The introduction of the Internet of Things (IoT) in the construction industry is evolving facility maintenance (FM) towards predictive maintenance development. Predictive maintenance of building facilities requires continuously updated data on construction components to be acquired through integrated sensors. The main challenges in developing predictive maintenance tools for building facilities is IoT integration, IoT data visualization on the building 3D model and implementation of maintenance management system on the IoT and building information modeling (BIM). The current 3D building models do not fully interact with IoT building facilities data. Data integration in BIM is challenging. The research aims to integrate IoT alert systems with BIM models to monitor building facilities during the operational phase and to visualize building facilities’ conditions virtually. To provide efficient maintenance services for building facilities this research proposes an integration of a digital framework based on IoT and BIM platforms. Sensors applied in the building systems and IoT technology on a cloud platform with opensource tools and standards enable monitoring of real-time operation and detecting of different kinds of faults in case of malfunction or failure, therefore sending alerts to facility managers and operators. Proposed preventive maintenance methodology applied on a proof-of-concept heating, ventilation and air conditioning (HVAC) plant adopts open source IoT sensor networks. The results show that the integrated IoT and BIM dashboard framework and implemented building structures preventive maintenance methodology are applicable and promising. The automated system architecture of building facilities is intended to provide a reliable and practical tool for real-time data acquisition. Analysis and 3D visualization to support intelligent monitoring of the indoor condition in buildings will enable the facility managers to make faster and better decisions and to improve building facilities’ real time monitoring with fallouts on the maintenance timeliness.

Digital twins are considered the next step in IoT-based cyber–physical systems; they allow for the real-time monitoring of assets, and they provide a comprehensive understanding of a system behavior, allowing for data-driven insights and informed choices. However, no comprehensive framework exists for the development of IoT-based digital twins. Moreover, the existing frameworks do not consider the aspects introduced by the Industry 5.0 paradigm, such as sustainability, human-centricity, and resilience. This paper proposes a framework based on the one defined as the outcome of a project funded by the European Union between 2010 and 2013 called the IoT Architectural Reference Model (IoT-A or IoT-ARM), with the aim of the development and implementation of a standard IoT framework that includes digital twins. This framework establishes and implements a standardized collection of architectural instruments for modeling IoT systems in the 5.0 era, serving as a benchmark for the design and implementation of an IoT architecture focused on digital twins and enabling the sustainability, resilience, and human-centricity of the information system. Furthermore, a proof of concept of a monitoring digital twin for a vertical farming system has been developed to test the validity of the framework, and a discussion of applications in the manufacturing and service sectors is presented.

The establishment of the digital product passport is regarded to be a prominent tool to promote environmental and social sustainability, thus enabling the transition towards Industry 5.0. In this way, it represents a holistic tool for the decision-making process of several actors of a product’s value chain. However, its development is still ongoing and the absolute perspective of environmental sustainability and the social sustainability have been overlooked. The present work aims to fill these gaps and complement the literature currently available on the digital product passport with a threefold purpose. Firstly, by referring to social life cycle assessment methodologies, useful social indicators to include in the digital product passport are discussed and proposed. Secondly, the need for an absolute perspective of environmental sustainability that respects the natural limits of our planet is presented; based on the LCA methodology and the Planetary Boundaries framework, environmental attributes and environmental impact indicators with the corresponding threshold are proposed to be included in the passport and enable the so-called absolute environmental sustainability assessment of products. Finally, a framework based on a cyber-physical system for filling in the digital product passport throughout a product lifecycle is conceived. This work represents an example of how the hallmark technologies of Industry 4.0 can be used towards Industry 5.0.

With the proliferation of systems generating huge amounts of product information and the increasing number of companies involved in the production processes, the efficient management of product lifecycle is becoming a challenging issue. The problem of maintaining a coherent structure to represent and link different pieces of information is crucial for companies aiming at improving their performances by reducing the time to search for particular information.The need of developing models for such a complex information structure can be found in many works, which define semantic models and ontologies to represent and integrate information along the product lifecycle. However, some works address only specific cases, thus resulting in very detailed ontologies that model few portions of the product lifecycle and are not easily generalizable or usable, while other works define more general models, but did not provide concrete examples of applications in industrial domains.The aim of our work is to propose a reference ontology to support PLM, general enough to represent the main concepts and relationships needed to manage the whole product lifecycle. Furthermore, the PLM reference ontology can be extended and specialized to manage specific product lifecycles by adding new entities, sub-entities and relationships to its structure. An example of a real application of the development and extension of the PLM reference ontology in an industrial case is reported. The work presented in this paper is supported by the EU-FP7 project amePLM

Collaborative robots belong to the enabling technologies of Industry 4.0. They allow the set-up of semi-automatic workcells where robots and humans collaborate in the execution of complex tasks, with unprecedented flexibility if compared with standard robotic cells. This paper addresses some of the many issues that arise from introducing in the factory, not only a new workcell, but also a new working paradigm. The study considers the introduction of collaborative robots in a small production workcell. To increase the chances of success of the new cell, it proposes a method for firstly assigning tasks to human and robotics operators, based on the task characteristics and operator abilities, and then dynamically reassigning tasks to overcome disturbances or delays at the shop floor level. The justification of the method is that outages are frequent in small non-standardized productions, therefore offline optimized task assignment could be ineffective. The method is tested against an industrial case study and the results are discussed.