2021
Authors
Simoes, A; Ferreira, F; Castro, H; Senna, P; Silva, D; Dalmarco, G;
Publication
2021 IEEE 19TH INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN)
Abstract
The need of lockdown, due to COVID-19, led many manufacturing companies to accelerate the adoption of digital technologies. Manufacturing companies were strongly affected by workforce shortages associated with the spread of COVID-19 and the lockdown, as well by connectivity losses among business partners. Therefore, these companies are reviewing their strategies to increase productivity, mainly embracing digital manufacturing technologies. Here the adoption of digital technologies aims to improve efficiency and flexibility in their processes, also improving connectivity among business partners. This study investigates how collaborative academia-industry R&D cases accelerated the adoption of digital technologies by manufacturing companies, given the current COVID-19 pandemic situation. Based on multiple case studies, this article reports the challenges and the strategies of three ongoing collaborative industry-academia R&D projects developed during the COVID pandemic situation. The results are presented in four different perspectives derived from industry 4.0 readiness maturity models: interpersonal communication, personal competencies and skills, systems integration, and technological strategy. It highlights the importance of manufacturing companies to have a well-designed digitalization strategy, need of continuous training and development of their workforce, and the support of Research & Technology Organizations (RTO) to bring more maturity to the efforts required during a turbulent situation. The results of this paper can provide relevant decision support for manufacturing companies, and its stakeholders, in face of challenges of the actual pandemic and post-pandemic scenario.
2022
Authors
Maia, D; Coelho, A; Ricardo, M;
Publication
2022 18TH INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS (WIMOB)
Abstract
5G has become increasingly popular nowadays, mainly due to its characteristics which enable high data rates and low latency. At the same time, mobile robotic platforms, such as drones and robots, appeared as suitable platforms to carry radio stations, enabling the on-demand placement of 5G communications cells. The main contribution of this paper is an obstacle-aware on-demand 5G network. The proposed solution consists of a 5G radio station (gNB) carried by a mobile robotic platform capable of providing obstacle-aware wireless connectivity to 5G User Equipments (UEs), leveraged by a novel virtual network function - On-Demand Mobility Management Function (ODMMF). ODMMF is designed to integrate the 5G Core network and it allows to monitor the radio conditions provided to the served UEs, while enabling the positioning of the mobile robotic platform remotely by taking advantage of the visual information provided by on-board video cameras. The proposed solution was validated using an experimental prototype, under a representative networking scenario.
2012
Authors
Shamsuzzoha, A; Ferreira, F; Faria, J; Azevedo, A; Hao, Y; Helo, P;
Publication
2012 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM)
Abstract
The reality in today's business is to compete with dynamic and shorter market opportunities. In order to cope up with such environment, manufacturing firms, especially small and medium size enterprises (SMEs) are needed to collaborate with each other for mutual benefits. This collaboration offers process enhancement within the environment of virtual enterprise (VE) and contributes towards sharing costly resources and valuable knowledge among manufacturing companies. This research is basically focused on the process collaboration among companies that motivates them achieving identified business opportunities. A collaboration framework is proposed in this paper with respect to VE process mapping. Visualization of such processes is also highlighted though 'Dashboard' user interfaces in order to monitor and control a successful VE.
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