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Kmeans is one of the most algorithms that are utilized in data clustering. Number of metrics is coupled with kmeans in order cluster data targeting the enhancement of both locally clusters compactness and the globally clusters separation. Then, before the ultimate data assignment to their corresponding clusters, the selection of the optimal number of clusters should constitute a crucial step in the clustering process. The present work aims to build up a new clustering metric/heuristic that takes into account both space dispersion and inferential characteristics of the data to be clustered. Hence, in this paper, a Geometry-Inference based Clustering (GIC) heuristic is proposed for selecting the optimal numbers of clusters. The conceptual approach proposes the “Initial speed rate” as the main geometric parameter to be inferentially studied. After, the corresponding histograms are fitted by means of classical distributions. A clear linear behaviour regarding the distributions’ parameters was detected according to the number of optimal clusters k* for each of the 14 datasets adopted in this work. Finally, for each dataset, the optimal k* is observed to match with the change-points assigned as the intersection of two clearly salient lines. All fittings are tested using Khi2 tests showing excellent fitting in terms of p-values, and R² also for linear fittings. Then, a change-point algorithm is launched to select k*. To sum up, the GIC heuristic shows a full quantitative aspect, and is fully automated; no qualitative index or graphical techniques are used herein.

Metal additive manufacturing is an emerging advanced technology, it differs from conventional manufacturing methods as machining, casting and forging, which are either subtractive or forming. Firstly, the objective of this work is to elaborate a new 316L stainless steel material by Selective Laser Melting (SLM) from metallic powder according to specific operating parameters namely laser scanning speed and power. Secondly, the characterization of this developed material by 3D printing is carried out. For this purpose, metallographic observations and heat treatments at different temperatures 650, 800 and 1050°C were performed. Thus, the contribution of this study is to develop procedure and tools to enhance their mechanical properties at the level of parts obtained by conventional processes. Therefore, samples were examined by X-RF, SEM, EDS mapping, density, and hardness measurements as well. Results show that mechanical properties of additive manufactured samples can be improved in certain conditions linked to operating parameters and heat treatment. Also, this work has allowed us to confirm the resistance of the 316L stainless steel developed by SLM to high temperatures.

Actually, additive manufacturing (AM) is considered as a major class of complex parts manufacturing technologies. Including a wide range of materials, a huge set of physico-chemical phenomena are involved and adapted to control and master the variety of materials processing. On the other side, AM still knows a low productivity rate, due to different reasons that are mainly related to the material-process interaction control. In this paper, the authors propose a novel 2D scanning strategy that could be adapted to AM processes such as Laser Beam Powder Bed Fusion of Metals (PBF-LB/M) and polymers (PBF-LB/P), Electron Beam Powder Bed Fusion for metals (PBF-EB/M), and Material Extrusion-based (MEx) (ISO/ASTM 52,900 standards). The novelty presented corresponds to a Skeleton Based Perpendicularly (SBP) scanning strategy that aims to reduce the scanning lengths, and thus the production time and processing energy. The competitiveness of the new technique is mainly discussed according to the hatch space distance and the dimensions of a rectangular shape that was selected for the proof of concept of this new scanning strategy. In other words, it is proposed to investigate the competitiveness of the new scanning technique compared to four classical scanning strategies that are widely used in AM in term of process productivity. A detailed benchmark analysis has been applied to the following strategies: chess, stripe, spiral, and contour scanning. An analytical mathematical modeling was developed leading to the evaluation of the performance of SBP scanning compared to the scanning benchmark strategies by means of two proposed geometrical indices: the “gain of length” and the “specific gain of length per surface unit”. These were exploited in two separate study cases. The simulation showed that the SBP scanning length exhibits an increasing quadratic dependence on rectangle dimensions and a decreasing hyperbolic behavior according to hatch space distance. The lengths of the benchmark scanning strategies also presented a hyperbolic decreasing behavior according to hatch space distance. After that, it was proved that the SBP strategy is absolutely competitive compared to chess and stripe scanning; the competitiveness fluctuates around 95%, but it is highly concentrated around 100%. Otherwise, for the contour and stripe strategies, it has been shown that the competitiveness is strongly affected by the hatch space distance and by the dimensions of the shape being scanned. A particular behavior of the feasibility percentage of decision variable combinations, was detected as power laws or polynomials of the hatch space distance in the case of SBP/spiral comparison. In this case, the competitiveness (feasibility) ranged from 20 to 98% while it ranged from 0 to 75% in the case of SBP/contour comparison. The results of this study could also constitute a major contribution to related scientific and technical fields concerned with optimal area or volume control.

Nowadays, the energetic efficiency becomes one of the major interests of the global society. Thus, the energetic challenges of the new century enforce the scientific and industrial environment to the development of new efficient materials, which present more than the classical thermal properties, according to the energy storage, energy consumption and other specific needs. In this context, the present work constitutes the third step of the development of a new kind of composite materials (micro-composites and nano-composites), using natural marl (clay) clay and biodegradable polymer, which is the PolyEthylene Glycol 6000 (PEG 6000). This step corresponds to characterization of the variation of the specific heat (denoted Cp) of the materials elaborated. So, in order to estimate the capacity of thermal energy adsorption, we utilized a SHIMATZU-DSC 60 Differential Scanning Calorimeter. The main results present the evolution of the Cp according to the PEG 6000 doping and also the specific melting enthalpy of the polymer within the natural clay matrix; by the way this enthalpy constitutes the specific heat stocked in the materials.

Miocene marl is one of the widespread geological substrates in Fez vicinity (Central Morocco). In this study we proceed by a physicochemical characterization of the marl after doping with metal oxides, by various analytical techniques, namely the X-ray fluorescence, the mineralogical analysis, and dielectric property. The doping of these marl was conducted by solid oxides of Al2O3 at different percentages (5%, 10% and 15%). The results of chemical analysis showed the Al2O3 increase during doping. So, the mineralogical analysis of doped clays shows peaks' increases for kaolin. The marl doped acquired the property of their good electrical conductor compared to crass marl.

In this paper, we compare different nanoclay-PEG composites and the influence of the input parameters especially the percentage of PEG and the clay size. Because of the facility of material elaboration, dried state with grinding, we adopted a complete experiments plan to obtain a maximum of robustness of the responses. For each sample, we made an XRD analysis to see if we obtain the intercalation of the PEG 6000 (Polyethylene Glycol 6000) within the clay sheets. The characterization adopted consists on the measurement of the shrinking of some cylinders we made, the liquidity and plasticity limits according to the Casagrande protocol used in geotechnical clays characterizations. We utilize also the methylen blue protocol to estimate the variation of the specific surface of ionic exchange of the clay sheets according to the PEG 6000 percentage and the clay sizes. SEM microscopy permits to visualize some of the phases detected by the XRD analysis. The TEM microscopy permits also to see the amorphous phases created by the grinding protocol which affects significantly the specific surface and the shrinking of the new materials. For each section, we made some conclusions with interpretation in order to integrate these results in civil engineering, classical/artisanal material construction and geotechnical fields.

In this paper, we tried to formulate the interdependences of the systematic maintenance policies and the choice of a production master plan. We started from the intuitive relation between the time of production and the degradation state of the equipment to mathematically formulate the problematic and thus to build the objective space function and feasible solution set of this multiobjective problematic. The solutions set could after be presented to the decision maker to choose one, or more of these solutions, in order to manage and control the maintenance and production policies at the same time.

The aim of this paper is to characterize mechanically the new micro-composites that have been developed in our laboratories. The composites are composed by natural clay (as a matrix) with variant percentages of Polyethylene Glycol 6000 (PEG 6000) as micro-fillers. We used the compression test for the measurement of the static parameters such as elasticity modulus in elastic region and the hardening coefficient which permits to describe the plasticity behaviour of the materials. An additional energetic approach is proposed in order to quantify the evolution of the plasticity of the reinforced materials, caused by the PEG 6000, for different percentages of this polymer.