Abstract
Objective: A systematic literature review was conducted to identify relevant ergonomic and safety factors for designing collaborative workspaces in industrial settings. Background: The growing use of smart and collaborative robots in manufacturing brings some challenges for the human-robot interaction design. Human-centered manufacturing solutions will improve physical and mental well-being, performance, productivity and sustainability. Method: A systematic review of the literature was performed based on the protocol of Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Results: After a search in the databases Scopus and Web of Science, applying inclusion and exclusion criteria, 33 publications in the English language, published between the years 2010 and 2020, remained in the final analysis. Publications were categorized in cognitive ergonomic factors (13), safety factors (10), physical ergonomic factors (6) and organizational ergonomic factors (4). The analysis of results reinforced that to optimize the design of collaborative workstations it is imperative to have a holistic perspective of collaboration, integrating multiple key factors from areas such as engineering, ergonomics, safety, sociology and psychological as well as manufacturing efficiency and productivity. Application: Considering the advantages of the use of cobots in manufacturing, the results of this review will be useful to support companies in implementing human-robot collaboration. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Technological breakthroughs, such as the Internet of Things, Big Data repositories, artificial intelligence or additive manufacturing, are triggering a Fourth Industrial Revolution. This new revolution, also known as Industry 4.0, is characterized by the combination of physical and digital worlds in digital ecosystems that connect the different members in the value chain from clients to suppliers and distributors. Companies are redefining their strategies based on this new paradigm to obtain a competitive advantage. They aim to achieve more efficient and flexible productive processes that can produce high-quality products at low costs, investing on mass customization to satisfy their clients. Accordingly, governments are implementing support programs that create a suitable environment for the adoption of technological innovation strategies by the companies. Although some programs may diverge in some objectives, they all aim to promote workers' skills adaptation, technological supply development, and business modernization. The Portuguese Government also released its program for Industry 4.0 support, known as Portugal i4.0, which is intended to stimulate Portuguese economy digitalization. Furthermore, in latest years, it has been supporting projects through European funds mobilizations from Portugal 2020 program. The present study analyses whether companies that received financial support from Portuguese government to implement innovative projects, within the Industry 4.0 paradigm, were able to improve economic and financial performance and competitivity gains. For such purpose, it was applied an inference statistical method to analyse the differences verified in economics and financial indicators between the periods before and after projects implementation in a selected group of companies.

Abstract
Technological evolution has continuously driven the development of industries and consequently of society. The fourth industrial revolution consists in the combination of a set of physical and digital technologies that has been changing systems' operations within industries. The pharmaceutical industry has a considerable impact on well-being and has been strongly challenged with this new reality, not only by those that are transversal to all industries but also due to the fact that it is a highly regulated sector, which creates additional barriers for industry 4.0 (I4.0) initiative's implementation. However, it is due to the fact that this revolution provides high growth opportunities to the industry, and consequently for the improvement of population's quality of life, that this topic has been subject to so much research at a global level. This study's main purpose is to understand the impact of I4.0 paradigm implementation in the pharmaceutical industry (mainly in the production area), to analyze the technological readiness of Portuguese pharmaceutical companies to implement I4.0 technologies and to understand the role of the I4.0 paradigm to fight the pandemic situation caused by the COVID-19. To achieve this purpose, an exploratory multiple-case study based on semi-structured interviews was conducted in two Portuguese pharmaceutical companies. It is expected that the results of this work lead to recommendations that help the Portuguese pharmaceutical industry to be better prepared to face the challenges that are coming with this revolution.

Abstract
In the pursuit of increasing efficiency, productivity and flexibility at production lines and their corresponding workstations, manufacturing companies have started to heavily invest in "collaborative workspaces" where close interaction between humans and robots promises to lead to these goals that neither can achieve on their own. Therefore, it is necessary to know the contributions, recommendations and guidelines that literature presents in terms of designing a manufacturing workplace where humans and cobots interact with each other to accomplish the defined objectives. These aspects need to be explored in an integrated and multidisciplinary way to maximize human involvement in the decision chain and to promote wellbeing and quality of work. This paper presents a systematic literature review on designing human-robot collaboration (HRC) workspaces for humans and robots in industrial settings. The study involved 252 articles in international journals and conferences proceedings published till 2019. A detailed selection process led to including 65 articles to further analysis. A framework that represents the complexity levels of the influencing factors presented in human-robot interaction (HRI) contexts was developed for the content analysis. Based on this framework the guidelines and recommendations of the analysed articles are presented in three categories: Category 1 - the first level of complexity, which considers only one specific influencing factor in the HRI. This category was split into two: human operator, and technology; Category 2 - the second level of complexity, includes recommendations and guidelines related to human-robot team's performance, and thus several influencing factors are present in the HRI; and, finally, Category 3 - the third level of complexity, where recommendations and guidelines for more complex and holistic approaches in the HRI are presented. The literature offers contributions from several knowledge areas capable to design safe, ergonomic, sustainable, and healthy human-centred workplaces where not only technical but also social and psychophysical aspects of collaboration are considered.

Abstract
Recently there has been an increasing demand for technologies (automated and intelligent machines) that brings benefits to organizations and society. Similar to the widespread use of personal computers in the past, today's needs are towards facilitating human-machine technology appropriation, especially in highly risky and regulated industries like robotics, manufacturing, automation, military, finance, or healthcare. In this context, trust can be used as a critical element to instruct how human-machine interaction should occur. Considering the context-dependency and multidimensional trust, this study seeks to find a way to measure the effects of perceived trust in a collaborative robot (cobot), regardless of its literal credibility as a real person. This article aims at translating, adapting, and validating a Human-Computer Trust Scale (HCTM) in human-robot interaction (HRI) context and its application to cobots. The Human-Robot Interaction Trust Scale (HRITS) involved 239 participants and included eleven items. The 2nd order CFA with a general factor called trust have proven to be empirically robust (CFI=.94; TLI=.93; SRMR=.04; and RMSEA=.05) [CR=.84; AVE=.58, and MaxRH=.92]; results indicated a good measurement of the general factor trust, and the model satisfied the criteria for measure trust. An analysis of the differences in perceptions of trust by gender was conducted using a t-test. This analysis showed that statistical differences by gender exist (p=.04). This study's results allowed for a better understanding of trust in HRI, specifically regarding cobots. The validation of a Portuguese scale for trust assessment in HRI can give a valuable contribution to designing collaborative environments between humans and robots.

Abstract
Collaborative robots are being increasingly used by manufacturing companies due to their potential to help companies cope with market volatility. Before introducing this technology, companies face the decision phase where they determine the investment feasibility. Decision models for cobot adoption can assist decision-makers in this task, but they require previous identification of decision criteria. Since existing literature overlooked this issue, this study aims to provide a list of decision criteria that can be considered in the cobot adoption decision process. These criteria were identified by a literature review of the benefits, advantages, and disadvantages of cobot adoption. Results show that flexibility, competitiveness, ergonomics, quality, safety, space, mobility, ease of programming, technical features, human-robot collaboration, and productivity are important aspects to consider when deciding whether to invest in cobots. The findings of this study provide a better understanding of the decision process for cobot adoption by listing decision criteria along with some indicators, which is an important input for the design of a decision-making process.