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- Data Science for Industry 4.0 and Sustainability: A Survey and Analysis Based on Open DataPublication . Castro, Helio; Costa, Filipe; Ferreira, Tânia; Ávila, Paulo; Cruz-Cunha, Manuela; Ferreira, Luís; Putnik, Goran D.; Bastos, JoãoIn the last few years, the industrial, scientific, and technological fields have been subject to a revolutionary process of digitalization and automation called Industry 4.0. Its implementation has been successful mainly in the economic field of sustainability, while the environmental field has been gaining more attention from researchers recently. However, the social scope of Industry 4.0 is still somewhat neglected by researchers and organizations. This research aimed to study Industry 4.0 and sustainability themes using data science, by incorporating open data and open-source tools to achieve sustainable Industry 4.0. To that end, a quantitative analysis based on open data was developed using open-source software in order to study Industry 4.0 and sustainability trends. The main results show that manufacturing is a relevant value-added activity in the worldwide economy; that, foreseeing the importance of Industry 4.0, countries in America, Asia, Europe, and Oceania are incorporating technological principles of Industry 4.0 in their cities, creating so-called smart cities; and that the industries that invest most in technology are computers and electronics, pharmaceuticals, transport equipment, and IT (information technology) services. Furthermore, the G7 countries have a prevalent positive trend for the migration of technological and social skills toward sustainability, as it relates to the social pillar, and to Industry 4.0. Finally, on the global scale, a positive correlation between data openness and happiness was found.
- Literature review of decision models for the sustainable implementation of Robotic Process AutomationPublication . Patrício, Leonel; Ávila, Paulo; Varela, Leonilde; Cruz-Cunha, Maria Manuela; Pinto Ferreira, Luís; Bastos, João; Castro, Helio; Silva, JoséRobotic Process Automation (RPA) is a rules-based system for automating business processes by software bots that mimic human interactions to relieve employees from tedious work. It was verified in the literature that there are few works related to RPA decision support models. This technology is in great growth and, therefore, it becomes important to study the evaluation of the implementation of RPA. The objective of this work is focused on a literature review for the identification and analysis of Robotic Process Automation implementation models. This work analyses some models or studies available in the literature and, in addition, analyses it from a perspective relating to the Triple Bottom Line (TBL) related to environmental, social and economic effects. Regarding the results obtained, it appears that there is still a lot of room to improve research in this field, for example, with regard to the development of an evaluation model for the implementation of the RPA, taking into account the TBL of the sustainability concept.