CNH Industrial (Italy)

SUMMARY & CONCLUSIONSFailure Mode and Effects Analysis (FMEA) is essential in reliability engineering but is often manual and time-consuming. This work implements local version of a semi-automated workflow that integrates Microsoft Excel, Python (using the xlwings package), and ChatGPT to accelerate and standardize FMEA generation while retaining engineering oversight.Engineers begin by entering the system context in an Excel worksheet; a Python back end then queries ChatGPT to generate an initial list of system components and candidate failure modes. Engineers review and refine these suggestions, define system boundaries and each component’s function, and approve or modify the items captured in designated Excel cells. The Python functions prompt ChatGPT with component context and repair/warranty data so that suggested failure modes, effects, and causes are grounded in organization-specific evidence rather than generic model knowledge.The implemented workflow produces FMEA entries that align more closely with observed field failure trends by incorporating repair and warranty data into prompt context. Auto-population of failure modes, causes, and effects substantially reduces routine authoring effort; initial tests indicate markedly faster completion times and broader coverage of plausible failures. Offloading routine content generation to the LLM allows engineers to focus on analysis, validation, and prioritization, improving consistency and the effective use of engineering judgment.Combining a familiar spreadsheet interface with Python automation and ChatGPT produces a practical, deployable semi-automated FMEA process. The approach enables reliability teams to generate richer, data-informed FMEA results more quickly, enhancing productivity and providing deeper insight into failure analysis. Planned Version 2 (cloud) work will include user-upload able, product- and system-specific knowledge bases (with macros to upload and tag documents to the cloud) so that subsequent Design Failure Mode and Effects Analysis (DFMEA) for the same system can limit retrieval-augmented generation (RAG) retrieval to a curated, relevant document set.

Cold atmospheric pressure plasma's applications are gaining interest in the biomedical and industrial fields. In particular, atmospheric pressure surface dielectric barrier discharge (SDBD) plasma constitutes a promising approach for the decontamination of large and sensitive substrates that require non-contact plasma treatment, as their process mostly relies on the transfer of plasma-generated reactive species, such as ozone, to the treatment samples. In this context, numerical modeling of plasmas can represent a valuable tool to enhance the understanding of the fundamental mechanisms promoting the process. As some detailed models, such as self-consistent fluid models, would accurately simulate the ozone transport to the substrate, these often require significant computing power and high execution times. Multizone global modeling of plasmas might represent a valid alternative to consider detailed chemical mechanisms while including approximated mechanisms for the transport of species from the plasma to the gas phase. In this work, the ozone concentration predicted by a multizone global model is compared with experimental measurements in order to characterise and understand the influence of species transport on the simulation results.

Agricultural tractors and their implements are at the basis of modern farming. Besides propulsion, in such system, most of the mechanical actuations are performed with a fluid power system that is highly power-dense and versatile, but has a low energy efficiency. This article first describes the challenges of the state-of-the-art hydraulic system that cause poor efficiency. Afterward, it proposes and demonstrates a solution that can significantly increase such efficiency without affecting the cost and functionality of the overall hydraulic control system. The proposed solution is based on a peculiar control approach to the hydraulic supply units that power the implement functions through the hydraulic remote connections. The approach is based on an impressed-pressure control methodology, as opposed to the traditional impressed flow method used in off-road machinery. The result is that the typical energy-inefficient pressure saturation conditions that often occur in common vehicles are mitigated and brought to a more efficient state. To support the development of the technology, the research takes into consideration the circuit of a 400-hp tractor and a 16-row planter. A simulation model of the hydraulic system of the two vehicles was implemented and validated against experiments. The model was then utilized to estimate the reduction in the energy consumption achieved by the proposed solution. Lab tests and field experiments of the proposed solutions applied to the reference tractor and planter system confirmed an overall 18% energy efficiency improvement.

This paper presents a novel approach for estimating the vertical load exerted on the rear axle of agricultural vehicles during fieldwork using tire compression measurements. The system comprises an optical time-of-fight (TOF) sensor integrated into the wheel rim, a microcontroller, and an online identification algorithm. The sensor exhibits minimal measurement error, approximately 1%, which, when combined with effective preprocessing and a piecewise linear regression model fueled by tire pressure data, yields a root mean square error (RMSE) of around 7%, with a maximum drawdown of 3% when considering periodic updates. This technology promises to reduce production costs while enabling optimal tire pressure calibration, thereby ensuring reduced fuel consumption and improved comfort for agricultural vehicle operators.

Heavily loaded gear trains are known to produce a characteristic whine noise and vibration signature, which radiates through the bearings producing an undesired noise emission affecting the NVH behavior of the overall machine. This phenomenon is generated by the variable mesh stiffness and the static transmission error of the gear pairs in mesh within the gear train, but its magnitude strongly depends on how the meshing processes combine between each others. In this context, the present work proposes an analytical methodology to predict amplitude and direction of the variable loads applied on the bearings of idle gears, assuming quasi-static conditions. The dissertation demonstrates that the multiple mesh forces produce a variable load on idle gear bearings describing an ellipse whose shape depends on various geometrical parameters of the system. Numerical examples are shown to assess the potentials of the method and highlight how gear train spatial layout and phasing between different meshings may be used during gearbox design projects to limit the emitted noise of the gear train.

This note is about a novel, thermodynamically consistent formulation for small strains continuum electro-chemo-mechanics applied to all solid state batteries, which are claimed to be the next-generation battery system in view of their safety accompanied by high energy densities. The response of a cell, made of a lithium metal foil, a solid electrolyte, and a porous LiCoO2 cathode, has been investigated in terms of quantities of interest such as the electric potential, the lithium concentrations profiles, displacements, and stresses. The plating and stripping of the lithium has been considered together with the volumetric evolution of the porous cathode. Together they contribute to the outbreak of mechanical stresses, which may influence the life cycle of a battery.

The objective of this paper is to size the power required by the main powertrain components used to electrify a backhoe loader in order to meet the requirements demanded by an operating cycle called backfill. The backhoe loader is modelled based on the external forces acting on itself. The power sizing approach was inspired in a technique applicable to the on-road vehicle electrification. This technique was adapted to electrify a backhoe loader. The backhoe loader modelling and the power sizing were implemented in a script developed in MATLAB. The simulation results showed backhoe loader is not able to recover braking kinetic energy along the backfill. The results also showed that power minimization of the engine-generator set maximizes the capacities of power and energy of the electrical energy storage source.

It has been known for some time that sputtered low-density coatings deposited under vacuum (e.g. carbon or B4C), applied on top of high-density metallic coatings, can enhance the reflectivity in the soft x-ray band (below ~5 keV). In the last years, we experimented with novel carbonated coatings obtained by dip-liquid deposition, in which a thin film is formed on the surface of a mirror by immersion in a suitable precursor solution. After several attempts with different chemical compounds, we found an optimal candidate both for the reflectivity performance and for the convenience of the deposition process, which is much simpler and inexpensive compared to conventional processes. In particular, such coatings can enhance the soft x-ray response at the reflection angles employed in future telescopes, like ATHENA (ESA), Lynx (NASA) and eXTP (CAS). In this paper we consider the application of dip-liquid overcoatings on conventional coatings (Au, Ir) or in combination with recently proposed chromium overcoatings and their possible uses to enhance the reflectivity of x-ray mirrors at low, medium or higher energies, presenting the first experimental results of x-ray tests on these coatings.

The use of LiDARs in automotive is increasingly widespread. In order to operate in a critical environment such as that of mobility, these systems must offer increasingly high performance. In particular, the ability to estimate the position of objects regardless of their reflectance and presence of diffusing backgrounds is a very sought-after feature by manufacturers. In commercial systems various strategies are used to make the measurement as insensitive as possible to these effects, however, it is not possible to fully compensate for the measurement errors caused by them. In this paper, we propose two simple experimental setups to verify the presence of these measurement errors in two scenarios. Moreover, we report the performance of a commercial LiDAR (MRS 6000 by Sick) using certified reflectance standards (Spectralon® Diffuse Reflectance Standards, by Labsphere). For this LiDAR, the results obtained show that a logarithmic variation of the reflectance of the target of 1.26-log at a target distance 2.4 m provides incompatible measurements. Furthermore, the presence of a background at a distance shorter than 11 cm, 12 cm and 13 cm respectively with 50 %, 75 % and 99 % reflectance also provides incompatible measurements for a target distance of 1.3 m from the LiDAR.