Browsing by Author "Pellegri, Umberto"
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- Co-design process for upskilling the workforce in the factories of the futurePublication . Geraldes, Carla A.S.; Fernandes, Florbela P.; Sakurada, Lucas; Rasmussen, Ann Lilith; Bennyson, Rene; Pellegri, Umberto; Leitão, PauloThe digital transformation that the world is facing has a strong impact in the professional occupations and job profiles in the factories of the future context, requiring the need of upskilling and re-qualification of the workforce. Taking this into account, an Industrial Collaborative Educational Design (ICoED) is presented comprising three stages and eight steps, and considering a democratic and collaborative participation of the different stakeholders, namely the managers, educators and learners, each one providing its own perspective on the design of the training programme. In this co-design process, the analysis of the skills’ gap is a crucial task to prepare the initial stage of the process, particularly identifying the needs in terms of soft and hard skills. The proposed ICoED process was applied to solve an upskilling problem of an industrial metal stamping company, with the participants performing three workshops to execute the eight steps, reaching a training programme with five modules, each one settled with proper activities, resources and infrastructures.
- Digitization of Gauge inspection control procedurePublication . Davanzo, Giuseppe Antonio Setem; Piardi, Luis; Aikes Junior, Jorge; Leitão, Paulo; Pellegri, UmbertoGauge inspection tools are usually used for the visual and geometrical tolerances verification, using paper tutorials for guidance through the inspection steps and paper to register the results of the performed inspection. This practice may be misleading to the quality control management, not providing an effective and error-prone quality control operation. This paper proposes a cost-effective solution for supporting the realization of gauge inspection control procedures by using emergent technologies, namely Human-Machine interfaces and virtual reality, to guide more efficiently the operators during the execution of their tasks, and using Internet of Things (IoT) and cloud technologies to dynamically collect and store the inspection results. The proposed solution was deployed in an industrial production facility, with the achieved results showing its efficiency and robustness, as well as a very positive feedback from the operators. This solution also contributes for a faster and more efficient execution of inspection tests, particularly reducing the setup time required to change the product reference being inspected.
- Monitoring electrical and operational parameters of a stamping machine for failure predictionPublication . Pecora, Pedro; Garcia, Fernando Feijoo; Melo, Victória; Leitão, Paulo; Pellegri, UmbertoGiven the industrial environment, the production efficiency is the ultimate goal to achieve a high standard. Any deviation from the standard can be costly, e.g., a malfunction of a machine in an assembly line tends to have a major setback in the overall factory efficiency. The data value brought by the advent of Industry 4.0 re-shaped the way that processes and machines are managed, being possible to analyse the collected data in real-time to identify and prevent machine malfunctions. In this work, a monitoring and prediction system was developed on a cold stamping machine focusing on its electrical and operational parameters, based on the Digital Twin approach. The proposed system ranges from data collection to visualization, condition monitoring and prediction. The collected data is visualized via dashboards created to provide insights of the machine status, alongside with visual alerts related to the early detection of trends and outliers in the machine’s operation. The analysis of the current intensity is carried out aiming to predict failures and warn the maintenance team about possible future disturbances in the machine condition.