Abstract
5G has become increasingly popular nowadays, mainly due to its characteristics which enable high data rates and low latency. At the same time, mobile robotic platforms, such as drones and robots, appeared as suitable platforms to carry radio stations, enabling the on-demand placement of 5G communications cells. The main contribution of this paper is an obstacle-aware on-demand 5G network. The proposed solution consists of a 5G radio station (gNB) carried by a mobile robotic platform capable of providing obstacle-aware wireless connectivity to 5G User Equipments (UEs), leveraged by a novel virtual network function - On-Demand Mobility Management Function (ODMMF). ODMMF is designed to integrate the 5G Core network and it allows to monitor the radio conditions provided to the served UEs, while enabling the positioning of the mobile robotic platform remotely by taking advantage of the visual information provided by on-board video cameras. The proposed solution was validated using an experimental prototype, under a representative networking scenario.

Abstract
The need of lockdown, due to COVID-19, led many manufacturing companies to accelerate the adoption of digital technologies. Manufacturing companies were strongly affected by workforce shortages associated with the spread of COVID-19 and the lockdown, as well by connectivity losses among business partners. Therefore, these companies are reviewing their strategies to increase productivity, mainly embracing digital manufacturing technologies. Here the adoption of digital technologies aims to improve efficiency and flexibility in their processes, also improving connectivity among business partners. This study investigates how collaborative academia-industry R&D cases accelerated the adoption of digital technologies by manufacturing companies, given the current COVID-19 pandemic situation. Based on multiple case studies, this article reports the challenges and the strategies of three ongoing collaborative industry-academia R&D projects developed during the COVID pandemic situation. The results are presented in four different perspectives derived from industry 4.0 readiness maturity models: interpersonal communication, personal competencies and skills, systems integration, and technological strategy. It highlights the importance of manufacturing companies to have a well-designed digitalization strategy, need of continuous training and development of their workforce, and the support of Research & Technology Organizations (RTO) to bring more maturity to the efforts required during a turbulent situation. The results of this paper can provide relevant decision support for manufacturing companies, and its stakeholders, in face of challenges of the actual pandemic and post-pandemic scenario.

Abstract
Today, manufacturing is moving towards customer-driven and knowledge-based proactive production. Shorter product life cycles lead to increased complexity in areas such as product and process design, factory deployment and production operations. To handle this complexity, new knowledge-based methods and technologies are needed to model, simulate, optimize and monitor manufacturing systems. Product lifecycle management research tends to focus on situations that are responsive to formal analysis and modelling. However, in several domains such as knowledge intensive collaborative environments, it's not possible to model processes using formal notations. Knowledge based and collaborative process management involves a combination of structured and non-structured processes. Structured processes management can be reduced to a set of fully-defined rules leading to high efficiency but also low flexibility, whereas the management of non-structured processes is not prone to a full formalization. A combination of both structured and unstructured management approaches is required in order to achieve a successful trade-off between efficiency, flexibility and controllability. We call a process as semi-structured when it contains both structured and non-structured sub-processes leading to a flexible and efficient hybrid approach. Large enterprise information systems, impose structured and predictable workflows, while knowledge based collaborative processes are unpredictable to some extent, involving high amount of human-decision. Moreover, large enterprise information systems are not able to manage the daily ad hoc communication inherent to the knowledge-based process itself. This paper introduces a set of concepts, methods and tools of an innovative Hybrid Process Management approach validated by a real world business case in the automotive industry.

Abstract
The focus of this paper is to elaborate collaborative business process monitoring within virtual factory (VF) environment in a smarter way. This process monitoring is tracked through visualisation over a user interface such as 'dashboard'. This research briefly provides all aspects of implementing process monitoring through the dashboard user interface and explains technical aspects of monitoring. The dashboard features state-of-the art business intelligence and provides data visualisation, user interfaces and means to support VF partners to execute collaborative processes. With advanced visualisations that produce quality graphics it offers a variety of information visualisations that brings the process data to life with clarity. This data visualisation provides critical operational matrices (e.g. KPIs) required to manage virtual factories. Key reporting outputs such as KPIs and day-to-day operational data can be used to monitor and empower partners' processes that help to drive collaborative decisions e VF broker or partners' also retain full flexibility to create, deploy and maintain their own dashboards using an easy to understand wizard-driven widget and an extensive array of data visualisation components such as gauges, charts, maps, etc. Various technical aspects of this dashboard user interface portal are elaborated within the scope of this research such as installation instructions, technical requirements for the users and developers, execution and usage aspects, limitations and future works. In addition to the dashboard user interface portal this research also investigates the VF life cycle and provides architectural framework for VF. The research work highlighted in this paper is conceptualised, developed, and validated within the scope of the European Commission NMP priority of the Seventh RTD Framework Programme for the ADVENTURE (ADaptive Virtual ENterprise ManufacTURing Environment) project.

Abstract
This paper presents a framework to support the full life-cycle of extended manufacturing enterprises, from creation to operation and dissolution phases. The deployment and operation of such enterprises can be compared with the concept of 'plug-and-play', as the internal processes and legacy systems of the companies involved are smoothly integrated within an overall business process designed, validated and executed according to a specific business opportunity. During the plug phase, the specific business requirements are elicited and integrated with the design of the extended business processes. On the other hand, in the play phase, those predefined processes are executed in order to run the extended enterprise successfully. The paper describes an application case regarding an engineer-to-order and one-of-a-kind engineering product. This scenario is common to a large number of technology-driven SMEs, and illustrates the value of the framework to exploit business opportunities that require a combination of skills and resources that do not exist in-house. The case shows how the platform addresses the two main challenges in the deployment of an extended enterprise. The first challenge is finding the right set of partners to address a new business opportunity and the design of the underlying collaborative processes. The second challenge is mostly technical, and focuses on the integration of the legacy systems of the partners participating in the network so that cooperation can take place quickly and seamlessly.