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This paper presents an innovative Universal Multi-Parametric Model for designing devices using Magneto Rheological Fluids based on the explication of relationships between the functional requirements and the corresponding combination of related properties (chemical and physical)A rationale thus results to select the best MRF for a specific application. This might constitute a useful tool providing organized knowledge on the MRF world for scholars and practitioners approaching to the world of MRF technology as well as a support to engineers/designers during the early design tasks.

With the constant increase of energy costs and environmental impacts, improving the process efficiency is considered a priority issue for the manufacturing field. A wide knowledge about materials, energy, machinery, and auxiliary equipment is required in order to optimize the overall performance of manufacturing processes. Sustainability needs to be assessed in order to find an optimal compromise between technical quality of products and environmental compatibility of processes. In this new Industry 4.0 era, innovative manufacturing technologies, as the additive manufacturing, are taking a predominant role. The aim of this work is to give an insight into how thermodynamic laws contribute at the same time to improve energy efficiency of manufacturing resources and to provide a methodological support to move towards a smart and sustainable additive process. In this context, a fundamental step is the proper design of a sensing and real-time monitoring framework of an additive manufacturing process. This framework should be based on an accurate modelling of the physical phenomena and technological aspects of the considered process, taking into account all the sustainability requirements. To this end, a thermodynamic model for the direct laser metal deposition (DLMD) process was proposed as a test case. Finally, an exergetic analysis was conducted on a prototype DLMD system to validate the effectiveness of an ad-hoc monitoring system and highlight the limitations of this process. What emerged is that the proposed framework provided significant advantages, since it represents a valuable approach for finding suitable process management strategies to identify sustainable solutions for innovative manufacturing procedures.

Metal additive manufacturing is growing its impact on high-tech industrial sectors so far. The capability to recover and repair worn components, with costs that are gradually more affordable, is giving a boost to the development of these technologies. The direct laser metal deposition (DLMD) technology is taking a leading role in this domain. Manufacturing components, with high mechanical properties, require a careful process design and a continuous control. The monitoring of the thermal field thus assumes a crucial role in processes in which high-power sources are involved. Thermal treatments influence the microstructure, morphology and the grain size of the depositions indeed, which determine high-performance standards. In this work, an ytterbium fibre laser source was used to build single-track depositions of a nickel-based superalloy powder on a substrate of the same material. Temperature field monitoring was performed using a high-frequency (100 Hz) IR thermal camera, allowing an accurate monitoring of peeks temperature, thermal cycles and thermal gradients. Thermal data and process parameters were compared with metallographic analysis to capture the relation between the geometrical and microstructural characteristics of clads. The study focuses on the influence of the powder feed rate and energy density on thermal parameters. An innovative approach to the solidification map method, commonly implemented with numerical simulations of welding and additive manufacturing, has been successfully applied to experimental data giving results consistent with the literature.

The direct laser metal deposition (DLMD) is an emerging technology in the additive manufacturing field, which is becoming widely adopted in several industrial applications. The optimal selection of process parameters is critical, given the cost of physical tests and the requirement for high-quality manufacturing. Correct forecasting of process parameters using predictive physical models is a viable alternative to shorten the setup phase and improve the sustainability. In this paper, firstly, several models available so far in the literature are reviewed, and then, a general model is derived to evaluate the best combination of process parameters in single track operations. The proposed phenomenological model allows simple forecasting based on three main process parameters: laser power (P), powder feed rate (F) and translation speed (V). An innovative approach is proposed to generalise the model and overcome the “try and error” method used in numerous works to determine the exponents (α, β, γ). The model was designed considering the physical parameters which best explained the variability of the exponents: the thermal diffusivity of the base material and the density of the powder material. The best ranges of the process parameter exponents are suggested to establish the most suitable combined parameters for the prediction of geometric characteristics of the clad. The potentialities of the model are proven based on an experimental case performed over a commercially available Nickel-based super-alloy powder. New formulations are recommended, which are in good agreement with the behaviours defined in the literature, as shown in the test case.

The effect of mixing suspended nanoparticles into a bi-disperse magneto-rheological fluid on sedimentation phenomena is explored. A reference bi-disperse MRF has been modified using a ferrofluid containing magnetite nanoparticles of two shapes (spheres or hexagonal platelets) suspended in paraffin-oil as carrier fluid. The reference MRF was prepared with a mixture of two diameter sizes for the micrometric particles. The reference MRF was also prepared using two different grades of carbonyl-iron micrometric particles (herein these will be referred to as HARD and SOFT), which differ each other for their mechanical properties. The experiment monitored the evolution with time of the sediment-supernatant interface. This experiment showed that the presence of nanoparticles (particularly the spherical ones) slows down the sedimentation effects in terms of ratio and rate, independently of the other characteristics of the fluid. This study also showed that fluids based on SOFT carbonyl iron powders, in presence of nanospheres, are more stable than HARD carbonyl iron powder based fluids, since their sedimentation rate slows down in the long term. At the same time, HARD particle-based magnetorheological fluids show smaller sedimentation ratios than SOFT based fluids.

International audience; A Cyber-Physical-Social System (CPSS) is an emerging research trend that focuses on integrating the social dimension into Cyber-Physical System (CPS). The CPSS consists of social, physical, and cyberspaces. There is a lack of influential theories and design approaches to reach a unified structure of a CPSS. Furthermore, the impacts of a CPSS on the sustainability performance of systems and processes are still unexplored. The paper addresses this latter research issue by evaluating case studies on CPSSs discussed in the literature.