Digital Twin is defined as a realistic digital model of an object's physical state, representing its interaction with the environment in the real world. The research on Digital Twin has been advancing intensively in recent years. As a result of an emerging and broad research topic, various interpretations and Digital Twin applications have been developed. In this scenario, there is an opportunity to research the Digital Twin types and understand the concept evolvement. This paper provides an overview of the Digital Twin concept, classifies the existing body of literature, and discusses the Digital Twin evolution. Therefore, this research applies a combination of methods, including bibliometrics, natural language processing, and content analysis. The results show an expansion of Digital Twin's role from an enabler of cyber-physical systems to a product lifecycle data integration and processing platform.

Our aim is to analyze the changes that have taken place in the academic literature of project management induced by the growing interest in the soft side within project management, identifying concepts, trends and challenges. Based on a bibliometric approach, a systematic literature review focusing on content analysis was made in articles published from 1994 to 2015 in the ISI Web of Science and Scopus databases. The literature was found to maintain the separation between the hard and the soft side, being the soft side, for most researchers, an enabler of project performance and success. Each kind of examined skills provides different aspects of project quality and management, being the hard side clearer and more objective and the soft side more ambiguous and subjective. In the whole article, the base used 13 soft skills. The most cited among them was 'Communication', cited fifteen times, followed by 'Leadership' and 'Teamwork' cited nine times each. Despite the stronger impact of the soft skills in the project performance, the literature says that the project members, within the project team, must combine soft and hard skills towards the best performance of the projects.

A integração de tecnologias modernas de Internet e tecnologias de manufatura, o que vem se denominando de Industrie 4.0, permite a produção distribuída usando manufatura aditiva em escala global com integração de máquinas e de processos. No entanto, manufatura distribuída impõe muitos desafios quanto a padronização, ao controle de qualidade e a gestão da informação em diferentes locais de fabricação. Este artigo tem como objetivo investigar a formação de redes em projetos de manufatura distribuída, identificando seus atores e tipos de conexões ao longo do projeto. A abordagem metodológica foi de pesquisa-ação longitudinal para um projeto de manufatura distribuída com foco em manufatura flexível, sendo a fábrica central localizada na Alemanha e o sítio de produção localizado no Brasil. O design e engenharia que gerou o modelo de produto foi desenvolvido na Alemanha, enquanto que o sítio de manufatura aditiva, a infraestrutura produtiva e as máquinas são localizadas no Brasil, formando uma rede de desenvolvimento e manufatura distribuída. Os resultados permitiram identificar como é organizada a comunicação e o compartilhamento do conhecimento entre os envolvidos no projeto de manufatura distribuída, e, além disso, compreender que tipo de conhecimento é compartilhado entre os envolvidos.Palavras-have: Industrie 4.0. Manufatura distribuída. Manufatura aditiva. Rede de projetos.The integration of modern internet technology and manufacturing technology, which has been denominated Industrie 4.0, allows for distributed manufacturing using additive manufacturing on a global scale with the integration of machines and processes. However, distributed manufacturing poses many challenges for standardization, quality control and management of information in different manufacturing sites. This article aims to investigate the formation of networks in distributed manufacturing projects, identifying the stake-holders and types of connections throughout the project. The methodological approach used was longitudinal action research for a distributed manufacturing project with a focus on flexible manufacturing. The central plant was located in Germany and the supplier located in Brazil, with a partnership between the

As a result of Industry 4.0 developments, the amount of product data collected over the entire product lifecycle has been growing. Advances in digitalization resulted in the intensive use of data in the manufacturing environment. Different manufacturing systems store data across the product lifecycle-PLM (Product Lifecycle Management), ERP (Enterprise Resource Planning), and MES (Manufacturing Execution Systems), among other specialized IT systems. In many cases, there is already a connection between these systems. However, the integration between company internal manufacturing data with real-time customers' usage data is still initial. Therefore, the Internet of Things (IoT) has become an important research agenda. Information and communication technologies have been employed to digitally mirror the lifecycle of a corresponding physical product in Digital Twin (DT) applications. However, Digital Twin implementation has been focused on the beginning of life and manufacturing machines data, leaving space for developing a DT model that encompasses and connects different phases of the product lifecycle. Besides, implementing such a model in a multiplatform environmentconnecting various systemsis also an open issue. This thesis proposes the definition of a Closed-loop Digital Twin implemented as a middleware software that connects the PLM, ERP, and MES systems with customers' usage data. The proposed concept was implemented at a learning factory based on industry standard software. The implement DT processes product data to provide analysis results. This research also proposes a DT definition and typology model to support its understanding and implementation and an IoT selection model. Results demonstrated the concept potential to consolidate product data, support data analyses based on algorithms, and provide insights for different phases and stakeholders of the product lifecycle.