Abstract
(1) Background: In this study on Robotic Process Automation (RPA), the feasibility of sustainable RPA implementation was investigated, considering user requirements in the context of this technology’s stakeholders, with a strong emphasis on sustainability. (2) Methods: A multi-objective mathematical model was developed and the Weighted Sum and Tchebycheff methods were used to evaluate the efficiency of the implementation. An enterprise case study was utilized for data collection, employing investigation hypotheses, questionnaires, and brainstorming sessions with company stakeholders. (3) Results: The results underscore the significance of user requirements within the RPA landscape and demonstrate that integrating these requirements into the multi-objective model enhances the implementation assessment. Practical guidelines for RPA planning and management with a sustainability focus are provided. The analysis reveals a solution that reduces initial costs by 21.10% and allows for an efficient and equitable allocation of available resources. (4) Conclusion: This study advances our understanding of the interplay between user requirements and RPA feasibility, offering viable guidelines for the sustainable implementation of this technology.

Abstract
In the context of a distributed/agile/virtual enterprise (D/A/VE) and due to the large number of potential candidate resources, it is important to make a selection of those that will give more guarantees in terms of success of this cooperation and bring better performance to D/A/VE. There are several projects of D/A/VE with different approaches to the selection process. Considering the functionalities of the resources selection model of our project, the main objective of this paper is to present the development of a prototype/demonstrator tool to support it. As result a tool, named SelecE A/VV0, was developed and providing following features: pre-selection ofresources with and without integration of the value analysis (VA), and final selection of resources. This tool supports the development of BMVEARM selection model and permits the validation of the importance of VA integration in the final performance of the resources system selected. Copyright © 2016 Inderscience Enterprises Ltd.

Abstract
A production system constrained by workers and machines, where machines are not fully staffed and workers can be transferred between machines, is here considered. Previous simulation research on this type of dual resource constrained production systems assumes that machines are fully reliable. However, this is questionable in most practical situations. Discrete event simulation is used as research method to assess the impact of machine failures on where to transfer workers. Experimentation was carried out for different levels of machine availability, worker utilization and worker assignment rules. Results show that the modified operation due date rule for worker assignment improves tardiness related performance for all production situations considered. This rule shifts between a focus on completing jobs on dune and a focus on speeding up jobs with short processing time. Results further show that ignoring the machine state at worker assignment may lead to significant performance deterioration. For a machine availability of 97% and a worker utilization of 90%, a deterioration between 101% and 416% on the percentage of tardy jobs was observed, compared to scenarios where machines are always available. However, if the machine state is considered, deterioration ranges only between 11% and 30% under the same conditions. 'This highlights the need to considered machine availability at worker assigment.

Abstract
Boarding time constitutes a critical element of turnaround time, which is used to measure the efficiency of airline operations. Therefore, to reduce boarding time, it is imperative to reconsider traditional passenger boarding strategies to make them more efficient. In this sense, this study seeks to analyze the impact of different strategies on boarding times using discrete event simulation on an Airbus 320. Seven boarding strategies have been identified and considered in our study, as follows: random, back-to-front, outside-in, reverse pyramid, blocks, Steffen, and modified optimal. The impact of carrying hand luggage and the presence of priority passengers has been considered, as well as the impact of having a continuous arrival of passengers during the boarding process versus having all passengers available at boarding time. In general, simulation results have pointed out that the outside-in and reverse pyramid strategies are the most effective, improving boarding time by up to 15%, when compared to the random strategy. Moreover, the back-to-front strategy, which is generally implemented by airline companies, has been shown to be the most inefficient strategy. Efficient boarding strategies are expected to contribute to the sustainability of air travel by minimizing the turnaround time, improving operational efficiency, and reducing emissions.

Abstract
The so-called fourth industrial revolution brought a disruptive change in the way that communication technologies, distributed systems, intelligent data management, analytics and computational capability and other technologies are integrated to enable new functions and enhance capabilities not only to production systems, but also in many other domains such as education. Mobile Health (m-Health) education is one of these, where the number of applications and tools for m-Health education is extensive. The SARS-Cov2 (Covid-19) pandemic brought to life immense challenges towards education, technology, and the symbiosis with medicine. This paper introduces 31 of the current state-of-the-art m-Health education applications and analyses the results of an an inquiry to students and junior doctors during the confinement, designed to understanding their knowledge, use and trust regarding these apps. The results show that several applications are well perceived by their users and deserved their trust and confirms a good relation between use and trust on the applications analysed. This analysis open doors to a deeper study to evaluate at which extent improving m-Health education means not only to transmit knowledge but also to developing skills and better practices.

Abstract