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Comparison of pull management policies for a divergent process with DDMRP buffers: an industrial case study
No full textInternational audienceProduction planning and scheduling for companies with divergent processes, where a single component can be transformed into several finished products, are challenging as planners might face material misallocation issues. In this paper, we address the problem of managing a divergent process with DDMRP stock buffers, where different finished products are bottled with the same component having a fixed batch size. An allocation decision needs to be made to determine the quantities of finished products to be bottled. This study is motivated by a real-life problem faced by a dermo-cosmetic company. We compare and analyze by simulation nine different policies triggering allocation decisions. The first policy is the classic DDMRP rule, while the others are new policies, including a virtual buffer of a generic finished product and ConWIP loops, delaying the allocation decision. Our results show that the policy combining the classic DDMRP rule and a ConWIP loop surrounding a part of the process reduces the work-in-process by 34% compared to the classic DDMRP while ensuring high customer service rates and control of flow times
Supercritical carbon dioxide solubility measurement and modelling for effective size reduction of nifedipine particles for transdermal application
No full textInternational audienceNifedipine (NIF) is a Class II drug of the Biopharmaceutical Classification System (BCS) with low oral bioavailability, low dissolution rate and significant hepatic drug metabolism. The transdermal route using supersaturated systems could be considered. For this purpose, physicochemical properties of NIF such as its dissolution rate, may be a limiting factor and must be improved. Crystallization processes assisted by supercritical carbon dioxide (scCO2) and particularly the Rapid Expansion of Supercritical Solution (RESS) process may improve drug bioavailability by reducing particle size and consequently increasing surface area. This study addresses the reduction of NIF particle size using scCO2-RESS as crystallization process. Experimental solubility studies were performed at different temperature (308 and 318 K) and pressure ranges (9-24 MPa). Solubility data were correlated with two thermodynamic models in order to predict NIF solubility in scCO2. Optimized operating conditions, identified by thermodynamic modelling, allowed the production of thinner NIF particles and a size reduction up to ten fold. Particle size reduction improved NIF dissolution kinetics in aqueous medium: after 90 min, 42 % of raw NIF was released against 80 % for crystallized NIF. The scCO2-RESS process is a solvent free process, that can produce micronized or nanosized crystals able to improve physicochemical properties of poorly water-soluble drugs
Improved aromatic yield and toluene selectivity in propane aromatization over Zn–Co/ZSM-5: effect of metal composition and process conditions
No full textInternational audienceIn this report, a catalytic enhanced-conventional process production background was employed to determine the most cost-effective and environmentally friendly techniques to improve the catalytic production of toluene and other aromatic compounds from propane aromatization. 2 wt% of zinc was co-impregnated with 1–3 wt% of cobalt on HZSM-5. Characterizations and analysis showed that catalysts are crystalline and microporous. Propane conversion was carried out at 540 °C, 1200 ml/g-h gas hourly space velocity and atmospheric pressure over Zn–Co/ZSM-5 bimetallic catalysts. Toluene selectivity in the aromatic products was greatly improved and sustained significantly together with other aromatic products. Catalytic conversion of propane and aromatic yield over Zn–Co/ZSM-5 was improved and stabilized due to metallic collaboration on HZSM-5. Aromatic yield averaged 46, 32, and 36%, respectively, for 1–3 wt% Co in Zn–Co/ZSM-5 bimetallic catalyst. Average toluene selectivity in the aromatic products for 12 h time on stream from 60, 50 and 51% for 1–3 wt% Co loading. The threshold loading of cobalt with zinc was 2% above which the general aromatic selectivity declined. A decrease in conversion from 73 to 15% was observed for flowrate increase from 6 to 35 ml min−1 and an increase in aromatic selectivity from 80 to 87%. An increase in temperature of 500–560 °C increased catalytic performance, 32–47% for propane conversion, and 79–86% aromatic selectivity
Effect of process parameters of Plain Water Jet on the cleaning quality, surface and material integrity of Inconel 718 milled by Abrasive Water Jet
No full textInternational audienceAbrasive Water Jet (AWJ) is considered as a promising milling method for difficult-to-machine aeronautical materials as Inconel alloy 718 (IN718). However, grit embedment during AWJ is known as a detrimental effect on certain applications as aircraft repair, where surface condition may play an important role on additive material technologies. To overcome this problem, Plain Water Jet (PWJ) has been used in the present study as cleaning process and demonstrated to be an effective method to remove grit particles from the surface with marginal alterations of surface state. In this paper, firstly the influence of AWJ process parameters on abrasive embedment and surface texture on IN718 specimens milled by AWJ were addressed. Then these surfaces were subjected to PWJ cleaning process and were extensively characterized in terms of grit embedment, surface texture and roughness, erosion depth, microhardness and residual stresses. Before cleaning, the milled surfaces presented a grit embedment level varying between 7 % and 14 %. One setting condition was selected for performing PWJ cleaning which reduced the grit level up to a quarter of the initial total surface area (less than 4 % in all cleaned surfaces) without relatively modifying neither the surface texture nor the erosion depth. Comparable microhardness gradients were observed before and after PWJ cleaning which corresponded to ∼ 30 % higher than the bulk values at surface and then decreased beneath the surface up to 200 µm before to reach bulk value (∼ 245 HV). Compressive residual stress state at surface initially induced by AWJ milling in some surfaces remained unchanged after PWJ process but in other ones was slightly relieved (∼ 50 MPa). Residual stresses after PWJ process resulted from − 630 MPa to – 315 MPa depending on the milling process parameters
Size Effect on the Tensile Mechanical Behavior of Thin Ti6242S Specimens at 723 K and 823 K
No full textInternational audienceThe mechanical behavior of titanium-based alloy Ti6242S was investigated under uniaxial tensile loading at 723 K (450 °C) and 823 K (550 °C) under air and argon environments. Microtensile specimens ranging from 1 mm to 100 µm in thickness were tested to investigate the influence of the decrease in thickness on mechanical properties. Fractographic analyses were carried out using scanning electron microscopy. At 450 °C and 550 °C, a decrease in yield strength, ultimate tensile strength, and strain-to-failure with decreasing thickness was observed. These drops in the macroscopic tensile properties of the thinnest specimens result from a combination of oxidation, which further impairs the specimens with a high surface-to-volume ratio, and the overall lower number of colonies of α lamellae contained in thinner specimens. Ti6242S exhibited dynamic strain aging at 450 °C, especially in specimens with thickness below 500 µm
Influence de la microstructure semi-cristalline du Poly(Ether-Ketone-Ketone) sur la perméabilité à l'hydrogène
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A Synthetic Dataset Generation for the Uveitis Pathology Based on MedWGAN Model
No full text© 2023 Copyright held by the owner/author(s). Publication rights licensed to ACMInternational audienceArtificial Intelligence (AI) has undergone considerable development in recent years in the field of medicine and in particular in decision support diagnostic. However, the development of such algorithms depends on the presence of a sufficiently large amount of data to provide reliable results. Unfortunately in medicine, it is not always possible to provide so much data on all pathologies. This problem is particularly true for rare diseases. In this paper we focus on uveitis, a rare disease in ophthalmology which is the third cause of blindness worldwide. This pathology is difficult to diagnose because of the disparity in prevalence of its etiologies. In order to provide physicians with a diagnostic aid system, it would be necessary to have a representative dataset of epidemiological profiles that have been studied for a long time in this domain. This work proposes a breakthrough in this field by suggesting a methodological framework for the generation of an open source dataset based on the crossing of several epidemiological profiles and using data augmentation techniques. The results of these generated synthetic data have been qualitatively validated by specialist physicians in ophthalmology. Our results are very promising and consist in a first brick to promote research in AI on Uveitis disease
Conception d'un système de détection des risques piloté par les données de suivi temps-réel des flux logistiques
No full textIn the current context of globalization, intermodal container transport plays an important role in the efficiency and effectiveness of the supply chain. Indeed, containerization induces a high productivity during port handling and a reduction of transport costs thanks to groupage. It also ensures the integrity and security of the goods transported. However, the large number of actors involved in the container transport process makes it extremely complex and leads to a loss of visibility and traceability during the transit of goods. In addition, the transit process is very often subject to random events that lead to delivery delays and increased transport costs. In view of all these difficulties, this thesis addresses the following problem: How to detect the causes of delays and quantify their impact on the time of containerized transports in an intermodal context? A system based on a hybrid approach is proposed to address this issue. First, we propose a knowledge model of risks in intermodal transport in the form of a domain ontology. Then, by using this knowledge, and relying on container traceability/visibility data and data from textual information sources, we extract in real time the random events that may disrupt the transport flow. We are interested in decision support for the activities of the actors involved in the intermodal transport chain (exporters, consignees, carriers, shipping companies, etc.). The research is conducted in collaboration with an industrial partner which develops a real-time tracking solution for containers.Dans le contexte de mondialisation actuel, le transport intermodal des conteneurs joue un rôle important dans l'efficience et l'efficacité de la chaîne d'approvisionnement. En effet la conteneurisation induit une forte productivité lors des manutentions portuaires et une réduction des coûts de transport grâce au groupage. Elle assure également l'intégrité et la sécurité des marchandises transportées. Néanmoins, le grand nombre d'acteurs impliqués dans le processus de transport des conteneurs le complexifie énormément et induit une perte de visibilité et de traçabilité lors du transit des marchandises. De plus, ce dernier est très souvent soumis à des évènements aléatoires qui entraînent des retards de livraison et une augmentation des coûts de transport. Au regard de toutes ces difficultés, cette thèse adresse la problématique suivante : comment détecter les causes de retard et quantifier leurs impacts sur les délais d'acheminement des marchandises en transport conteneurisé dans un contexte intermodal ? Un système basé sur une approche hybride est proposé pour répondre à cette problématique. Nous proposons premièrement un modèle de connaissances des risques dans le transport intermodal sous forme d'une ontologie de domaine. Ensuite, en utilisant cette connaissance, puis en nous appuyant sur les données de traçabilité/visibilité des conteneurs et des données provenant des sources d'informations textuelles, nous extrayons en temps réel les évènements aléatoires susceptibles de perturber le flux de transport. Nous nous intéressons ici à l'aide à la décision pour supporter les activités des acteurs impliqués dans la chaîne de transport intermodal (exportateurs, consignataires, transporteurs, compagnie maritime, etc). Les recherches sont menées en collaboration avec un partenaire industriel qui développe une solution de tracking temps réel des conteneurs
Monte Carlo method to solve the heat equation in a complex media
No full textInternational audiencePorous or fibrous complex medias are widely used for energy applications such as heat storage, thermal insulation, solar absorbers, heat exchangers... There is a need to develop methods that are relevant to solve the heat equation in those complex medias. Monte Carlo method can be used to solve parabolic partial differential equations such as heat equation in complex geometries or porous media. It relies on reformulating the thermal model first as an integral and then as an expected value introducing a probability density function. An important point is that this method does not require a volumic mesh which makes it relevant for complex geometries. Randomly generated paths carry information (known temperature or flux on a boundary, volumetric heat source...) in their weights. The observable - local temperature, mean temperature on a given surface - is then evaluated by computing the arithmetic mean of the weights, based on the Law of Large Numbers. It is noticeable that Monte Carlo method does not evaluate a temperature field but only the observable. Therefore, it reduces the amount of data to handle for post-treatment. The Monte Carlo algorithm can easily be parallelized since each path is independently computed on a single processor.Based on the Central Limit Theorem, the result is always given with its variance and then with the associated uncertainty. In this work, we solve the thermal model in a diphasic complex porous media. Geometry has been obtained through tomography technique and is composed of 8 x10^6 triangles. This sample has been chosen for its complexity: large range of spatial scales, hollow fibres... Computations have been performed with the free and open-source software Stardis (https://www.meso-star.com/projects/stardis/stardis.html) which is suitable to take conduction, convection and radiation transfers into account. Based on recent work of Tregan, Stardis has been extended to non-linear cases to take the radiative term - difference of temperatures to the power four - into account without linearization which is crucial when the difference of temperatures is high. In the present work, the thermal model has been successfully solved to determine the apparent conductivity tensor with and without radiative transfers.Further work is required to investigate how to solve other advection-diffusion equations with this Monte-Carlo method