The marble extractive industry heavily depends on diesel-powered equipment, particularly wheel loaders and excavators used for block handling, resulting in high energy consumption and operating costs. In this study, the potential for fuel reduction through managerial and technological transitions was evaluated using the example of the marble quarry located in the Carrara basin. The energy demand of excavators, wheel loaders, and dumpers was characterized using telemetry data gathered through an Industry 4.0 methodology. A standard elementary cycle was modeled via the program evaluation and review technique (PERT) to map productive tasks and idling periods. To ensure comparability, a specific consumption coefficient (SCC) was defined. Subsequently, a novel fuel handling index (FHI) is proposed to prioritize investments by accounting for the uncertainties and production variables typical of quarry projects. Results demonstrate that while idle management offers a 4% fuel reduction, transitioning to hybrid wheel loaders represents a more significant strategy, achieving a 12% saving among the scenarios analyzed. The full-hybrid scenario leads to a cumulative 17% reduction. This framework supports decision-making for energy efficiency in high-yield extraction sectors, mitigating the economic risk associated with technological transitions.

The deployment of autonomous haulage systems and battery electric vehicles represents a promising pathway to decarbonizing the extractive industry while mitigating severe occupational hazards. This study investigates a 40-year historical dataset (1984–2024) from the U.S. Mine Safety and Health Administration across the stone and sand and gravel sectors to establish baseline injury trajectories and evaluate the safety impacts of fleet electrification and automation. Predictive and probabilistic modeling shows that removing onboard drivers achieves a net fatal risk reduction between 58% and 92%, even after incorporating emerging high-power battery charging hazards. However, haulage automation reconfigures shift dynamics without inherently eliminating ground-level hazards; residual non-fatal frequency rates depend critically on daily task reallocation across manual handling and auxiliary ground logistics. Furthermore, semi-quantitative assessment confirms a critical risk migration toward high-voltage maintenance (R = 12) and confined underground charging (R = 12), where thermal runaway off-gassing elevates explosion risks. Maximizing the safety benefits of autonomous electric haulage requires shifting safety governance from driver training to advanced high-voltage protocols, sensor maintenance and dedicated ventilation standards.

The purpose of this paper is to compare the levels of whole-body vibration (WBV) exposure to which operators are subjected when using conventional heavy equipment with internal combustion engines to hybrid heavy machines, which demonstrate potential advantages in terms of efficiency and sustainability. The study was carried out in a quarry using an experimental approach that analyzed conventional and hybrid heavy equipment during the same working phases in mining activities. The methodology involved direct vibration samples using triaxial accelerometers positioned uniformly on the operator’s driving stations. The vibrations were analyzed in accordance with ISO 2631-1, focusing on intensity and frequency distribution. To minimize the influence of interference factors and ensure a straightforward comparison of the results, the entire measurement campaign was conducted under the same conditions, including vehicle and operator characteristics. Hybrid machines provide notable sustainability benefits, but the results show they produce higher vibration levels compared to conventional ones. This underscores the need to improve vibration control in hybrid machinery to ensure operator comfort and health while supporting their sustainability advantages.

Traditional occupational noise risk assessment in quarries relies on static annual averages, failing to capture exposure peaks driven by operational shifts. Although noise risk assessment is a strict mandate under European Directives, capturing real-world operational volatility would require continuous, unfeasible phonometric campaigns. This study addresses this limitation by developing a dynamic, telemetry-driven energetic model to map occupational noise exposure and fleet volatility within the Carrara marble basin. The framework integrates continuous tracking from Internet-of-Things (IoT) platforms over a full calendar year with targeted in-cabin phonometric data. The empirical results reveal a dual-directional acoustic divergence from manufacturer specifications due to real-world quarry conditions and automated engine sub-regimes. Energetic tracking uncovers extensive exposure variance across production weeks; during peak periods, the skid-steer loader breaches statutory action boundaries, reaching a critical exposure value of 84.2 dB(A). Ultimately, this framework fulfills regulatory requirements through a streamlined, low-cost approach, providing a significantly more reliable and realistic hazard tracking tool than traditional static models.