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.

While it is essential to increase agricultural production to meet the needs of a growing global population, this task is becoming increasingly difficult due to the environmental challenges faced in recent decades. A promising solution to enhance the efficiency and sustainability of agricultural production is the integration of Industry 4.0 technologies, such as IoT, UAVs, AI, and Blockchain. However, despite their potential, there is a lack of comprehensive bibliometric analyses that cover the full range of these technologies in agriculture. This gap limits understanding of their integration and impact. This study aims to provide a holistic bibliometric analysis of the integration of Industry 4.0 technologies in agriculture, identifying key research trends and gaps. We analyzed relevant literature using the Scopus database and VOSviewer software (version 1.6.20, Centre for Science and Technology Studies, Leiden University, The Netherlands)and identified five major thematic clusters within Agriculture 4.0. These clusters were examined to understand the included technologies and their roles in promoting sustainable agricultural practices. The study also identified unexplored technologies that present opportunities for future research. This paper offers a comprehensive overview of the current research landscape in Agriculture 4.0, highlighting areas for innovation and development, and serves as a valuable resource for enhancing sustainable agricultural practices through technological integration.

The quality of resistance spot welding (RSW) joints is strongly affected by the condition of the electrodes. This work develops a machine learning-based tool to automatically assess the influence of electrode wear on the quality of RSW welds. Two different experimental campaigns were performed to evaluate the effect of electrode wear on the mechanical strength of spot welds. The resulting failure load of the joints has been used to define the weld quality classes of the machine learning tool, while data from electrode displacement and electrode force sensors, embedded in the welding machine, have been processed to identify the predictors of the tool. Some machine learning algorithms have been tested. The most performing algorithm, i.e., the neural network, achieved an accuracy of 90%. This work provides important theoretical and practical contributions. First, the decreasing thermal expansion of the weld nugget as the electrode degradation advances results in a strong correlation between the difference of the maximum displacement value and the last value recorded during the welding and the relative failure load. Then, this work offers a practical decision support tool for manufacturers. In fact, the automatic detection of low-quality welds allows to reduce or eliminate unnecessary redundant welds, which are performed to compensate for the uncertainty of electrode wear. This leads to savings in time, energy, and resources for manufacturers. Finally, general recommendations for the timing of redressing or replacing the electrode are provided in the manuscript based on the company willingness to accept some non-compliant welds or not.

Industrial companies are moving toward the electrification of equipment and processes, in line with the broader energy transition taking place across the economy. Particularly, the energy efficiency and, consequently, the reduction of environmental pollution of intralogistics activities have become a competitive element and are now an actual research and development objective. A wireless power transfer is a contactless electrical energy transmission technology based on the magnetic coupling between coils installable under the ground level and a coil mounted under the vehicle floor, and it represents an excellent solution to decrease the demand for batteries by reducing vehicle downtimes during the recharge. This work aims to define a methodology to determine the optimal positioning of wireless charging units across the warehouse, both for static and dynamic recharging. To this aim, firstly, a mathematical model of the warehouse is proposed to describe transfers and storage/retrieval operations executed by the forklifts. Then, an integer linear programming problem is applied to find the best possible layout of the charging infrastructures. The optimal solution respects the energetic requirements given by the customer and minimizes the overall system cost. The proposed approach was applied to optimize the installation in a real-size warehouse of a tire manufacturing company. Several scenarios were computer generated through discrete event simulation in order to test the optimizer in different warehouse conditions. The obtained results show that integrated dynamic and static WPT systems ensure a constant state of charge of the electric vehicles during their operations.