Miguel

Digitalization is transforming the worldwide economy. In such digital transformation the human integration in CPS assumes a crucial importance, complemented with some key enabling technologies like IoT, cloud computing, big data and machine learning. In this context, user interfaces are used to collect data and to monitor and control the systems, being required to use design and ergonomics guidelines, as well as user expirience, for their deployment in industrial enviroments. This paper describes the use of friendly and ergonomic user interfaces to support the human integration at operational and strategic level, aligned with the Industry 4.0 context, for an industrial metal stamping unit.

2019Conference object

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Using internet of things technologies for an efficient data collection in maintenance 4.0

Publication . Cachada, Ana; Barbosa, José; Leitão, Paulo; Alves, Americo; Alves, Leandro; Teixeira, João Manuel; Teixeira, Carlos

The digital transformation in the manufacturing world raised an additional interest in data collection and connectivity, preferably to the one performed in real time. Internet of Things (IoT) and Machine to Machine (M2M) technologies allow the collection of the huge amount of generated data in the shop ﬂoor, at the desired rates and without any human intervention. This paper describes the application of IoT technologies to create an automatic data collection solution for an industrial metal stamping unit, supporting its posterior processing, aiming to develop monitoring, prediction and optimization in an industrial intelligent and predictive maintenance system.

2019Conference object

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Maintenance 4.0: intelligent and predictive maintenance system architecture

Publication . Cachada, Ana; Barbosa, José; Leitão, Paulo; Geraldes, Carla A.S.; Deusdado, Leonel; Costa, Jacinta Casimiro da; Teixeira, Carlos; Teixeira, João Manuel; Moreira, Antonio H.J.; Moreira, Pedro Miguel; Romero, Luís

In the current manufacturing world, the role of maintenance has been receiving increasingly more attention while companies understand that maintenance, when well performed, can be a strategic factor to achieve the corporate goals. The latest trends of maintenance leans towards the predictive approach, exempliﬁed by the Prognosis and Health Management (PHM) and the Condition-based Maintenance (CBM) techniques. The implementation of such approaches demands a well structured architecture and can be boosted through the use of emergent ICT technologies, namely Internet of Things (IoT), cloud computing, advanced data analytics and augmented reality. Therefore, this paper describes the architecture of an intelligent and predictive maintenance system, aligned with Industry 4.0 principles, that considers advanced and online analysis of the collected data for the earlier detection of the occurrence of possible machine failures, and supports technicians during the maintenance interventions by providing a guided intelligent decision support.

2018Conference object

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