Abstract
This paper describes an <> system to support decision making in the planning processes of Virtual Enterprises, viewed as networks of different units, namely plants, logistic centres and storage facilities. The system aims at improving customer due date calculation, and is intended to be a multi-site planning tool to co-ordinate local activities across the Virtual Enterprise network. It is based on the use of aggregate information and on a set of local rough capacity models. This work is part of a broader project with a particular focus on the microelectronics industry. Companies of this industry are a good example of Virtual Enterprises, where a quick response to the customers needs and to unpredictable changes in production conditions is considered a major factor for success.

Abstract

Abstract
In 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.

Abstract

Abstract
The emergence of the COVID-19 pandemic required swift adaptations within public spaces, particularly in view of the uncertainties enveloping the transmission dynamics of the virus. Among the prominently contacted surfaces, door handles have garnered significant attention in research efforts aiming to curtail transmission risks. A notable proposition emerged to obviate the necessity of direct physical contact with handles, thereby introducing a novel approach. Thus, the manufacturing modality of three-dimensional (3D) printing was naturally embraced, primarily attributable to its expeditious prototyping capabilities. Although the extant literature and the open-source community have proffered diverse panaceas, this inquiry embarked on rectifying certain inadequacies that had afflicted antecedent methodologies. Elaborate exposition is provided pertaining to the progression of the developmental trajectory and the concomitant design refinements. In a bid to substantiate the efficaciousness of the produced solution, the finite element analysis (FEA) was judiciously employed to assess two distinct loading scenarios: during the installation phase and the subsequent operation of the contrivance. The empirical findings manifest the commendable load tolerance, with the proposed solution being capable of withstand forces exceeding 15 N. Furthermore, even under the most adverse circumstances, the device evinced a maximal displacement of 15 mm. Collectively, the corollaries borne out of this scholarly investigation corroborate the efficacy, utilitarian functionality, and ergonomic viabilities of the proposed solutions and manufacturing process. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Abstract
Robotic 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.