Enabling Value co-creation with customers through Artificial Intelligence: A case study approach

The digital movement has radically altered how manufacturing companies interact with their customers. By using Artificial Intelligence (AI), companies have drastically changed their value co-creation (VCC) strategies. We adopt a case study approach and engage with an original equipment manufacturer (OEM) to get a grasp of the phenomenon. Among the data collection methods we assume, we conduct semi-structured interviews with the company project team and its customer base. In addition, we collect secondary data and run focus groups within the studied firm\u27s management team. This research in progress will advance a framework linking VCC with service maturity and identify the performance metrics required for the AI-based journey. Such a framework may assist practitioners in building services based on AI and VCC. Ultimately, we plan to offer theoretical implications to progress the AI and VCC debate and propose future research suggestions

Using Artificial Intelligence to Co-Create Value with Customers

The advent of interrelated technologies such as Big Data (BD) and Artificial Intelligence (AI) has radically transformed how industrial firms can co-create value with their customers. We collect data from an organization in the manufacturing industry to understand how it co-creates value from BD using AI. In addition to secondary data collection, we engage with the company actors and the customers involved in developing the solution based on AI by conducting a series of focus groups and adopting a semi-structured interviewing approach. We propose a conceptualization of value co-creation to identify the potential relationship between AI-augmented solutions and the customer journey. Furthermore, we offer performance metrics for value co-creation on AI applications with customers. Finally, we present theoretical and practical implications and suggest future research directions to advance the field of value co-creation and AI

Dating and Mating : Attitudes of Middle Eastern Students in the United States

The need for this study stemmed from the fact that a large number of Middle Eastern students are coming to the United States of America to seek higher education. This has created a social problem for both the Middle Eastern students and their American counterparts because of the great differences between their cultures in the practice of dating and mating. The objectives of the study were to examine the opinions of a sample of Middle Eastern students in the United States in regards to dating and mating practices. The sample size was one hundred students. A literature search of the materials that are relevant to the subject showed a scarcity of scientific approach on the subject. The analyses of the findings indicated that the Middle Eastern students selected dating partners by significantly different criteria than those by which they selected their mating partners. Furthermore, it was noted that the independent variables of sex, age, marital status, time in the United States, type of resident visa, country of origin, and religious affiliation greatly affected the preferences of the respondents in regards to selected personal characteristics for a dating or a marital partner

Learning deep policies for physics-based robotic manipulation in cluttered real-world environments

This thesis presents a series of planners and learning algorithms for real-world manipulation in clutter. The focus is on interleaving real-world execution with look-ahead planning in simulation as an effective way to address the uncertainty arising from complex physics interactions and occlusions. We introduce VisualRHP, a receding horizon planner in the image space guided by a learned heuristic. VisualRHP generates, in closed-loop, prehensile and non-prehensile manipulation actions to manipulate a desired object in clutter while avoiding dropping obstacle objects off the edge of the manipulation surface. To acquire the heuristic of VisualRHP, we develop deep imitation learning and deep reinforcement learning algorithms specifically tailored for environments with complex dynamics and requiring long-term sequential decision making. The learned heuristic ensures generalization over different environment settings and transferability of manipulation skills to different desired objects in the real world. In the second part of this thesis, we integrate VisualRHP with a learnable object pose estimator to guide the search for an occluded desired object. This hybrid approach harnesses neural networks with convolution and recurrent structures to capture relevant information from the history of partial observation to guide VisualRHP future actions. We run an ablation study over the different component of VisualRHP and compare it with model-free and model-based alternatives. We run experiments in different simulation environments and real-world settings. The results show that by trading a small computation time for heuristic-guided look-ahead planning, VisualRHP delivers a more robust and efficient behaviour compared to alternative state-of-the-art approaches while still operating in near real-time

Machinability and Modeling of Cutting Mechanism for Titanium Metal Matrix Composites

"RÉSUMÉ:" Les composites à matrice métallique de titane (CMMTi) sont une nouvelle classe de matériaux. Le CMMTi possède les caractéristiques des alliages de titane (légèreté, résistance et biocompatibilité) tout en ayant des propriétés physiques accrues lui conférant des avantages sur les alliages de titane. Ses nombreuses applications potentielles dans différents secteurs industriels tels l’aéronautique et le domaine biomédical en font un matériau de l’avenir. Déjà, certains fabricants de turbines montrent un grand intérêt pour de futures applications. Dans le domaine biomédical, le CMMTi offre un avantage pour les greffes osseuses présentant une action de glissement/frottement. Par contre, le CMMTi doit être usiné avant d'être utilisé comme pièce ou partie d'un assemblage, mais les particules solides de céramique ajoutées à l’alliage de titane rendent son usinage très difficile. De plus, l'intégrité de la surface du matériau après usinage est de première importance avant son utilisation dans un assemblage mécanique. La vie de l'outil est donc limitée en raison de son usure par l’action abrasive des particules dures, ainsi qu’à cause de la diffusion en raison de la température élevée de l'interface outil-matériau. Lors de l'usinage, la durée de vie de l'outil et la rugosité de la surface de la pièce sont des préoccupations majeures pour les industriels. Trois approches ont été élaborées afin d'optimiser les paramètres d’usinage du CMMTi. La première approche expérimentale consiste en une méthode de planification d’expériences (TAGUCHI) utilisée afin d’identifier les effets des paramètres de coupe (vitesse, avance, et profondeur de coupe) sur les forces de coupe, la rugosité de surface, et l’usure de l’outil. Dans une deuxième approche, et afin de mieux comprendre le mécanisme de coupe du CMMTi, la formation de copeaux lors de la coupe a été analysée et un nouveau modèle de la bande de cisaillement adiabatique a été développé. Dans la dernière approche, et pour obtenir un meilleur outil d'analyse pour la compréhension du mécanisme de coupe, un nouveau modèle constitutif du CMMTi a été développé, en utilisant un modèle d’endommagement, à des fins de simulation. Les résultats des simulations de Modèle d’Élément Fini (MEF) ont permis de prévoir la température, les contraintes, les déformations et l’endommagement du matériau. Ces dernières informations peuvent être utilisées pour l'analyse de l’usinage ainsi que pour des applications industrielles.----------"ABSTRACT:" Titanium Metal Matrix composites (TiMMC) is a new class of material. The enhanced properties of TiMMC provide it with many advantages over titanium alloys. TiMMC is a material of the future and has many potential applications in the aeronautical sector, as in the turbines’ cold section parts, and in biomedical applications, for example in bone transplants where a sliding/rubbing action is present. Turbine engine manufacturers already show a great interest in TiMMC for future applications. However, TiMMC requires machining in order to be used as part of an assembly, but the abrasive action of the added ceramic TiC particles, combined with the problems of cutting titanium alloys, make it a very difficult to cut material. Therefore, the tool life is limited, due to the abrasion wear from the hard particles and to the diffusion wear due to the high temperature of the tool-chip interface that characterizes the cutting of titanium alloys. When machining, tool life, and surface roughness are major concerns for industrials. In order to optimize the machining of TiMMC, three approaches (stages) were used. First, a TAGUCHI method for the design of experiments was used in order to identify the effects of the machining inputs (speed, feed, depth) to the output (cutting forces, surface roughness). To enhance even further the tool life, Laser Assisted Machining (LAM) was also experimented. In a second approach, and in order to better understand the cutting mechanism of TiMMC, the chip formation was analyzed and a new model for the adiabatic shear band in the chip segment was developed. In the last approach, and in order to have a better analysis tool to understand the cutting mechanism, a new constitutive model for TiMMC for simulation purposes was developed, with an added damage model. The FEM simulations results led to predictions of temperature, stress, strain, and damage, and can be used as an analysis tool and even for industrial applications. In the literature, no research studies are found on the machining of TiMMC. The first experimental approach of this current research is the only study to provide practical recommendations for determining the cutting parameters and for evaluating different cutting tools for machining TiMMC. Following experimental work and analysis, I found that cutting TiMMC at higher speeds is more efficient and productive because it increases tool life. This is in opposition to most materials, where higher cutting speeds reduce tool life. This phenomenon of efficient cutting at higher speeds was explained by the different tool/particles behavior

NOVEL FAST ANALYTICAL METHODS FOR THE ANALYSIS OF FLUOXETINE IN PURE AND PHARMACEUTICAL DOSAGE FORM

Novel and accurate analytical methods were developed and validated for the characterization of Fluoxetine in its pure and pharmaceutical dosage form Prozac®. Fluoxetine was determined by IBA techniques (PIGE, PIXE and RBS). It has been also analyzed spectrophotometrically at 610 nm after oxidation with potassium permanganate in alkaline medium. In addition, Fluoxetine was kinetically determined using the initial rate method, the fixed absorbance method and the fixed time method. Moreover, a Gas chromatography - mass spectrometry technique is proposed for the investigation of Fluoxetine without a prederivatization phase. The spectrophotometric method was performed with a concentration array of 2-10 μg/mL at 610 nm and a regression coefficient (r) of 0.996. The fixed time method was the most suitable one to determine Fluoxetine with correlation coefficient value (r) of 0.9966. The Gas chromatography - mass spectrometry investigated the drug in a concentration range of 20-100 μg/mL and a regression coefficient (r) of 0.999. IBA analysis presented a precision of less than 3% and a very low limit of detection. Consequently, these proposed methods would be useful tools for determining Fluoxetine as all the assay results exposed satisfactory sensitivity, accuracy and reproducibilit

FOURIER TRANSFORM INCOHERENT BROADBAND CAVITY ENHANCED ABSORPTION SPECTROSCOPY DEVELOPED FOR THE STUDY OF COLD ASTROPHYSICAL ANIONS IN A PLANAR LAVAL NOZZLE EXPANSION

The molecular diversity of cold interstellar medium has been recently enriched with the detection of molecular anions: $C_4H^-$, $C_6H^-$, $C_8H^-$, $C_3N^-$, $C_5N^-$ and $CN^-$. Although by far less abundant than neutrals, anions could play a significant role in the chemistry of molecular clouds\footnote{A. Van Orden, R.J. Saykally, Chem. Rev. 98 (1998) 2313-2358}$^,$\footnote{W. Weltner Jr, R.J. Van Zee, Chem. Rev. 89 (1989) 1713-1747}. With the exception of $C_5N^-$, whose identification in space was based on high-level ab initio calculations\footnote{J. Cernicharo et al. The Astrophysical Journal 688, no 22008: L83 86}, the astronomical detection of these anions was made possible thanks to the laboratory characterization of their rotational spectra. Our ultimate goal is to characterize the anionic carbon chains $C_x^-$ (x = 3, 4, 5,…) through their electronic spectra in order to explain the absorption features already observed one century ago in some diffuse interstellar clouds illuminated by reddened stars. We will represent our new instrument based on a planar de Laval supersonic plasma source coupled to Incoherent Broadband Cavity-Enhanced Absorption Spectroscopy (IBB-CEAS) in conjunction with a high-resolution Fourier transform spectrometer for the detection. Preliminary results obtained on neutral species ($O_2$, $CH_4$, $C_2H_2$) will be presented