Thematische Bibliographien / Intelligence – Industrie

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Bücher
  4. Buchteile
  5. Konferenzberichte
  6. Berichte der Organisationen

Auswahl der wissenschaftlichen Literatur zum Thema „Intelligence – Industrie“

Autor: Grafiati
Veröffentlicht am 25. Mai 2024

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Zeitschriftenartikel zum Thema "Intelligence – Industrie"

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Preuß, Thomas, Dirk Nölken und Frank Kusterer. „Controlling für eine Industrie- und Handelskammer“. Controlling 31, Nr. 4 (2019): 14–21. http://dx.doi.org/10.15358/0935-0381-2019-4-14.

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Der CFO einer IHK wird zunehmend zum strategischen Partner der Führungskräfte sowie zum betriebswirtschaftlichen Dienstleister einer IHK-Organisation und deren Kunden. Ein Kunden- und Leistungs-Controlling auf Basis einer neuen Business-Intelligence Lösung bildet dabei ein wesentliches Instrument der Informationsversorgung.
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Mazzucchi, Nicolas. „Intelligence artificielle et industrie de défense, le grand défi“. Revue Défense Nationale N° 820, Nr. 5 (01.05.2019): 86–92. http://dx.doi.org/10.3917/rdna.820.0086.

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3

Jarmoun, A., S. Messaoud, A. Mountassir, S. El Hilali, A. Abeydi Taleb, Z. Zeghari, R. Razine und M. Obtel. „P34 - Intelligence artificielle et industrie pharmaceutique - De nouveaux défis pour des nouvelles innovations“. Journal of Epidemiology and Population Health 72 (Mai 2024): 202474. http://dx.doi.org/10.1016/j.jeph.2024.202474.

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4

Thoben, Klaus-Dieter, Stefan Wiesner und Thorsten Wuest. „“Industrie 4.0” and Smart Manufacturing – A Review of Research Issues and Application Examples“. International Journal of Automation Technology 11, Nr. 1 (05.01.2017): 4–16. http://dx.doi.org/10.20965/ijat.2017.p0004.

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A fourth industrial revolution is occurring in global manufacturing. It is based on the introduction ofInternet of thingsandservitizationconcepts into manufacturing companies, leading to vertically and horizontally integrated production systems. The resultingsmart factoriesare able to fulfill dynamic customer demands with high variability in small lot sizes while integrating human ingenuity and automation. To support the manufacturing industry in this conversion process and enhance global competitiveness, policy makers in several countries have established research and technology transfer schemes. Most prominently, Germany has enacted itsIndustrie 4.0program, which is increasingly affecting European policy, while the United States focuses onsmart manufacturing. Other industrial nations have established their own programs on smart manufacturing, notably Japan and Korea. This shows that manufacturing intelligence has become a crucial topic for researchers and industries worldwide. The main object of these activities are the so-called cyber-physical systems (CPS): physical entities (e.g., machines, vehicles, and work pieces), which are equipped with technologies such as RFIDs, sensors, microprocessors, telematics or complete embedded systems. They are characterized by being able to collect data of themselves and their environment, process and evaluate these data, connect and communicate with other systems, and initiate actions. In addition, CPS enabled new services that can replace traditional business models based solely on product sales. The objective of this paper is to provide an overview of the Industrie 4.0 and smart manufacturing programs, analyze the application potential of CPS starting from product design through production and logistics up to maintenance and exploitation (e.g., recycling), and identify current and future research issues. Besides the technological perspective, the paper also takes into account the economic side considering the new business strategies and models available.
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Barlow, Julie. „Comment les humains battront-ils les machines ?“ Gestion Vol. 48, Nr. 3 (31.08.2023): 84–88. http://dx.doi.org/10.3917/riges.483.0084.

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L’intelligence artificielle mènera-t-elle l’humanité au désastre ou vers des lendemains qui chantent ? Voilà l’idée sous-jacente derrière la Déclaration de Montréal pour un développement responsable de l’intelligence artificielle, signée par plus de 2 000 personnalités du monde de la technologie. En mars 2023, la question a incité plus de 1 000 sommités à signer une pétition demandant à l’industrie de décréter un moratoire de six mois sur la formation des systèmes d’intelligence artificielle (IA).
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Nakao, Yohichi, und Hayato Yoshioka. „Special Issue on the Latest Machine Tool Technologies and Manufacturing Processes“. International Journal of Automation Technology 13, Nr. 5 (05.09.2019): 573. http://dx.doi.org/10.20965/ijat.2019.p0573.

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With the 2011 launch of Industrie 4.0, a German project aiming to promote the computerization of manufacturing, the integration of physical or actual manufacturing systems with cyber-physical systems (CPS) using various technologies, such as the Internet of things (IoT), industrial Internet of things (IIOT), and artificial intelligence, is considered to be more important than ever before. One of the goals of the Industrie 4.0 is to realize smart factories or smart manufacturing using advanced digital technologies. However, the core component in the manufacturing systems is still machine tools. This special issue, composed of eleven excellent research papers, focuses on the latest research advances in machine tools and manufacturing processes. It covers various topics, including machine tool control, tool path generation for multi-axis machining, and machine tool components. Furthermore, this special issue includes innovative machining technologies, including not only cutting and grinding processes but also the EDM process and burnishing process connected effectively with force control techniques. All the research contributions were presented at IMEC2018, a joint event with JIMTOF2018, held in Tokyo, Japan in 2018. The editors would like to sincerely thank the authors for their dedication and for their well written and illustrated manuscripts. We are also profoundly grateful for the efforts of all the reviewers who ensured their quality. Finally, we sincerely hope that studies on machine tools and related manufacturing technologies will further contribute to the development of our global society.
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Uhl, Joachim, und Tim Siebels. „Für effiziente und sichere industrielle Produktion/MagnOtrop – Three-dimensional magnet-field-based object and motion tracking“. wt Werkstattstechnik online 111, Nr. 09 (2021): 607–11. http://dx.doi.org/10.37544/1436-4980-2021-09-33.

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Im Umfeld von Industrie 4.0 halten die modernen Informationstechnologien immer stärker Einzug. Dabei sind Schlüsseltechnologien wie zum Beispiel künstliche Intelligenz (KI) oder Artificial Reality (AR) für sich allein genommen im industriellen Praxiseinsatz nur sehr bedingt verwendbar. Den Schlüssel zum Erfolg liefert vielmehr die Vernetzung dieser modernen Technologien sowohl untereinander als auch mit dem humanen Bedienpersonal durch Algorithmen und Systeme zur Mensch-Maschine-Kollaboration (MMK).   In modern times of Industry 4.0 innovative technologies become more and more important, but key-technologies like Artificial Intelligence (AI) and Artificial Reality (AR) need to be combined in the practical field of human working processes. The key to success is delivered by Man-Machine-Collaboration (MMC) algorithms and systems.
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Knell, Mark. „The digital revolution and digitalized network society“. Review of Evolutionary Political Economy 2, Nr. 1 (13.02.2021): 9–25. http://dx.doi.org/10.1007/s43253-021-00037-4.

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AbstractThis lecture discusses technological revolutions and techno-economic paradigms, but with an emphasis on the digital revolution and the digitalization of the economic and society. It draws its inspiration from works of Joseph Schumpeter, Christopher Freeman, and Carlota Perez on long waves of technological development and places the story within the context of global innovation networks. The lecture contends that the digital revolution not only transformed the world we live in but also created new ways to organize networks within it. We are now in second half of the digital (fifth technological) revolution, when the digitalization of the global networked economy prevails, and not at the beginning of Industrie 4.0. On the contrary, this is the period when economic growth drives the use of innovative digital technologies, including ubiquitous computing, robotics, and artificial intelligence, toward a truly digitalized network society.
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ITO, Yoshimi. „Layout design for flexible machining systems in FCIPS and convertibility to CPS module in smart factory“. Journal of Machine Engineering 4, Nr. 17 (12.12.2017): 5–28. http://dx.doi.org/10.5604/01.3001.0010.7000.

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Although being not in accordance with the original concept proposed in the “Industrie 4.0”, the smart factory has been gradually applied to the practice. In contrast, we can observe that nearly all discourses, suggestions and discussions have been carried out without considering the convertibility of flexible manufacturing in FCIPS (Flexible Computer-Integrated Production Structure), which is the utmost leading facility within the industrial nation, to the CPS (Cyber Physical Systems) module in the smart factory. Admitting the powerful potentiality of the smart factory, at crucial issue is to discuss to what extent and how the technological and human resources so far accumulated in FCIPS are available for the smart factory. This paper proposes, first, the conceptual drawing of the smart factory on the basis of the concept of FCIPS, and then suggests the similarity of both the concepts. In fact, the smart factory consists of cloud computing, information communication network and CPS modules, whereas FCIPS consists of CIM, information communication network and a group of FMCs (Flexible Manufacturing Cells). Then, the paper describes the present and near future perspectives of the CPS module and FMC, especially placing the stress on machining, and asserts the convertibility of FMC for “One-off Production with Keen Machining Cost” to the CPS module. Finally, the paper summarizes the research and engineering development subjects in FCIPS and the smart factory necessary to be investigated hereafter together with detailing one leading subject, i.e. methodology to incorporate the human-intelligence into CIM.
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Thilmany, Jean. „Digital World Spawns Identical Twins“. Mechanical Engineering 139, Nr. 10 (01.10.2017): 32–37. http://dx.doi.org/10.1115/1.2017-oct-1.

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This article explores the concept of digital twins and reasons why manufacturers prefer digital replicas of products, machines, processes, or even entire factories. A digital twin models the robotic line with such high fidelity that the engineer can do all this in the virtual world. Digital twins are the foundation of tomorrow’s smarter workplace. A factory’s digital twin must be robust enough to capture those changes, plus all relevant data from each operation. Smart factories, such as GE’s Brilliant Factory and Siemens’ competing Industrie 4.0, need both types of digital twins—product and process—to work. Digital product models contain each component that goes into a product, from screws and welds to plastic shapes and machined metals. Digital twins also support greater automation. As artificial intelligence (AI) systems learn more about specific machines, they will use their digital twins to help engineers run plants more efficiently. AI can analyze it to see if a screw is loose or a bearing is starting to fail. The better the AI knows the machine, the more accurately it can predict when that failure is likely to happen.
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Dissertationen zum Thema "Intelligence – Industrie"

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Schoebel, David. „Multikriterielle Gestaltung von pharmazeutischen Wirkstoffanlagen der Einsatz von computational intelligence im strategischen Anlagencontrolling“. Wiesbaden Gabler, 2007. http://d-nb.info/989360660/04.

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Touzani, Hicham. „Planification Multi-Robot du Problème de Répartition de Tâches avec Évitement Automatique de Collisions et Optimisation du Temps de Cycle : Application à la Chaîne de Production Automobile“. Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST079.

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Dans l’industrie automobile, plusieurs robots sont nécessaires pour réaliser simultanément des séquences de soudage sur un même véhicule. L’attribution et la coordination des tâches de soudage entre les robots est une phase manuelle et exigeante qui doit être optimisée à l’aide d’outils automatiques. Le temps de cycle de la cellule dépend fortement de différents facteurs robotiques tels que la répartition des tâches entre les robots, les solutions de configuration et l’évitement d’obstacles. De plus, un aspect clé, souvent négligé dans l’état de l’art, est de définir une stratégie pour résoudre le séquencement des tâches robotiques avec une intégration efficace de l’évitement de collisions robot-robot. Cette thèse est motivée par la résolution de ce problème industriel et cherche à relever différents défis de recherche. Elle commence par présenter les solutions de pointe actuelles en matière de planification robotique. Une enquête approfondie est menée sur les solutions académiques/industrielles existantes pour résoudre le problème de répartition des tâches robotiques, en particulier pour les systèmes multi-robot. Cette enquête permet d’identifier les défis lors de l’intégration de plusieurs facteurs robotiques dans le processus d’optimisation. Cette thèse présente un algorithme itératif efficace qui génère une solution de haute qualité pour le problème de répartition de tâches multi-robot. Ce dernier gère non seulement les facteurs robotiques mentionnés, mais également les aspects liés aux contraintes d’accessibilité et à l’évitement de collisions mutuelles. De plus, un planificateur fait maison (RoboTSPlanner) gérant des robots à six axes a été validé dans un scénario de cas réel. Afin d’assurer l’exhaustivité de la méthodologie proposée, nous effectuons une optimisation dans l’espace des tâches, de configuration et de coordination de manière synergique. Par rapport aux approches existantes, la simulation comme les expérimentations réelles révèlent des résultats positifs en termes de temps de cycle et montrent la capacité de cette méthode à s’interfacer à la fois avec les logiciels de simulation industrielle et les outils ROS-I
In the automotive industry, several robots are required to simultaneously carry out welding sequences on the same vehicle. Assigning and coordinating welding tasks between robots is a manual and challenging phase that must be optimized using automatic tools. The cycle time of the cell strongly depends on different robotic factors such as the task allocation among the robots, the configuration solutions, and obstacle avoidance. Moreover, a key aspect, often neglected in the state-ofthe- art, is to define a strategy to solve the robotic task sequencing with an effective robot-robot collision avoidance integration. This thesis is motivated by solving this industrial problem and seeks to raise different research challenges. It begins by presenting the current state-of-the-art solutions regarding robotic planning. An in-depth investigation is carried out on the related existing academic/industrial solutions to solve the robotic task sequencing problem, particularly for multi-robot systems. This investigation helps identify the challenges when integrating several robotic factors into the optimization process. An efficient iterative algorithm that generates a high-quality solution for the Multi-Robotic Task Sequencing Problem is presented. This algorithm manages not only the mentioned robotic factors but also aspects related to accessibility constraints and mutual collision avoidance. In addition, a home-developed planner (RoboTSPlanner) handling six-axis robots has been validated in a real case scenario. In order to ensure the completeness of the proposed methodology, we perform optimization in the task, configuration, and coordination space in a synergistic way. Compared to the existing approaches, both simulation and real experiments reveal positive results in terms of cycle time and show the ability of this method to be interfaced with both industrial simulation software and ROS-I tools
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Dries, Monique Henriette van den. „Archaeology and the application of artificial intelligence : case-studies on use-wear analysis of prehistoric tools /“. Leiden : University of Leiden, Faculty of archaeology, 1998. http://catalogue.bnf.fr/ark:/12148/cb37069588c.

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Mkhida, Abdelhak Aubry Jean-François Thiriet Jean-Marc. „Contribution à l'évaluation de la sûreté de fonctionnement des Systèmes Instrumentés de Sécurité à Intelligence Distribuée“. S. l. : S. n, 2008. http://www.scd.inpl-nancy.fr/theses/2008_MKHIDA_A.pdf.

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Konate, Mathy. „La mise en place d'une cellule d'Intelligence Économique en Côte d'Ivoire : cas du secteur touristique“. Thesis, Brest, 2015. http://www.theses.fr/2015BRES0041.

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La mise en place d’une cellule d’Intelligence économique en Côte d’Ivoire, Cas du secteur touristique. Cette thèse porte sur la mise en place d’une cellule d’Intelligence économique en Côte d’Ivoire compte tenu des spécificités culturelles et organisationnelles de ce pays, notamment en matière d’informations. Elle s’intéresse particulièrement au secteur de l’industrie touristique de la Côte d’Ivoire. L'IE fait aujourd'hui partie intégrante de l'économie mondiale fondée sur l'économie du savoir, elle fait de l'information le maillon central de la chaine et permet aux organisations de déceler les opportunités de croissance tout en se protégeant d'éventuelles menaces. Le concept, né au sein de grands groupes issus des pays développés, ne peut souvent pas être appliqué tel quel aux petites et moyennes organisations et encore moins à celles des pays du tiers monde. La Côte d'ivoire peinant à sortir de la crise ainsi que des importants désordres structurels et organisationnels qui minent son économie, a du mal à trouver sa place au sein de cette « nouvelle » culture collective de l'information. Notre démarche consistera, sur la base d'entretiens préalables à toute analyse, à établir un modèle méso économique de cellule d'IE viable en Côte d'ivoire. Sur un plan méthodologique, cette thèse s’articule après une revue de la littérature, à la sélection d’un échantillon de 10 entreprises de l’industrie touristique ivoirienne dans une démarche qualitative reposant sur des entretiens semi-directifs. Elle se décompose en six chapitres, proposant l’aller du général au particulier. Ainsi, le chapitre premier de cette étude propose de comprendre les fondements de l’intelligence. Tandis que le chapitre II s’intéresse à l’IE dans son approche fonctionnelle et que le chapitre III s’intéresse aux PME ainsi qu’à leur pratique de l’IE notamment dans le contexte du sous développement. Dans un second temps, les chapitre 4, 5 et 6 proposent d’approfondir notre étude en effectuant l’état des lieux de l’économie de la connaissance au sein du contexte particulier d’un pays tel que la Côte d’Ivoire mais également du secteur particulier de notre étude, à savoir, l’industrie touristique ivoirienne. S’ensuit la mise en exergue de facteurs clés de succès de l’IE au sein de l’entreprise ivoirienne appuyée par le cas pratique portant sur l’échantillon sélectionné. Ces travaux permettent la mise en relief les attentes et les besoins des acteurs d’un secteur donné en matière d’IE et d’aboutir à une série d’actions à réaliser pour la pratique de l’IE dans le contexte ivoirien, au sein de l’activité choisie. Dans une logique réplicative, ce plan de mise en œuvre pourra être appliqué à l’ensemble des secteurs sur la base des attentes des acteurs de ceux-ci
This thesis focuses on the establishment of an economic Intelligence in Côte d'Ivoire given cell specificities cultural and organizational of this country, particularly with regard to information. It is particularly interested in the sector of the tourism industry in Côte d'Ivoire. Business Intelligence is today part integral of the world economy based on the knowledge economy, it is the central link in the chain information and enables organizations to identify growth opportunities while protecting any threats. The concept, born within large groups of developed countries, often cannot be applied as to small and medium-sized organizations and even less to those of the countries of the third world. Côte d'Ivoire struggling to get out of the crisis and important organizational and structural disorders that undermine its economy, has difficulties to find its place in this 'new' collective culture of the information era. Our approach will be based on prior interviews to any analysis, to establish a model meso economic IE cell viable in Côte d'Ivoire. On a methodological level, this thesis is structured after a review of the literature, to the selection of a sample of 10 companies of the Ivorian tourism industry in a qualitative approach based on semi-structured interviews. It breaks down into six chapters, offering the go from the general to the particular. These work highlighted the expectations and needs of the actors in a given area in Business Intelligence and lead to a series of actions to achieve for the practice of Business Intelligence in the Ivorian context, within the chosen activity. In replicative logic, this implementation plan can be applied to all the sectors on the basis of the expectations of the actors
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Alexandre, Laurice. „Les pratiques du portage commercial à l'international : le rôle des stratégies de contre-intelligence économique et stratégique“. Lyon 3, 2001. http://www.theses.fr/2001LYO33007.

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Le portage commercial est un mode d'entrée à l'international. Il concerne principalement deux partenaires. Le premier (dans la plus part des cas un groupe), prête son circuit de distribution, à l'autre partenaire (dans la plus part des cas une PME), dans le but de lui faciliter l'accès aux marchés où le groupe possède des filiales. Ce partenariat exige une transparence totale de la part des deux partenaires, et une présence physique de l'entreprise porteuse à l'étranger. Cette réalité nous a poussé à penser que les pratiques de l'intelligence économique peuvent être dangereuses pour ce type de partenariat, notamment pour l'entreprise porteuse. Dans ce sens, il nous a paru intéressant de découvrir les stratégies de contre-intelligence économique adoptées par les groupes à cet effet. Trois étapes caractérisent notre recherche : la première étape consiste à approfondir la connaissance des difféentes formes du portage, ses avantages et ses inconvénients, etc. . . Dans le but de mieux comprendre les pratiques de l'intelligence économique, nous allons effectué une recherche-action au sein d'une cellule d'intelligence économique. Cette expérience a confirmé l'existence des risques dans le cadre du portage. Nous avons alors mené une troisième recherche auprès des groupes porteurs, des différentes administrations concernées par la promotion du portage, ou par la sensibilisation à la sûreté, mais aussi auprès de responsables sûreté au sein des groupes. Cette recherche nous a montré que tous les groupes pratiquent la contre-intelligence économique appelée souvent sûreté. Ces pratiques se résument à des aspects juridiques comme le contrat de clauses de confidentialité ou de non concurrence, ou encore les brevets. Sur un plan technique, nous évoquons la classification de l'information, la cryptologie. Sur le plan informatique, nous citons l'exemple du changement de mots de passe permanent, etc. . .
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Argerich, martin Clara. „Etude et développement de nouvelles technologies acoustiques pour nacelle produits“. Thesis, Paris, HESAM, 2020. http://www.theses.fr/2020HESAE019.

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Cette thèse visite toutes les étapes qui participent à la conception d'une nouvelle technologie du point de vue de l'industrie 4.0, où les approches fondées sur les données et les techniques d'intelligence artificielle deviennent de plus en plus pointues. L'objectif de cette thèse est d'établir les outils qui peuvent aider à concevoir et à fabriquer plus rapidement les nouvelles technologies en cours de développement. Tout d'abord, les procédés de fabrication sont un sujet brûlant de la thèse. La fabrication de revêtements acoustiques pour les nacelles sera présentée et l'utilisation des techniques d'intelligence artificielle pour optimiser un processus de formage de composites sera mise en évidence. Pour cette thèse, un nouvel algorithme appelé "Code2Vect" est présenté pour surmonter deux défis : la visualisation des données en haute dimension et la régression dans la limite des données en basse dimension. Globalement, toutes les étapes de la conception et de la mise en œuvre de nouvelles technologies dans l'industrie seront analysées du point de vue de l'intelligence artificielle
This Phd visits all the stages taking part in the conception of a new technology from the industry 4.0 point of view, where data-driven approaches and artificial intelligence techniques are becoming leading edge. The objective of this dissertation is to establish the tools that can help design and manufacture faster new technologies in development. First of all, manufacturing processes are a hot-topic of the dissertation. The manufacturing of acoustic liners for nacelles will be presented and the use of artificial intelligence techniques for optimizing a composite forming process will be highlighted. For this dissertation a new algorithm called ‘Code2Vect’ is presented to overcome two challenges: visualization of high-dimensional data and regression in the low-data limit. Overall, all the stages involving the design and implementation of new technologies in the industry will be analyzed from an artificial intelligence point of view
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Harroussi, Siham. „Systèmes de veille stratégique basé sur un réseau d'experts : méthodes et outils“. Aix-Marseille 3, 2004. http://www.theses.fr/2004AIX30016.

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Ce mémoire a porté sur l'étude des besoins des acteurs verriers en matière d'information élaborée ainsi que sur l'étude des outils et moyens nécessaires pour la mise en place d'un système de veille stratégique couvrant l'ensemble des secteurs de l'industrie du verre en s'appuyant sur un réseau d'experts. La stratégie adoptée consiste dans un premier temps à sensibiliser les différents acteurs de la veille, en visant plus particulièrement deux acteurs dont la participation est vitale pour la réussite de ce système : les experts (pertinence des études) et les décideurs (étude des besoins). Ensuite, une stratégie-réseau a été étudiée pour impliquer des experts externes dans le processus de veille afin de capitaliser leurs savoir et compétences. Grâce à l'appui du Ministère de l'Economie, des Finances et de l'Industrie au système de veille mis en place, un portail pour l'industrie du verre française a été créé pour assurer le partage et la diffusion d'informations stratégiques sur le secteur
This report presents a study of the needs for the glass industry's actors in terms of elaborated informations and also the necessary tools and means for setting up a strategic watch system covering the glass industry as a whole and based on an experts network. The adopted strategy initially consists in sensitizing the different actors participating in the strategic watch system, by aiming more particularly two actors whose participation is vital for the success of this system: experts (to ensure relevance and value-added to the stategic watch studies) and decision makers (to study the needs and to create demand). Then, a strategy-network was set up, implicating external experts in the strategic watch process in order to capitalize their knowledge and competences. Thanks to the support of the Ministry of Economy, Finances and Industry, to the strategic watch system set up, the first french glass industry's Internet portal was created so as to ensure sharing and diffusion of strategic informations on the glass sector
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Jain, Sheenam. „Big data management using artificial intelligence in the apparel supply chain : opportunities and challenges“. Thesis, Lille 1, 2020. http://www.theses.fr/2020LIL1I051.

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L’industrie de l'habillement a bénéficié, au cours de la dernière décennie, de l'application de big data et de l'intelligence artificielle pour résoudre divers problèmes commerciaux. Face à la concurrence accrue sur le marché et aux attentes des clients en matière de personnalisation, ces industriels sont en permanence à la recherche des moyens d'améliorer leurs stratégies commerciales afin d'accroître leur rapidité et leur rentabilité. A cet égard, les solutions de gestion de big data offrent aux enseignes de la distribution textile la possibilité d'explorer leur chaîne d'approvisionnement et d'identifier les ressources de données importantes. Ces ressources précieuses, rares et inimitables permettent de créer des stratégies axées sur les données (data-driven) et d'établir des capacités dynamiques à maintenir dans un environnement commercial incertain. Grâce à ces stratégies data-driven, les enseignes de prêt-à-porter sont en mesure de confectionner des vêtements de façon intelligente afin de fournir à leurs clients un article adapté à leurs besoins et, par conséquent, d'adopter des pratiques de consommation et de production durables.Dans ce contexte, la thèse étudie les avantages de l'utilisation de big data et de l'intelligence artificielle (IA) dans les entreprises de l'habillement, afin d'améliorer leurs opérations commerciales tout en recherchant des opportunités de gestion de big data à l'aide de solutions d'IA. Dans un premier temps, cette thèse identifie et classifie les techniques d'IA qui peuvent être utilisées à différents stades de la chaîne d'approvisionnement pour améliorer les opérations commerciales existantes. Dans un deuxième temps, des données relatives aux produits sont présentées afin de créer un modèle de classification et des règles de conception susceptibles de fournir des recommandations personnalisées ou une personnalisation permettant une meilleure expérience d'achat pour le client. Dans un troisième et dernier temps, la thèse s'appuie sur les évidences de l'industrie de l'habillement et la littérature existante pour suggérer des propositions qui peuvent guider les responsables dans le développement de stratégies data-driven pour améliorer la satisfaction du client par des services personnalisés. Enfin, cette thèse montre l'efficacité des solutions analytiques basées sur les données pour maintenir un avantage concurrentiel grâce aux données et aux connaissances déjà présentes dans une chaîne d'approvisionnement de l'habillement. Plus précisément, cette thèse contribue au domaine textile en identifiant des opportunités spécifiques de gestion de big data à l'aide de solutions d'intelligence artificielle. Ces opportunités peuvent être une source de référence pour d'autres travaux de recherche dans le domaine de la technologie et de la gestion
Over the past decade, the apparel industry has seen several applications of big data and artificial intelligence (AI) in dealing with various business problems. With the increase in competition and customer demands for the personalization of products and services which can enhance their brand experience and satisfaction, supply-chain managers in apparel firms are constantly looking for ways to improve their business strategies so as to bring speed and cost efficiency to their organizations. The big data management solutions presented in this thesis highlight opportunities for apparel firms to look into their supply chains and identify big data resources that may be valuable, rare, and inimitable, and to use them to create data-driven strategies and establish dynamic capabilities to sustain their businesses in an uncertain business environment. With the help of these data-driven strategies, apparel firms can produce garments smartly to provide customers with a product that closer meets their needs, and as such drive sustainable consumption and production practices.In this context, this thesis aims to investigate whether apparel firms can improve their business operations by employing big data and AI, and in so doing, seek big data management opportunities using AI solutions. Firstly, the thesis identifies and classifies AI techniques that can be used at various stages of the supply chain to improve existing business operations. Secondly, the thesis presents product-related data to create a classification model and design rules that can create opportunities for providing personalized recommendations or customization, enabling better shopping experiences for customers. Thirdly, this thesis draws from the evidence in the industry and existing literature to make suggestions that may guide managers in developing data-driven strategies for improving customer satisfaction through personalized services. Finally, this thesis shows the effectiveness of data-driven analytical solutions in sustaining competitive advantage via the data and knowledge already present within the apparel supply chain. More importantly, this thesis also contributes to the field by identifying specific opportunities with big data management using AI solutions. These opportunities can be a starting point for other research in the field of technology and management
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Flamand, Marina. „Le déploiement de l'intelligence technologique dans le processus d'innovation des firmes : quels objectifs, enjeux et modalités pratiques ? : Une application à l'industrie automobileu“. Thesis, Bordeaux, 2016. http://www.theses.fr/2016BORD0083/document.

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Confrontées à des environnements d’affaires toujours plus turbulents, les firmes doiventredoubler d’efforts pour se doter de moyens leur permettant de se saisir pleinement de ces évolutions.L’intelligence technologique, en tant que vecteur de connaissances sur les dynamiques d’innovation,constitue un instrument au service des firmes afin d’orienter leurs activités économiques.L’enjeu de cette thèse, financée par le Groupe PSA, est de participer au renforcement des pratiquesd’intelligence technologique d’un grand groupe industriel.La première partie de cette thèse vise à rendre l’intelligence technologique plus intelligible afind’asseoir la légitimité de son intégration effective dans les processus des firmes. Pour cela, nousmobilisons les éléments théoriques du référentiel des ressources et compétences de la firme afind’apporter des éléments de réponse à trois problématiques. Pourquoi la compréhension del’environnement externe relève d’une nécessité pour la firme ? Quel statut au sein de la firme octroyerà cette aptitude de compréhension ? Et enfin, quels sont les apports concrets de l’intelligencetechnologique pour le management stratégique et opérationnel de l’innovation ?L’opérationnalisation de l’intelligence technologique est au coeur de la seconde partie de cette thèsequi s’attache à améliorer les pratiques de collecte de matériaux informationnels sur l’environnementexterne. Plus précisément, elle ambitionne non seulement de déterminer l’apport informationnel desdonnées brevet et de données actuellement peu exploitées, à savoir les données financières, maiségalement de formuler des recommandations opérationnelles pour leur exploitation
Challenged by turbulent environment, firms are driven to make extra efforts in order tothrive. Technology intelligence, as a vector of knowledge of innovation dynamics, constitutes aninstrument at the firms’ disposal to help steer their economic activities.The aim of this thesis, funded by Groupe PSA, is to participate in the enhancement of theimplementation of technology intelligence within large industrial groups.The first part of this Ph.D. thesis aims at making technology intelligence more comprehensible inorder to reinforce its purposes in the innovation process of firms.To this end, we will call upon theoretical elements from the resources and competencies based view ofthe firm in order to answer three questions: Why is the understanding of the external environment ofthe firm a necessity? What is its place within the organization of the firm? What is the significance oftechnological intelligence for strategic and operational management of innovation?By putting technology intelligence into practice, the second part of this thesis focuses on improvingcollection methods of data required for the analysis of the external environment of the firm. Moreprecisely, the intent is not only to determine the informational benefits of patent data and the seldomused financial data, but also to make practical recommendations for their exploitation
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Bücher zum Thema "Intelligence – Industrie"

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Rubinger, Bruce. Applied artificial intelligence in Japan: Current status, key research and development performers, strategic focus. New York: Hemisphere Pub. Corp., 1988.

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author, Ch'oe Chae-yong, und Yang Sŏng-gil author, Hrsg. 4-ch'a sanŏp hyŏngmyŏng why?: Industry 4.0. Sŏul T'ŭkpyŏlsi: Han'guk Kyŏngje Sinmun i, 2018.

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Fernandes, Steven Lawrence, und Tarun K. Sharma, Hrsg. Artificial Intelligence in Industrial Applications. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-85383-9.

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Masrour, Tawfik, Anass Cherrafi und Ibtissam El Hassani, Hrsg. Artificial Intelligence and Industrial Applications. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-51186-9.

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Masrour, Tawfik, Ibtissam El Hassani und Anass Cherrafi, Hrsg. Artificial Intelligence and Industrial Applications. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-53970-2.

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International Conference on Computational Intelligence and Industrial Engineering (2014). Computational Intelligence and Industrial Engineering. Herausgegeben von Wang, Tingting (Tina Tingting), editor. Southampton: WIT PRESS, 2015.

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Masrour, Tawfik, Hassan Ramchoun, Tarik Hajji und Mohamed Hosni, Hrsg. Artificial Intelligence and Industrial Applications. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43520-1.

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Masrour, Tawfik, Ibtissam El Hassani und Noureddine Barka, Hrsg. Artificial Intelligence and Industrial Applications. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43524-9.

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Produzione intelligente: Un viaggio nelle nuove fabbriche. Torino: Einaudi, 2014.

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Stevan, Dedijer, und Jéquier Nicolas 1941-, Hrsg. Intelligence for economic development: An inquiry into the role of the knowledge industry. Leamington Spa, [Warwickshire]: Berg, 1987.

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Buchteile zum Thema "Intelligence – Industrie"

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Knoll, Thomas, Alexander Lautz und Nicolas Deuß. „Machine-To-Machine Communication: From Data To Intelligence“. In Handbuch Industrie 4.0 Bd.3, 347–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-53251-5_84.

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Hänel, Tom, und Carsten Felden. „Operational Business Intelligence im Zukunftsszenario der Industrie 4.0“. In Analytische Informationssysteme, 259–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47763-2_13.

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Mangelsdorf, Axel, Nicole Wittenbrink und Peter Gabriel. „Regulierung und Zertifizierung von KI in der Industrie: Ziele, Kriterien und Herausforderungen“. In Digitalisierung souverän gestalten II, 110–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-64408-9_9.

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ZusammenfassungMit dem Vorschlag der Europäischen Kommission zur Regulierung von Künstlicher Intelligenz (dem Artificial Intelligence Act) ist die Zertifizierung von KI-Systemen in den Fokus gerückt. Gleichzeitig werden mit der Veröffentlichung der ersten Prüfkriterien die Anforderungen der Zertifizierung für Unternehmen konkreter. Der vorliegende Beitrag stellt den Regulierungsvorschlag der Kommission vor und fasst die dazugehörige Fachdebatte zusammen. Danach werden die Anforderungen eines Prüfkatalog zur Zertifizierung von KI-Systemen anhand eines ersten Vorschlags aus dem Projekt „Zertifizierte KI“ präsentiert und bewertet.
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Buła, Piotr, und Bartosz Niedzielski. „Industrial revolution – from Industry 1.0 to Industry 4.0“. In Management, Organisations and Artificial Intelligence, 1–34. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003184027-1.

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Zäh, Michael, Philipp Rinck, Sebastian Pieczona, Eva Schaupp, Thomas Grosch, Eberhard Abele und Joachim Metternich. „Das intelligente Werkzeug“. In Handbuch Industrie 4.0, 323–40. München: Carl Hanser Verlag GmbH & Co. KG, 2017. http://dx.doi.org/10.3139/9783446449893.013.

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Zäh, Michael, Philipp Rinck, Sebastian Pieczona, Eva Schaupp, Eva Schaupp, Thomas Grosch, Eberhard Abele und Joachim Metternich. „Das intelligente Werkzeug“. In Handbuch Industrie 4.0, 323–40. München, Germany: Carl Hanser Verlag GmbH & Co. KG, 2017. http://dx.doi.org/10.1007/978-3-446-44989-3_13.

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Bedi, Pradeep, S. B. Goyal, Anand Singh Rajawat, Jugnesh Kumar, Shilpa Malik und Lakshmi C. Radhakrishnan. „Industry Revolution 4.0: From Industrial Automation to Industrial Autonomy“. In Computational Intelligence for Modern Business Systems, 321–56. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-5354-7_17.

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Bogner, Eva, Christopher Kästle, Jörg Franke und Gunther Beitinger. „Intelligent vernetzte Elektronikproduktion“. In Handbuch Industrie 4.0, 653–90. München: Carl Hanser Verlag GmbH & Co. KG, 2017. http://dx.doi.org/10.3139/9783446449893.024.

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Bogner, Eva, Christopher Kästle, Jörg Franke und Gunther Beitinger. „Intelligent vernetzte Elektronikproduktion“. In Handbuch Industrie 4.0, 653–90. München, Germany: Carl Hanser Verlag GmbH & Co. KG, 2017. http://dx.doi.org/10.1007/978-3-446-44989-3_24.

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Vermeulen, Andreas François. „Industrialized Artificial Intelligence“. In Industrial Machine Learning, 533–56. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5316-8_14.

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Konferenzberichte zum Thema "Intelligence – Industrie"

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Sakurada, Lucas, Paulo Leitão, Fernando De la Prieta und Juan M. Corchado. „Multi-Agent Systems to Realize Intelligent Asset Administration Shells“. In Proceedings of the III Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation: 18th December 2020 Online. Ediciones Universidad de Salamanca, 2022. http://dx.doi.org/10.14201/0aq03114358.

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The digital transformation driven by the fourth industrial revolution is promoting the transition of traditional manufacturing systems towards flexible, reconfigurable and intelligent factories based on Cyber- Physical Systems (CPS), bringing new opportunities and innovative solutions for modern manufacturing systems. However, this condition imposes complex planning across the production chain and lifecycle of the industry. In this context, the Reference Architecture Model Industrie 4.0 (RAMI4.0) provides guidelines to develop Industry 4.0 (I4.0) compliant solutions based on industrial standards. As the main specification of RAMI4.0, the Asset Administration Shell (AAS) is a standardized digital representation of an asset that represents an object of value for the industry. This paper discusses how Multi-Agent Systems (MAS) technology can be used to realize the AAS, mapping their inherits characteristics into AAS functionalities and also extending them, introducing intelligence and data analytics capabilities.
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Luhn, Gerhard, Dirk Habich, Katrin Bartl, Johannes Postel, Travis Stevens und Martin Zinner. „Real-Time Information Base as key enabler for Manufacturing Intelligence and “Industrie 4.0”“. In 2015 26th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC). IEEE, 2015. http://dx.doi.org/10.1109/asmc.2015.7164474.

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Adjogble, Franck Komi, Joachim Warschat und Matthias Hemmje. „Advanced Intelligent Manufacturing in Process Industry Using Industrial Artificial Intelligence“. In 2023 Portland International Conference on Management of Engineering and Technology (PICMET). IEEE, 2023. http://dx.doi.org/10.23919/picmet59654.2023.10216797.

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Emuowhochere, Oghenevwegba T., Enesi Y. Salawu, Samson O. Ongbali und Oluseyi O. Ajayi. „Future of Artificial Intelligence in Developing a Sustainable Intelligent Engineering Systems: A Review“. In 2023 International Conference on Sustainable Engineering and Materials Development. Switzerland: Trans Tech Publications Ltd, 2024. http://dx.doi.org/10.4028/p-0wnidr.

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Studying the behaviour of engineering systems and processes from the perspective of applications of artificial intelligence provides an invaluable reference to improve their productivity and industrial development at large. This study comprehensively unveiled the problems faced by engineering systems and how artificial intelligence could be deployed as a technique for the future advancement of the industry. A brief background of the application of artificial intelligence in some selected engineering fields revealed that insufficient operational and process data from both plants and processes are major problems causing the survival of sustainable intelligent systems thereby, leading to incessant system failure. Furthermore, it was equally discovered that artificial intelligent for specific application are based on the data obtained from such application. Thus, there is no universally agreed artificial intelligent for a specific application. This made it a bit complex in developing intelligent systems. Keywords: Artificial Neural Network, Applications, Engineering, Training, Data.
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Chen, Shuzhi, Meiliang Huang, Qimeng Shen, Jie Chen, Xiaoqiang Liu, Junli Wang, Weidong Wang und Yueming Fu. „Feasibility Analysis of Intelligent Instrument Application In Nuclear Power“. In 2022 29th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/icone29-93298.

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Abstract To achieve the in-depth combination of informatization and intelligence has become a development trend in the nuclear power industry, and the digitization/intelligence of instrumentation is a big part. Based on the technical status of nuclear power instruments and industrial integrated circuits, this paper analyzes the feasibility and suggestions of intelligent/digital instrument application for nuclear power plant by combing the environmental conditions of nuclear power, intelligence/digitization of typical meters, testing and verification etc. basic work.
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Guerra-Zubiaga, David, Logan Block, Adam Ricketts, Jacob Faile und Charlie Dickson. „A New Approach to Develop an Intelligent Robotic Gripper Using Virtual Tools Implementing IIoT and ML Technologies“. In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-69993.

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Abstract Industrial manufacturing companies face the challenge of adapting to increasingly complex demands, especially with the influx of online ordering. One case of this is in the underperformance of end-effectors, limiting the adaptability of robotic arms in manufacturing functionality. To create proper gripper adaptability, intelligent gripper design is required to improve the sensibility and processing capability of the end-effectors. This will allow for grippers to perform effective decision-making and optimize production. This paper suggests a methodology that includes a step-by-step design process for an intelligent gripper and discusses how to develop intelligence utilizing key components of Industry 4.0 (Internet of Things, machine learning, and cloud manufacturing). This method was analyzed in a case study of a low-level intelligent vacuum gripper design. The methodology will be beneficial to intelligent gripper design from multiple levels of intelligence, creating a guide for engineers to follow to effectively design intelligent gripper solutions for their systems.
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Heikkilä, Päivi, Susanna Aromaa, Hanna Lammi und Timo Kuula. „Framework of Future Industrial Worker Characteristics“. In 9th International Conference on Human Interaction and Emerging Technologies - Artificial Intelligence and Future Applications. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1002927.

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The ways of working are changing in the manufacturing industry due to new technologies and the merging of physical and virtual environments (e.g., Industry 4.0 [1], Metaverse [2]). Already, work tasks are changing from physical and routine tasks towards intellectual and social activities which often include the use of ICT tools [3]. The pandemic has changed attitudes and ways of working towards hybrid arrangements and therefore, expectations related to flexibility in work may become more pertinent also for manufacturing workers [4]. Novel technologies are being developed to support the industrial worker in the future [5], which can be called augmentation or empowerment of workers [6-8].The World Manufacturing Forum has identified the top ten skills that will be needed in future manufacturing work [9]. In our study, we wanted to add understanding of the skills and characteristics needed in future industrial work and present the results in a format that would support designers of technological tools to consider the perspective of future workers. Our goal was to create a framework of worker characteristics that could guide the design of technological tools to assist workers in work tasks requiring new skills and characteristics. To understand the transformation of work and to create a framework, we conducted a literature review and 10 expert interviews, focusing on the ways emerging technologies are expected to change the nature of industrial work. Based on the results, a framework of future industrial worker characteristics (FIW) was created. The applicability of the framework was tested by applying it in a European research project that develops software solutions for the context of modern, flexible, and data-rich manufacturing. Altogether, 19 novel software solutions that are being developed to support industrial work were mapped using the characteristics of the framework. The mapping experiment provided understanding of the relevance of the worker characteristics and the ways to support them in practice.According to the FIW framework, future industrial work will require smarter operations, which emphasizes worker capabilities in terms of mastering complexity, solving problems, making proactive decisions, and considering sustainability. Transforming work requires resilience that can be strengthened by capabilities such as creativity, the ability to lead oneself, flexibility, and continuous learning. Being interactive will be a vital part of work and can be fostered by communication, collaboration, supporting inclusiveness and interculturality, as well as sharing a safety-oriented mindset and work practices. In addition, health and well-being will have a central role in the future work. A healthy worker can be characterized as feeling motivated, balanced, capable, and focused.The FIW framework can be used by designers and industrial companies to guide the design and acquirement of novel technology solutions to support the characteristics of future industrial work, and in general, to increase understanding on transformation of industrial work from the perspective of worker skills and characteristics. In the future, it would be good to apply the framework in other research cases and industrial contexts to find out the possible development needs and ways to embed the framework in the design or evaluation processes.REFERENCES[1]Henning Kagermann, Wolfgang Wahlster and Johannes Helbig. 2013. Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: securing the future of German manufacturing industry. 82.[2]Sang-Min Park and Young-Gab Kim. 2022. A Metaverse: taxonomy, components, applications, and open challenges. IEEE Access [3]Eurofound. 2018. Wage and task profiles of employment in Europe in 2030. [4]Gartner 2023. 9 Future of Work Trends for 2023. Available: gartner.com/en/articles/9-future-of-work-trends-for-2023 [Accessed Feb 15, 2023].[5]David Romero, Johan Stahre, Thorsten Wuest, Ovidiu Noran, Peter Bernus, Åsa Fast-Berglund and Dominic Gorecky. 2016. Towards an operator 4.0 typology: A human-centric perspective on the fourth industrial revolution technologies. CIE 2016: 46th International Conferences on Computers and Industrial Engineering. [6]Eija Kaasinen, Franziska Schmalfuß, Cemalettin Özturk, Susanna Aromaa, Menouer Boubekeur, Juhani Heilala, Päivi Heikkilä, Timo Kuula, Marja Liinasuo and Sebastian Mach. 2020. Empowering and engaging industrial workers with Operator 4.0 solutions. Computers & Industrial Engineering 139, 105678.[7]Roope Raisamo, Ismo Rakkolainen, Päivi Majaranta, Katri Salminen, Jussi Rantala and Ahmed Farooq. 2019. Human augmentation: Past, present and future. International Journal of Human-Computer Studies 131, 131-143.[8]Francisco Betti and Thomas Bohne. 2022. Augmented Workforce: Empowering People, Transforming Manufacturing.[9]The World Manufacturing Forum. 2019. Skills for the Future of Manufacturing.
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CAO, AN-YAN, QIAN LV und LI-GONG CUI. „RESEARCH ON THE TRAINING OF ELECTROMECHANICAL COMPLEX TALENTS IN HIGHER VOCATIONAL COLLEGES UNDER THE BACKGROUND OF ARTIFICIAL INTELLIGENCE“. In 2021 International Conference on Education, Humanity and Language, Art. Destech Publications, Inc., 2021. http://dx.doi.org/10.12783/dtssehs/ehla2021/35718.

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The new technology in artificial intelligence has a far-reaching impact on the intelligent development of the manufacturing industry. These new skill requirements are bound to promote the reform of vocational education in the field of intelligent control. It is urgent to train a group of highly skilled compound talents who can adapt to the development of artificial intelligence and intelligent manufacturing and can engage in the field of intelligent control technology. In this background, this paper takes Binzhou Polytechnic as an example, which is a high level vocational college with Chinese characteristics. We investigate the current situation and development prospect of artificial intelligence and intelligent manufacturing and analyze the problems and development opportunities of mechatronics technology specialty under the background of artificial intelligence development. We put forward some suggestions on the personnel training system of mechatronics technology from the aspects of specialty orientation and the integration and optimization of training specifications, the development of specialty curriculum system, the reform of teaching mode, and the construction of innovative teacher team.
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Myllylä, Mari, Antero Karvonen und Hanna Koskinen. „Design Systems for Intelligent Technology“. In Intelligent Human Systems Integration (IHSI 2024) Integrating People and Intelligent Systems. AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1004490.

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Intelligent technology seems poised to emerge with unprecedented force across many domains of human activity. Advanced technologies (e.g. artificial intelligence (AI)–based applications and services) hold great promise to enhance work processes such as industrial operations and process control. However, the promise of intelligent technologies will not be realised unless their use is properly grounded in terms of their advantages to human action, operational safety, and the efficiency of the controlled system. Therefore, the novelty associated with what can be done with intelligent technology and how it should be integrated into human action and thought presents key design problems and questions to be answered in the design of future systems.Design systems (DSs) have become standard product design and development tools for creating consistent and well-functioning software applications and industry products by providing standard and reusable design patterns, components, and language. Currently, the industrial application of DSs mainly focuses on aspects of technology design such as visual identity, design principles, user interface elements, traditional engineering design, and interaction patterns. In the present paper, we propose to investigate and open a discussion on the concept of DSs for intelligent technology. This concept extends and builds upon current ideas and industrial practices regarding DSs. This paper is based on case studies of Finnish industrial companies seeking to implement and develop intelligent technology solutions for process control and design processes.Based on our research, we offer preliminary ideas on how DSs should be expanded to better address, identify, and solve challenges relevant to the design of intelligent technologies. Furthermore, we see that these extensions to the present industrial applications of DSs represent an important – even indispensable – step towards realising the vision of Industry 5.0, in which people and intelligent technologies collaborate.
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Al-Jumah, Ali, Ilyas Kindy, Mahamood Rawahi und Aiman Quraini. „Data Science as an Enabler: Integrating Business Intelligence (BI) Tools with Artificial Intelligence (AI) for an Ever Evolving Industry“. In SPE Conference at Oman Petroleum & Energy Show. SPE, 2024. http://dx.doi.org/10.2118/218752-ms.

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The evolution of industrial revolutions has been marked by the increasing use of data and information to improve productivity and efficiency. Industry 3.0 introduced automation and digitalization, which generated a lot of data from various sources and processes. This data was mainly used for monitoring and controlling the industrial activities, such as production, quality, and maintenance. Industry 4.0 leveraged this data to generate insights and intelligence, using technologies such as cloud computing, big data analytics, and the Internet of Things (IoT). These technologies enabled the integration and communication of data across different levels and domains of the industrial system, such as machines, products, processes, and services. Industry 4.0 also introduced the concept of smart factories, which are self-organizing, adaptive, and learning systems that can optimize their performance and efficiency. Industry 5.0 aims to enable human-robot collaboration and artificial intelligence [1], creating a more personalized and sustainable industrial system. Industry 5.0 focuses on enhancing the human capabilities and creativity, rather than replacing them with machines. It also emphasizes the social and environmental aspects of industrial development, such as customer satisfaction, worker well-being, and resource conservation. Industry 5.0 envisions a human-centric and eco-friendly industrial paradigm, where humans and machines work together in harmony and synergy. One of the sectors that can benefit from the convergence of business intelligence (BI) and artificial intelligence (AI) is the energy industry, which faces challenges such as increasing demand, environmental regulations, and market volatility. By combining BI and AI, energy companies can unlock value from their data and optimize their operations, such as production, distribution, and consumption. BI helps energy companies to collect, store, analyze, and visualize data from various sources, such as sensors, meters, devices, and systems. BI enables energy companies to monitor and manage their assets, processes, and performance, as well as to identify and solve problems, improve efficiency, and reduce costs. AI helps energy companies to augment and automate their decision making, using techniques such as machine learning, natural language processing, computer vision, and deep learning. AI enables energy companies to generate predictions, recommendations, and insights from their data, as well as to optimize their operations, such as scheduling, dispatching, pricing, and trading. AI also helps energy companies to create new products and services, such as smart grids, smart meters, smart homes, and smart cities. By combining BI and AI, energy companies can create a data-driven and intelligent energy system, which can respond to the changing needs and preferences of customers, stakeholders, and regulators, as well as to the dynamic and uncertain market conditions. This paper discusses the approach of complimenting the established business intelligence (BI) process with Artificial Intelligence (AI) in order to optimize gas production in an oil field in the south of Sultanate of Oman, it details the facts, observations, and insights the multidisciplinary authors have captured throughout the progress of this work, as well as general industry insights and BI process description.
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Berichte der Organisationen zum Thema "Intelligence – Industrie"

1

Arnold, Zachary, und Ngor Luong. China’s Artificial Intelligence Industry Alliance. Center for Security and Emerging Technology, Mai 2021. http://dx.doi.org/10.51593/20200094.

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As part of its strategy to achieve global leadership in AI, the Chinese government brings together local governments, academic institutions, and companies to establish collaboration platforms. This data brief examines the role of China’s Artificial Intelligence Industry Alliance in advancing its AI strategy, and the key players in the Chinese AI industry.
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2

Varian, Hal. Artificial Intelligence, Economics, and Industrial Organization. Cambridge, MA: National Bureau of Economic Research, Juli 2018. http://dx.doi.org/10.3386/w24839.

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3

Clement, Michael, Sage Broderick und Marty Garton. Toxic Industrial Chemical / Material Intelligence Tool (TICMINT) user guide. Engineer Research and Development Center (U.S.), November 2023. http://dx.doi.org/10.21079/11681/47924.

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The Toxic Industrial Chemical / Material Intelligence Tool (TICMINT) is a web application that provides critical chemical and toxicological information to users quickly and efficiently for the purpose of enacting safe maneuvers in areas of operations. It provides an in-depth look at the makeup, properties, and hazardous effects of nearly 400 toxic chemicals of interest. It also provides background on the chemical makeup of a bevy of building materials, enabling soldiers in areas of operation to determine the toxicological risks associated with the combustion of those materials in their environment. This document’s purpose is to demonstrate the functionality of the TICMINT web application and provide instructional material for those managing its content.
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4

Iraj A. Salehi, Shahab D. Mohaghegh und Samuel Ameri. DEVELOPMENT OF A VIRTUAL INTELLIGENCE TECHNIQUE FOR THE UPSTREAM OIL INDUSTRY. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/835587.

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5

Fedasiuk, Ryan, Jennifer Melot und Ben Murphy. Harnessed Lightning: How the Chinese Military is Adopting Artificial Intelligence. Center for Security and Emerging Technology, Oktober 2021. http://dx.doi.org/10.51593/20200089.

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This report examines nearly 350 artificial intelligence-related equipment contracts awarded by the People’s Liberation Army and state-owned defense enterprises in 2020 to assess how the Chinese military is adopting AI. The report identifies China’s key AI defense industry suppliers, highlights gaps in U.S. export control policies, and contextualizes the PLA’s AI investments within China’s broader strategy to compete militarily with the United States.
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6

Phinisee, Eri, Autumn Toney und Melissa Flagg. AI and Industry: Postings and Media Portrayals. Center for Security and Emerging Technology, Mai 2021. http://dx.doi.org/10.51593/20200059.

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Artificial intelligence is said to be transforming the global economy and society in what some dub the “fourth industrial revolution.” This data brief analyzes media representations of AI and the alignments, or misalignments, with job postings that include the AI-related skills needed to make AI a practical reality. This potential distortion is important as the U.S. Congress places an increasing emphasis on AI. If government funds are shifted away from other areas of science and technology, based partly on the representations that leaders and the public are exposed to in the media, it is important to understand how those representations align with real jobs across the country.
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7

Szladow, A. J. Application of artificial intelligence technology to increase productivity, quality and energy efficiency in heavy industry. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1995. http://dx.doi.org/10.4095/315015.

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8

Smith, Curtis, Ahmad Al Rashdan und Vivek Agarwal. Using 'The New Math' - Artificial Intelligence and Machine Learning Applications in the Nuclear Power Industry. Office of Scientific and Technical Information (OSTI), November 2021. http://dx.doi.org/10.2172/1968441.

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9

Montero, Elkin Christian, Daniel Muñoz und Anderson Téllez. Ventajas en costos, tiempo y mantenimiento a laboratorios, al diseñar plantas para el aprendizaje de la automatización y control de procesos industriales. Escuela Tecnológica Instituto Técnico Central, 2013. http://dx.doi.org/10.55411/2023.46.

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One of the most important skills to an industrial levet is the control of industrial processes this in order to reach a good automation , the current industry needs trained personnel in these areas because most of the current machines are intelligent and increasingly most technologically advanced and automated undergraduate in this area is seer, by the electronics in your field somewhat analogous , as discreet as famous with PID control form that was borra in the early nineteenth century and today still a big boom industrial leve!. From AUTOMATOOLS have seen this need and the importance for students of Escuela Tecnologica and other universities and institutions interested in improving learning of control and process automation, with comprehensive training in these fields. AUTOMATOOLS it aims to cover the causes that prevent a breakthrough theme have both practical and theoretical because sometirnes time becomes the worst enemy when it comes to learning from these materials.
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10

Toney, Autumn, und Melissa Flagg. U.S. Demand for AI-Related Talent. Center for Security and Emerging Technology, August 2020. http://dx.doi.org/10.51593/20200027.

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The U.S. government and industry both see artificial intelligence as a pivotal technology for future growth and competitiveness. What skills will be needed to create, integrate, and deploy AI applications? This data brief analyzes market demand for AI-related jobs to determine their educational requirements, dominant sectors, and geographic distribution.
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