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1
Preuß, Thomas, Dirk Nölken, and Frank Kusterer. "Controlling für eine Industrie- und Handelskammer." Controlling 31, no. 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, no. 5 (May 1, 2019): 86–92. http://dx.doi.org/10.3917/rdna.820.0086.
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Jarmoun, A., S. Messaoud, A. Mountassir, S. El Hilali, A. Abeydi Taleb, Z. Zeghari, R. Razine, and M. Obtel. "P34 - Intelligence artificielle et industrie pharmaceutique - De nouveaux défis pour des nouvelles innovations." Journal of Epidemiology and Population Health 72 (May 2024): 202474. http://dx.doi.org/10.1016/j.jeph.2024.202474.
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Thoben, Klaus-Dieter, Stefan Wiesner, and Thorsten Wuest. "“Industrie 4.0” and Smart Manufacturing – A Review of Research Issues and Application Examples." International Journal of Automation Technology 11, no. 1 (January 5, 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, no. 3 (August 31, 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, and Hayato Yoshioka. "Special Issue on the Latest Machine Tool Technologies and Manufacturing Processes." International Journal of Automation Technology 13, no. 5 (September 5, 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, and Tim Siebels. "Für effiziente und sichere industrielle Produktion/MagnOtrop – Three-dimensional magnet-field-based object and motion tracking." wt Werkstattstechnik online 111, no. 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, no. 1 (February 13, 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, no. 17 (December 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, no. 10 (October 1, 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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Geisert, Claudio, Julian Polte, Eckart Uhlmann, Hartmut Rauch, and Karsten Brach. "Smarte Überwachung elektrischer Großantriebe/Smart monitoring large electric drives." wt Werkstattstechnik online 113, no. 07-08 (2023): 340–45. http://dx.doi.org/10.37544/1436-4980-2023-07-08-74.
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Die Nutzung von Digitalisierungstechnologien im Kontext von Industrie 4.0 bietet insbesondere für den gesamten Bereich der Wartung und Instandhaltung von elektrischen Großantrieben großes Potenzial zur Schaffung innovativer Serviceangebote. Durch erweiterte Sensorik im elektrischen Antrieb und Intelligenz in der Verarbeitung und Analyse von Daten im Betrieb von Anlagen, kann eine vorausschauende Instandhaltungsstrategie eingeführt werden, die eine höhere Verfügbarkeit der Anlagen ermöglicht und gleichzeitig den Aufwand für Instandhaltungseinsätze reduziert. Um diese Potenziale im Servicegeschäft elektrischer Großantriebe zu erschließen, wird in diesem Beitrag ein hypothesengetriebener Ansatz zur Zustandsüberwachung beschrieben. The use of digitization technologies in the context of Industry 4.0 offers great potential for creating innovative service offerings, particularly for the entire area of the maintenance and servicing of large electrical drives. Advanced sensor technology in the electric drive and intelligence in the processing and analysis of data in the operation of plants can be used to introduce a predictive maintenance strategy that enables higher availability of the plants and at the same time reduces the cost of maintenance operations. To unlock this potential in the service business of large electrical drives, the following paper describes a hypothesis-driven approach to condition monitoring.
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Fatima, Taqdees, Bingxiang Li, Shahab Alam Malik, and Dan Zhang. "The Spatial Effect of Industrial Intelligence on High-Quality Green Development of Industry under Environmental Regulations and Low Carbon Intensity." Sustainability 15, no. 3 (January 19, 2023): 1903. http://dx.doi.org/10.3390/su15031903.
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In order to thoroughly investigate how industrial intelligence influences green industrial development through direct, indirect, and spatial spillover effects in China and fill in the gaps left by earlier studies, the study combines industrial intelligence and green industrial development into a single analytical framework. The findings show that implementing industrial intelligence can proactively encourage high-quality green industrial development; additionally, a strong spatial correlation is shown between industrial intelligence and high-quality green industrial development. According to spatial spillover analysis, industrial intelligence fosters the development of green industries both inside and between regions. When regional heterogeneity is analyzed, it is revealed that the eastern part of China experiences industrial intelligence effects more strongly than the central region, while the western areas are unaffected. Environmental regulations are a crucial mediating mechanism for the operation of industrial intelligence; in particular, public-participation environmental regulation and market base environmental regulations strengthen the baseline relationship; however, industrial intelligence does not impact high-quality green industrial development through administrative environmental regulation. The partial mediating effect of carbon intensity was also observed. The findings could be used as a guide for decision-making by experts and policymakers in China and other developing nations to use industrial intelligence and support the green development of the sector during economic transformation.
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Wardina, Unung Vera, Nizwardi Jalinus, and Lise Asnur. "KURIKULUM PENDIDIKAN VOKASI PADA ERA REVOLUSI INDUSTRI 4.0." Jurnal Pendidikan 20, no. 1 (March 28, 2019): 82–90. http://dx.doi.org/10.33830/jp.v20i1.240.2019.
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Vocational education purpose is to produce ready-to-work graduates who have the relevant skills for current job employment. Entering the industrial revolution era 4.0 there were massive changes in various industries and workers' ability needs. This article intends to examine the implications of the industrial revolution 4.0 era for vocational education curriculum. Based on the study of various sources and business practices, it is necessary to develop vocational education curriculum that are in accordance with the era of industrial revolution 4.0 and relevant to answering the needs of new skills, such as the ability to create and manage coding, big data, and artificial intelligence. The vocational curriculum needs to apply blended learning, which integrates face-to-face and online learning, so as to more effectively build graduates' abilities and skills. The curriculum also needs to contain mastery of 4.0 competencies such as data literacy, technology literacy and human literacy. In order for the vocational education curriculum to have a broad impact, the government, educational institutions, industries must work together to revitalize the approach and content of the vocational education curriculum. Teachers must also be able to implement good learning to produce optimal graduate performance.
Pendidikan vokasi merupakan pendidikan yang menghasilkan lulusan siap kerja yang memiliki keterampilan sesuai kebutuhan dunia kerja. Memasuki era revolusi indusri 4.0 terjadi perubahan yang masif pada perbagai industri dan kebutuhan kemampuan pekerja. Artikel ini bermaksud mengkaji implikasi era revolusi industri 4.0 bagi kurikulum pendidikan vokasi. Berdasarkan kajian berbagai sumber dan praktek bisnis, diperlukan pengembangan kurikulum pendidikan vokasi yang sesuai dengan era revolusi industri 4.0 dan relevan menjawab kebutuhan keterampilan baru, seperti kemampuan membuat dan mengelola coding, big data, dan artificial intelligence. Kurikulum vokasi perlu menerapkan pembelajaran blended learning, yang mengintegrasikan pembelajaran tatap muka dan online, supaya lebih efektif membangun kemampuan dan ketrampilan lulusan. Kurikulum juga perlu memuat penguasaan kompetensi 4.0 seperti literasi data, literasi teknologi dan literasi manusia. Agar kurikulum pendidikan vokasi menghasilkan dampak yang luas, pemerintah, lembaga pendidikan, industri harus bersinergi untuk merevitalisasi pendekatan dan isi kurikulum pendidikan vokasi. Pengajar juga harus dapat menyelenggarakan pembelajaran yang baik untuk menghasilkan kinerja optimal lulusan.
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Wardina, Unung Vera, Nizwardi Jalinus, and Lise Asnur. "KURIKULUM PENDIDIKAN VOKASI PADA ERA REVOLUSI INDUSTRI 4.0." Jurnal Pendidikan 20, no. 1 (June 20, 2019): 82. http://dx.doi.org/10.33830/jp.v20i1.843.2019.
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Vocational education purpose is to produce ready-to-work graduates who have the relevant skills for current job employment. Entering the industrial revolution era 4.0 there were massive changes in various industries and workers' ability needs. This article intends to examine the implications of the industrial revolution 4.0 era for vocational education curriculum. Based on the study of various sources and business practices, it is necessary to develop vocational education curriculum that are in accordance with the era of industrial revolution 4.0 and relevant to answering the needs of new skills, such as the ability to create and manage coding, big data, and artificial intelligence. The vocational curriculum needs to apply blended learning, which integrates face-to-face and online learning, so as to more effectively build graduates' abilities and skills. The curriculum also needs to contain mastery of 4.0 competencies such as data literacy, technology literacy and human literacy. In order for the vocational education curriculum to have a broad impact, the government, educational institutions, industries must work together to revitalize the approach and content of the vocational education curriculum. Teachers must also be able to implement good learning to produce optimal graduate performance.
Pendidikan vokasi merupakan pendidikan yang menghasilkan lulusan siap kerja yang memiliki keterampilan sesuai kebutuhan dunia kerja. Memasuki era revolusi indusri 4.0 terjadi perubahan yang masif pada perbagai industri dan kebutuhan kemampuan pekerja. Artikel ini bermaksud mengkaji implikasi era revolusi industri 4.0 bagi kurikulum pendidikan vokasi. Berdasarkan kajian berbagai sumber dan praktek bisnis, diperlukan pengembangan kurikulum pendidikan vokasi yang sesuai dengan era revolusi industri 4.0 dan relevan menjawab kebutuhan keterampilan baru, seperti kemampuan membuat dan mengelola coding, big data, dan artificial intelligence. Kurikulum vokasi perlu menerapkan pembelajaran blended learning, yang mengintegrasikan pembelajaran tatap muka dan online, supaya lebih efektif membangun kemampuan dan ketrampilan lulusan. Kurikulum juga perlu memuat penguasaan kompetensi 4.0 seperti literasi data, literasi teknologi dan literasi manusia. Agar kurikulum pendidikan vokasi menghasilkan dampak yang luas, pemerintah, lembaga pendidikan, industri harus bersinergi untuk merevitalisasi pendekatan dan isi kurikulum pendidikan vokasi. Pengajar juga harus dapat menyelenggarakan pembelajaran yang baik untuk menghasilkan kinerja optimal lulusan.
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Brecher, C., K. Schiling, and S. Storms. "Auf dem Weg zum „smarten“ Ökosystem*/Towards a „smart“ ecosystem." wt Werkstattstechnik online 109, no. 09 (2019): 674–78. http://dx.doi.org/10.37544/1436-4980-2019-09-60.
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Künstliche Intelligenz, Internet of Things und der Digitale Zwilling stehen als Schlagworte repräsentativ für den technologischen, aber auch organisatorischen Wandel in der Produktionstechnik, der keinesfalls verschlafen werden darf. Man möchte ein „Amazon der Industrie“ oder „Google für Maschinendaten“ sein oder es droht der Verlust an Marktbedeutung nach den oft zitierten Beispielen von Nokia und Kodak. Doch lassen sich die Mechanismen der Vorbilder einfach übertragen? Gibt es nur das oft suggerierte Konzept einer großen marktbestimmenden Plattform und welche Rolle spielen mittelständische Unternehmen? Dieser Beitrag versucht aus der Perspektive der Produktionsautomatisierung die verschiedenen Aspekte einer intelligenten, vernetzten Produktion zu differenzieren und so Anknüpfungspunkte für individuelle Ideen zu geben. Artificial intelligence, the Internet of Things and the Digital Twin are the buzzwords that represent the technological and organizational changes in production technology which must not be missed. There is a desire to become an „Amazon of industry“ or „Google for machine data“, or the threat of a loss of market significance following the often cited examples of Nokia and Kodak. But can the mechanisms of the models simply be transferred? Is there only the often suggested concept of a large, market-determining platform and what role do medium-sized companies play? In this article, it is attempt to differentiate between the various aspects of intelligent, networked production from the perspective of production automation and thus provide starting points for individual ideas.
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Wu, Kexu, Zhiwei Tang, and Longpeng Zhang. "Population Aging, Industrial Intelligence and Export Technology Complexity." Sustainability 14, no. 20 (October 20, 2022): 13600. http://dx.doi.org/10.3390/su142013600.
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The ageing of the population has become a serious test for all countries and regions, and industrial intelligence, as a new development model that integrates traditional industries with modern technology, will contribute to the deep integration of the industrial and innovation chains and thus to the enhancement of national core competitiveness. Based on the dual influence of population ageing and industrial intelligence, this paper uses the 2016 version of the World Input-Output Database (WIOD) data for 16 manufacturing industries in 43 countries from 2000 to 2014 to construct an econometric regression model to empirically test the relationship between population ageing, industrial intelligence and technological complexity of exports. The results of the study show, firstly, that population ageing plays a positive role in the technical complexity of exports. Secondly, the introduction of industrial intelligence mitigates the adverse effects of an ageing population through a complementary substitution mechanism on the one hand, and promotes industrial upgrading and transformation through the infiltration and expansion effects of industrial intelligence on the other, which in turn has a positive impact on the increase in technological sophistication of exports. In addition, the paper further divides the level of industry technology, the level of national development and the age structure of the ageing population, and explores the impact of industry intelligence in different dimensions. The results show that industrial intelligence can have a positive impact on export technological sophistication at the industry level, at the national level and in terms of ageing demographics. The research results provide a new way of thinking, through which countries around the world can formulate population policies and industrial policies and improve the complexity of export technology under the background of aging.
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Seitz, Matthias, Felix Gehlhoff, Luis Alberto Cruz Salazar, Alexander Fay, and Birgit Vogel-Heuser. "Automation platform independent multi-agent system for robust networks of production resources in industry 4.0." Journal of Intelligent Manufacturing 32, no. 7 (April 27, 2021): 2023–41. http://dx.doi.org/10.1007/s10845-021-01759-2.
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AbstractThe Cyber-Physical Production System (CPPS) is a concept derived from software (cyber) and hardware (physical) applications and is based on global information exchange between such systems. The CPPS is known as a trend of Industry 4.0 (I4.0) focusing on flexibility regarding new products and adaptability to new requirements. This paper focuses on two I4.0 scenarios described by the Platform Industrie 4.0 that describe challenges for the industry towards its digital future. First, it looks at the Order Controlled Production (OCP) scenario that deals with flexible and self-configuring production networks. It describes the dynamic organization of production resources required to execute a production order. Second, the Adaptable Factory (AF) application scenario is discussed, which focuses on the configuration of production resources and describes the adaptability of an individual facility through (physical) modification. This paper first provides a detailed analysis of the requirements from these scenarios. Furthermore, it analyses the current Multi-Agent System (MAS) architectures and agent-based planning and decision support systems requirements. MAS can be used to create application-independent I4.0 systems with arbitrary hardware automation platforms. To create a scalable communication network that also supports application independence and enables the semantically machine-readable description of the exchanged data, the OPC UA standard was adopted. As a result of the study, the concept shows how different and independent automation platforms can be seamlessly connected via OPC UA. The proposed MAS concept has been evaluated in different use cases, namely OCP and AF.
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Santoso, Rudi, Candraningrat Candraningrat, and Lilis Binawati. "Elemen Kecerdasan Wirausaha Untuk Meningkatkan Kinerja Industri Kecil dan Menengah (IKM) di Surabaya." BISMA (Bisnis dan Manajemen) 10, no. 1 (October 31, 2017): 73. http://dx.doi.org/10.26740/bisma.v10n1.p73-89.
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The aims of this study is to know the influence of the four intelligences as independent variables on the performance of Small and medium Industries (SMI’s) in Surabaya Indonesia. The population of this research is SME’s in Surabaya, Indonesia which build by Department of Industry and Trade, Surabaya. The samples of this research is 100 small and medium industries. Analysis method used multiple regression analysis. The result of coefficient determination (R2) shows that the influence of all variables which are Spiritual Intelligence, Financial Intelligence, Emotional Intelligence dan Social Intelligence have contributed 56,7% to performance. While the other 43.3% contributed by another variable which is not discussed in this study. The hypothesis test shows that as simultaneously these 4 (four) variable shave significantly affect to the performance of SME’s, but as partially by t-test shows that Financial Intelligence and Emotional Intelligence and Social Intelligence have significantly affected to performance but Spiritual Intelligence have no significant effect on Performance of SME’s in Surabaya. Limitation of this study is to use a small research sample. In addition, the scope of the study area is too narrow, which is limited to Surabaya. Therefore, further research can be developed from the side of the number of samples used and the wider coverage area. The practical implications of this research are useful for IKM development in Surabaya. This development is done through 3 elements of entrepreneurial intelligence that is financial intelligence, social intelligence, and emotional intelligence. The three main elements are further developed with the aim that IKM in Surabaya will be more sustainable
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Sasmita, Riska, Hidayatuhzzahra Hidayatuhzzahra, and Suyadi Suyadi. "APPLICATION OF MULTIPLE INTELLIGENCES IN DEVELOPING CREATIVITY OF LAZUARDI HIGH SCHOOL STUDENTS IN DEPOK." Indonesian Journal of Educational Development (IJED) 4, no. 4 (February 28, 2024): 483–91. http://dx.doi.org/10.59672/ijed.v4i4.3458.
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In the 21st era, we are facing the industrial revolution 4.0 which is based on information technology. To face these challenges, individuals need to master certain skills. Schools are considered as a place to develop intelligence and produce quality future generations. However, there is still discrimination in assessing student intelligence, which is often only measured in cognitive terms. The introduction of the concept of multiple intelligences can be a solution to overcome discrimination in the world of education. This research aims to evaluate the application of multiple intelligences by Lazuardi High School in Depok and its impact on the development of student creativity. The research method used is qualitative with direct observation in the school and interviews towards teacher and students of Lazuardi High School, Depok. The research results show that the application of multiple intelligences through teacher approaches and extracurricular activities can successfully develop student creativity. When students can express the intelligence they have, this reflects the creativity they show.
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Wang, Fuzhe. "Review of the Application Status and Development Trend of Industrial Robots." SHS Web of Conferences 144 (2022): 03005. http://dx.doi.org/10.1051/shsconf/202214403005.
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With the progress of industrial civilization and the development of artificial intelligence technology, industrial robots are gradually approaching production workshop, and their status is improving day by day. This article will describe the current development status of emerging industrial robots and share their future development trends, aiming to provide a theoretical basis for industrial robot design departments and factories. Nowadays, industrial robots are developing rapidly in various countries, and have entered many emerging industries, such as aerospace, military and medical fields. The development trend of industrial robots in the future should mainly focus on five development directions: human-robot collaboration, artificial intelligence, new industrial users, digitization, and smaller and lighter robots.
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Bohra, Mrs Jyoti M., and Ms Bhagyashri G. Joshi. "Artificial Intelligence and its Role in Industry." International Journal of Trend in Scientific Research and Development Special Issue, Special Issue-ICDEBI2018 (October 3, 2018): 204–7. http://dx.doi.org/10.31142/ijtsrd18705.
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Batischeva, Elena. "ARTIFICIAL INTELLIGENCE. CURRENT STATE AND PROSPECTS FOR DEVELOPMENT IN RURAL." Russian Journal of Management 11, no. 4 (December 30, 2023): 634–41. http://dx.doi.org/10.29039/2409-6024-2023-11-4-634-641.
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Annotation. The author examines the practice of using artificial intelligence and the structure of the focus of the main government programs of the leading countries in the field of artificial intelligence. Within the framework of the national economy, the Government of the Russian Federation has identified priority areas for the development and implementation of critically important AI technologies in various industries, and in particular in agricultural production. The agro-industrial complex has enormous reserves for the introduction of various innovations. The transition of agricultural industries to "artificial intelligence" will lead to the formation of new ecosystems, remote monitoring and control over compliance with certified product safety requirements.
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Lv, Hao, Beibei Shi, Nan Li, and Rong Kang. "Intelligent Manufacturing and Carbon Emissions Reduction: Evidence from the Use of Industrial Robots in China." International Journal of Environmental Research and Public Health 19, no. 23 (November 23, 2022): 15538. http://dx.doi.org/10.3390/ijerph192315538.
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Driven by the information technology revolution, using artificial intelligence to promote intelligent manufacturing while achieving carbon emissions reduction is increasingly the focus of international attention. Given this, based on the fact that China’s industrial manufacturing is more intelligent, this paper uses industrial sector data and robot data from 2000 to 2017 to examine the impact of intelligent manufacturing on industrial carbon dioxide emissions and to discuss its internal mechanism. The research found that intelligent manufacturing significantly inhibits carbon dioxide emissions in the industrial sectors. The emission reduction effect is more obvious in industries with higher carbon emissions and intelligence. The mechanism test shows that intelligent manufacturing mainly achieves industrial emission reduction by reducing fossil energy consumption in the production process and improving energy use efficiency. The research findings of this paper provide favorable evidence for using new technologies, such as artificial intelligence, to achieve carbon emissions reduction, and validate the importance of intelligent manufacturing in tackling climate change in the future. It provides an essential reference for developing countries to use artificial intelligence for their carbon emissions reduction goals.
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آرین کامبخش, احمد نوید. "آیندۀ صنایع در پرتو هوش مصنوعی." ghalib quarterly journal 36, no. 1 (August 4, 2022): 25–41. http://dx.doi.org/10.58342/.v11i36.29.
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با تجزیهوتحلیل نخستین و نابترین تعریف از هوش مصنوعی، از زمانی که برای اولین بار توسط جان مک کارتی ابداع شد و تمرکز آن شبیهسازی هوش از طریق تعریف جنبههای یادگیری برای ماشینها بود، به وضوح میتوان دریافت، که هدف اولیه از توسعۀ هوش مصنوعی، افزودن هوش در ماشینها بود، تا بتواند مشکلات منحصربهفرد انسانی را به ماشینها تحویل دهد. این تحقیق به هدف بررسی این واقعیت که امروزه هوش مصنوعی از هدف اصلی خود برای توسعه بسیار دور شده است و در طول پیشرفت با سایر عوامل قدرتمندی که میتوانند تأثیر زیادی در زندهگی انسان داشته باشند، آمیخته شده است، انجام یافته است. سعی بر این بوده است که برای این پرسشها پاسخ بیابم که: آیا با چنین پیشرفتهای قدرتمند فنی و همهکاره، هوش مصنوعی از نظر ماشینآلات و نوع کار جایگزین بسیاری از صنایع خواهد شد؟ آیا هوش مصنوعی تغییر ماهیت بسیاری از مشاغل را اعمال میکند و نیروی انسانی آنها را به ماشین تغییر میدهد؟ این پژوهش به روش کیفی و با توجه به اطلاعات و مطالعات راهبردی سازمانهای توسعهیافته با هوش مصنوعی، که نقش تعیینکننده و مؤثر در بازار کار امروزی دارند، انجام یافته است. یافتههای تحقیق نشان میدهند که: هوش مصنوعی بهصورت گستردهیی و گاهی بهصورت منفی بر صنایع جهان امروزی تأثیراتی داشته است. این تأثیرات در ابعاد مختلف بررسی گردیده و راه حلهای علمی - تخنیکی ارائه گردیدهاند.
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Zhang, Zhaozhong, and Fangfang Deng. "How can artificial intelligence boost firms’ exports? evidence from China." PLOS ONE 18, no. 8 (August 23, 2023): e0283230. http://dx.doi.org/10.1371/journal.pone.0283230.
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This paper explores the impact of artificial intelligence and industrial robots on firms’ export behaviour and divides the impact mechanism into the productivity effect and labour substitution effect. It examines the effect of industrial robots on firms’ export value by using Chinese Customs data, Chinese Industrial Firm data and robot data from the International Robot Federation (IRF). The main findings are as follows: Firstly, the impact of artificial intelligence and industrial robots on Chinese firms’ export value is generally negative, which means the negative labour substitution effect dominates the positive productivity effect. Secondly, the impact of artificial intelligence varies significantly by industry, and the export value of firms from high-tech industries benefits from the use of industrial robots. Thirdly, the impact of artificial intelligence on firms’ export value also varies by time; before 2003, the use of industrial robots showed mainly an inhibiting effect on firms’ exports, which turned into a driving effect thereafter, and after 2006, industrial robots began to significantly promote firms’ export. Finally, the higher the quality of export products, the more likely the use of industrial robots will be to promote firms’ export value, and the higher the capital–labour ratio is, the more likely firms’ export value will be to benefit from the use of artificial intelligence and industrial robots. On the basis of these findings, this study proposes promoting the productivity effect to dominate the labour substitution effect through technological progress and the improvement of export product quality.
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Kim, Sung Wook, Jun Ho Kong, Sang Won Lee, and Seungchul Lee. "Recent Advances of Artificial Intelligence in Manufacturing Industrial Sectors: A Review." International Journal of Precision Engineering and Manufacturing 23, no. 1 (November 3, 2021): 111–29. http://dx.doi.org/10.1007/s12541-021-00600-3.
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AbstractThe recent advances in artificial intelligence have already begun to penetrate our daily lives. Even though the development is still in its infancy, it has been shown that it can outperform human beings even in terms of intelligence (e.g., AlphaGo by DeepMind), implying a massive potential for its broader application in various industrial sectors. In particular, the growing public interest in industry 4.0, which focuses on revolutionizing the traditional manufacturing scene, has stimulated a deeper investigation of its possible applications in the related industries. Since it has several limitations that hinder its direct usage, research on the convergence of artificial intelligence with other engineering fields, including precision engineering and manufacturing, is ongoing. This overview looks to summarize some of the important achievements made using artificial intelligence in some of the most influential and lucrative manufacturing industries in hopes of transforming the manufacturing sites.
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Kanade, Anuradha, Sachin Bhoite, Shantanu Kanade, and Niraj Jain. "Artificial Intelligence and Morality: A Social Responsibility." Journal of Intelligence Studies in Business 13, no. 1 (May 21, 2023): 65–75. http://dx.doi.org/10.37380/jisib.v13i1.992.
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Both the globe and technology are growing more quickly than ever. Artificial intelligence's design and algorithm are being called into question as its deployment becomes more widespread, raising moral and ethical issues. We use artificial intelligence in a variety of industries to improve skill, service, and performance. Hence, it has both proponents and opponents. AI uses a given collection of data to derive action or knowledge. There is therefore always a chance that it will contain some inaccurate information. Since artificial intelligence is created by scientists and engineers, it will always present issues with accountability, responsibility, and system reliability. There is great potential for economic development, societal advancement, and improved human security and safety thanks to artificial intelligence.
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Levina, Elena V. "The application of platform solutions in the assessment of corporate resources of industrial enterprises." Market economy problems, no. 3 (2021): 108–16. http://dx.doi.org/10.33051/2500-2325-2021-3-108-116.
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In this article the author examines the features of the use of digital platforms in the assessment and planning of corporate resources of industrial enterprises. The subject of the research is platform solutions and the use of artificial intelligence elements in the process of analyzing corporate resources of business structures. The purpose of the article is to analyze the possibilities of using digital platforms and elements of artificial intelligence in the analysis of the level of availability of necessary resources of industrial enterprises. Materials and methods. The methodological basis of the article consists of theoretical and applied research of Russian and foreign scientists, regulatory legal acts regulating the processes of digital transformation of industries and complexes. The author of the article uses such general scientific methods as analysis and synthesis to study the features of the use of digital platforms in the assessment of corporate resources of enterprises, system, structural, functional and situational approaches to study platform solutions as a system of interrelated and interdependent elements, the method of economic and statistical analysis to study the dynamic aspects and identify patterns of transformation of industries and complexes. Results. The article presents an analysis of the current state of corporate resources of industrial enterprises, and offers a universal method for assessing the level of human resources availability of business structures. Conclusions. In the current conditions of economic transformation, the use of platform solutions with elements of artificial intelligence in the analysis of technical, technological and information and communication support for industrial enterprises is becoming relevant and requires further research, especially in the context of providing industries with highly qualified specialists necessary for the effective operation of business structures. Application. The results obtained can be used for further analysis of the results and implementation of the methodology for evaluating corporate resources of industrial enterprises.
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Kang, Jinwon, Jong-Seok Kim, and Seonmi Seol. "The prioritization of technologies and public R&D roles between the manufacturing and service industries in the fourth industrial revolution." foresight 21, no. 6 (November 11, 2019): 680–94. http://dx.doi.org/10.1108/fs-03-2019-0021.
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Purpose The purpose of this study is to reveal the similarities and differences between the manufacturing and service industries in their prioritization of technologies and public research and development (R&D) roles, along with the complementation of properties of technology and public R&D role in the context of Fourth Industrial Revolution. Design/methodology/approach Two rounds of Delphi surveys were designed to meet the purpose of this study, which used rigorous triangulation techniques. The Delphi method was combined with the brainstorming method in the first-round Delphi survey, while the second-round Delphi survey focused on experts’ judgments. Finally, language network analysis was performed on the properties of technology and public R&D roles to complement the data analyses regarding prioritization. Findings This study identifies different prioritizations of five similar key technologies in each industry, so that it can note different technological impacts to the two industries in the Fourth Industrial Revolution. Smart factory technology is the first priority in the manufacturing industry, whereas artificial intelligence is the first priority in the service industry. The properties of the three common technologies: artificial intelligence, big data and Internet of things in both industries are summarized in hyper-intelligence on hyper-connectivity. Moreover, it is found that different technological priorities in the service and manufacturing industries require different approaches to public R&D roles, while public R&D roles cover market failure, system failure and government failure. The highest priority public R&D role for the service industry is the emphasis of non-R&D roles. Public R&D role to solve dy-functions, focus basic technologies and support challenging areas of R&D is prioritized at the highest for the manufacturing industry. Originality/value This study of the different prioritizations of technologies in the manufacturing and service industries offers practical lessons for executive officers, managers and policy-makers. They, by noting the different technological impacts in the manufacturing and service industries, can prepare for current actions and establish the priority of technology for R&D influencing the future paths of their industries in the context of the Fourth Industrial Revolution. While managers in the service industry should pay greater attention to the technological content of hyper-intelligence and hyper-connectivity, managers in the manufacturing industry should consider smart factory and robot technology.
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Thomas, Dr Basil John. "Business Intelligence Tools and Team Performance of Oil and Gas Industries." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (March 31, 2020): 1045–59. http://dx.doi.org/10.5373/jardcs/v12sp4/20201578.
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Carrasco Ramírez, José Gabriel, and Md Mafiqul Islam. "Utilizing Artificial Intelligence in Real-World Applications." Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 2, no. 1 (February 7, 2024): 14–19. http://dx.doi.org/10.60087/jaigs.v2i1.p19.
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Artificial Intelligence (AI) stands as a pivotal innovation deeply ingrained in both our daily routines and industrial operations. Its rapid evolution promises transformative impacts across various sectors, from cutting-edge industries to the lives of ordinary individuals. AI constantly updates human experiences, shaping interactions and augmenting capabilities. For instance, contemporary educational institutions leverage AI algorithms for attendance tracking via facial recognition technology. Looking ahead, the advent of autonomous vehicles represents a pinnacle of AI application, where vehicles rely entirely on AI systems for navigation, detecting traffic signals, and navigating roads.
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Carrasco Ramírez, José Gabriel, and Md mafiqul Islam. "Application of Artificial Intelligence in Practical Scenarios." Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 2, no. 1 (February 8, 2024): 14–19. http://dx.doi.org/10.60087/jaigs.v2i1.41.
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Artificial Intelligence (AI) stands as a pivotal innovation deeply ingrained in both our daily routines and industrial operations. Its rapid evolution promises transformative impacts across various sectors, from cutting-edge industries to the lives of ordinary individuals. AI constantly updates human experiences, shaping interactions and augmenting capabilities. For instance, contemporary educational institutions leverage AI algorithms for attendance tracking via facial recognition technology. Looking ahead, the advent of autonomous vehicles represents a pinnacle of AI application, where vehicles rely entirely on AI systems for navigation, detecting traffic signals, and navigating roads
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Barash, Guy, Mauricio Castillo-Effen, Niyati Chhaya, Peter Clark, Huáscar Espinoza, Eitan Farchi, Christopher Geib, et al. "Reports of the Workshops Held at the 2019 AAAI Conference on Artificial Intelligence." AI Magazine 40, no. 3 (September 30, 2019): 67–78. http://dx.doi.org/10.1609/aimag.v40i3.4981.
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The workshop program of the Association for the Advancement of Artificial Intelligence’s 33rd Conference on Artificial Intelligence (AAAI-19) was held in Honolulu, Hawaii, on Sunday and Monday, January 27–28, 2019. There were fifteen workshops in the program: Affective Content Analysis: Modeling Affect-in-Action, Agile Robotics for Industrial Automation Competition, Artificial Intelligence for Cyber Security, Artificial Intelligence Safety, Dialog System Technology Challenge, Engineering Dependable and Secure Machine Learning Systems, Games and Simulations for Artificial Intelligence, Health Intelligence, Knowledge Extraction from Games, Network Interpretability for Deep Learning, Plan, Activity, and Intent Recognition, Reasoning and Learning for Human-Machine Dialogues, Reasoning for Complex Question Answering, Recommender Systems Meet Natural Language Processing, Reinforcement Learning in Games, and Reproducible AI. This report contains brief summaries of the all the workshops that were held.
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Yun, JinHyo Joseph, EuiSeob Jeong, Xiaofei Zhao, Sung Deuk Hahm, and KyungHun Kim. "Collective Intelligence: An Emerging World in Open Innovation." Sustainability 11, no. 16 (August 19, 2019): 4495. http://dx.doi.org/10.3390/su11164495.
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Responding to the lack of empirical research on the effect of collective intelligence on open innovation in the fourth industrial revolution, we examined the relationship between collective intelligence and open innovation. Collective intelligence or crowd innovation not only produces creative ideas or inventions, but also moderates any firm to innovate inside-out, outside-in, or in a coupled manner. We asked the following research questions: Does collective intelligence (or crowd innovation) motivate open innovation? Is there any difference in the effect of collective intelligence on open innovation by industry? These research questions led to the following three hypotheses: (1) Collective intelligence increases the performance of a firm, (2) collective intelligence will moderate the effect of open innovation, and (3) differences exist between the automotive industry and the pharmaceutical industry in these two effects. To empirically examine these three hypotheses, we analyzed the registered patents of these two industries from 2000 to 2014 over a 15-year period. These automotive and pharmaceutical patents were registered in the B60 category and the A61K category of the Korea Patent office, respectively. Collective intelligence was measured by co-invention. We found differences in the effects of collective intelligence on open innovation between the two industries. In the automotive industry, collective intelligence not only directly increased the performance, but also indirectly moderated the open innovation effect. However, this was not the case for the pharmaceutical industry.
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Knittel, Dominique, Hamid Makich, and Mohammed Nouari. "Milling diagnosis using artificial intelligence approaches." Mechanics & Industry 20, no. 8 (2019): 809. http://dx.doi.org/10.1051/meca/2020053.
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The Industry 4.0 framework needs new intelligent approaches. Thus, the manufacturing industries more and more pay close attention to artificial intelligence (AI). For example, smart monitoring and diagnosis, real time evaluation and optimization of the whole production and raw materials management can be improved by using machine learning and big data tools. An accurate milling process implies a high quality of the obtained material surface (roughness, flatness). With the involvement of AI-based algorithms, milling process is expected to be more accurate during complex operations. In this work, a milling diagnosis using AI approaches has been developed for composite sandwich structures based on honeycomb core. The use of such material has grown considerably in recent years, especially in the aeronautic, aerospace, sporting and automotive industries. But the precise milling of such material presents many difficulties. The objective of this work is to develop a data-driven industrial surface quality diagnosis for the milling of honeycomb material, by using supervised machine learning methods. In this approach cutting forces are online measured in order to predict the resulting surface flatness. The developed diagnosis tool can also be applied to the milling of other materials (metal, polymer, etc.).
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Salehi, Mahdi, Mahin Ali Mirzaee, and Mahdieh Yazdani. "Spiritual and emotional intelligences, financial performance, tax avoidance and corporate disclosure quality in Iran." International Journal of Law and Management 59, no. 2 (March 13, 2017): 237–56. http://dx.doi.org/10.1108/ijlma-11-2015-0059.
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Purpose The purpose of the current study is to examine the effects of spiritual and emotional intelligences of managers in manufacturing industries on the ambiguous activities of tax avoidance and corporate disclosure quality. Design/methodology/approach Managers of 178 manufacturing companies have undergone a test regarding spiritual intelligence and emotional intelligence, of which 119 responded to the online questionnaire. Information on these two psychometric items was collected through King–Baron standard questionnaire, and quantitative data on tax avoidance, disclosure quality and performance were collected through the Rahavard Novin application, financial statements and Stock Exchange website. Obtained data were analyzed using factor analysis and structural equation modeling. Findings The results show that a relationship exists between the level of intellectual skills of managers (spiritual intelligence and emotional intelligence) and tax avoidance activities. Originality/value The current study is almost the first study in developing countries which focuses on the subject of the study.
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Nad, Stipo. "Intelligente Systeme für Industrie 4.0." ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb 111, no. 6 (June 28, 2016): 380–82. http://dx.doi.org/10.3139/104.111542.
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Wei, Jin. "Research Progress and Application of Computer Artificial Intelligence Technology." MATEC Web of Conferences 176 (2018): 01043. http://dx.doi.org/10.1051/matecconf/201817601043.
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With the development of science and technology, artificial intelligence technology has received more and more attention and attention. Under the background of the rapid development of big data and cloud computing, the artificial intelligence industry broke out. There is a huge amount of research on artificial intelligence and the artificial intelligence industry is huge. As far as the artificial intelligence industry in China is concerned, even the start is relatively late, but the industry scale, industrial layout, and technology research are all in a continuous improvement stage. Especially after the deepening of the layout of science and technology and manufacturing industries, the scale of artificial intelligence industry is further developed. More artificial intelligence products will appear at the same time. From the perspective of the concept, development history and new progress of artificial intelligence, this paper combines China’s artificial intelligence market and the development of artificial intelligence companies to analyze the current major application areas, and then further explore the future development trend of artificial intelligence.
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Chen, Keyu. "Innovation of Enterprise Management in the Era of Artificial Intelligence." International Journal of Global Economics and Management 2, no. 2 (April 7, 2024): 281–85. http://dx.doi.org/10.62051/ijgem.v2n2.35.
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As a product of social development and technological innovation, Artificial Intelligence has become the driving force of technological innovation and industrial transformation. It profoundly impacts the world economy, social progress as well as people’s lives. Artificial Intelligence’s commercial applications innovate enterprises’ internal operations and production processes, bringing both challenges and opportunities for management. This article analyses innovation in modern enterprise management with specific applications of AI to management theories. Some suggestions are also made for enhancing the application level of Artificial Intelligence in enterprise management.
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Subakti, Hani. "Media Edukasi Tentang Pentingnya Artificial Intelligence Bagi Dunia Pendidikan di Daerah Ibu Kota Nusantara (IKN)." JURNAL PENGABDIAN MASYARAKAT AKADEMISI 2, no. 1 (January 2, 2024): 56–60. http://dx.doi.org/10.59024/jpma.v2i1.603.
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Abstrak. Artificial intelligence (AI) adalah istilah dari industrial society yang merupakan sebuah "program komputer, pembelajaran mesin, perangkat keras dan perangkat lunak". Artificial intelligence ini menggunakan sebuah ilmu dari perangkat keras dan perangkat lunak yang terinspirasi oleh rekayasa terbalik dari pola neokognitron yang bekerja diotak manusia. Produk industri ini banyak digunakan dalam pengembangan dan aplikasi sehari-hari di berbagai bidang, termasuk pendidikan. Tujuan dari kegiatan ini adalah untuk memperjelas peran artificial intelligence dalam pendidikan, dan metode yang digunakan adalah metode media informasi, seperti poster yang pasang di majalah dinding sekolah. poster tersebut ini mengenai edukasi pentingnya artificial intelligence dalam membantu dan membuat profil pembelajaran untuk setiap siswa dan memungkinkan materi pembelajaran disesuaikan dengan kemampuan, gaya belajar, dan pengalaman setiap siswa.
Kata Kunci: Pendidikan, artificial intelligence, media edukasi.
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Cai, Hongbiao. "Promoting Regional Economic Transformation Forecast Based on Intelligent Computing Technology." Computational Intelligence and Neuroscience 2022 (March 4, 2022): 1–12. http://dx.doi.org/10.1155/2022/1835376.
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The core of the value of artificial intelligence is to integrate with the real economy and become more dependent on local industries. In the entire artificial intelligence + industry development process, many new changes have appeared. This article mainly studies how to promote regional economy based on smart technology. In the context of rapid economic development, the significance of artificial intelligence and the necessity of regional economic transformation are put forward. The model has designed the national science and technology mechanism framework from the four directions of technology guidance, technology service, technology innovation, and technology balance; following the cultivating ideas from products to innovative industries to innovative intelligent environments, due to the low income elasticity of product demand, technological innovation is mainly based on the dissemination of emerging technologies outside the industry and the lack of coordination between companies under the fiercely competitive market structure; the focus is on promoting the continuous improvement of labor productivity. The experimental results prove that the emerging technology industries of enterprises can promote economic transformation in the era of artificial intelligence, provide a reference for better optimization of industrial innovation and development, and provide methodological support for the government to establish sound emerging technology business models and optimized management methods.
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Iakovlev, Igor, Elmira Kremleva, and Roman Guzanov. "Enterprise automation using artificial intelligence: Methods, technologies and prospects." E3S Web of Conferences 460 (2023): 04007. http://dx.doi.org/10.1051/e3sconf/202346004007.
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The integration of Artificial Intelligence (AI) technologies is significantly transforming the landscape of enterprise automation across various industrial sectors. This article provides a comprehensive overview of the principal methods and AI technologies implemented in the automation of enterprise processes, along with illustrative examples of AI application in diverse industries. It delves into the key areas of machine learning, robotics, logistical process optimization, and human resource management, supported by specific cases from the automotive, pharmaceutical, and telecommunications industries. The conclusion part addresses the future outlook and potential challenges associated with the continued evolution of enterprise automation through AI, including ethical and economic considerations, the need for staff training, and security issues. The article highlights the importance of an integrated approach to the adoption of AI in production processes and enterprise management as a vital factor in enhancing their efficiency and competitiveness in the global market.
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Liu, Yutong, and Peiyi Song. "Creating Sustainable Cultural Industries: The Perspective of Artificial Intelligence and Global Value Chain." Journal of Environmental and Public Health 2022 (August 22, 2022): 1–11. http://dx.doi.org/10.1155/2022/6768388.
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In the era of artificial intelligence (AI), cultural industries have introduced new development opportunities, and their global value chain (GVC) position is receiving more attention. This study uses panel data from global cross-borders from 56 countries (regions) as the research sample to empirically analyze the impact of AI on improving the GVC position of cultural industries using the double fixed effects regression model and examines the heterogeneity effect. The results confirm that there is a significant positive correlation between AI and the GVC position of cultural industries. The mechanism test shows that AI impacts the division of labor position in the GVC of cultural industries mainly through technological innovation and the industrial structure. Heterogeneity analysis shows that AI has a significant effect on promoting the cultural industry’s GVC position in high-income countries (regions) but it has no significant effect on low- and middle-income countries (regions). The results of this study can provide a useful reference for improving the division of labor positions in the GVC and better promoting the development of cultural industries.
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Aristova, N. I. "Intelligence in industrial automation." Automation and Remote Control 77, no. 6 (June 2016): 1071–76. http://dx.doi.org/10.1134/s0005117916060102.
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Supriatna, Ucup, Zulvia Trinova, Samuel PD Anantadjaya, Mariana Puspa Dewi, and Irma M. Nawangwulan. "The Application of Multiple Intelligences in Islamic Religious Education." AL-ISHLAH: Jurnal Pendidikan 13, no. 3 (December 30, 2021): 2381–90. http://dx.doi.org/10.35445/alishlah.v13i3.700.
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This qualitative research aims to determine how crucial Multiple Intelligence is in Islamic religious learning. The method in this research is a theoretical study that tries to find hypotheses by examining various research sources and online media about Multiple Intelligence. The collecting data is by gathering some literature obtained from various articles, both accredited national journals and reputable international journals. Data analysis is done by mapping from the collected data and obtaining literature from multiple intelligences in Islamic Religious Education. The result of this research is that with the application of multiple intelligences, the teacher can map the condition of students based on their potential and interests and with the among system, the characteristics of students can be continuously fostered without being shackled to their "independence" to develop.
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Anwarsha, A., and T. Narendiranath Babu. "Artificial Intelligence-based Fault Diagnosis Procedure for a Sustainable Manufacturing Industry." IOP Conference Series: Earth and Environmental Science 1055, no. 1 (July 1, 2022): 012012. http://dx.doi.org/10.1088/1755-1315/1055/1/012012.
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Abstract All industries are fast transforming into smart industries as part of the sustainable developments in the fourth industrial revolution. Predictive maintenance is one of the most important aspects of such smart industries, to avoid unanticipated machine breakdowns and catastrophic failures. Machine vibration analysis is a common tool for predicting the state of machinery. Vibration analysis involves analysing vibration data collected from machinery and determining whether or not a fault exists. Despite the fact that different methods are utilized to handle data, artificial intelligence is capable of processing such data without the need for human intervention. Every day, a substantial amount of study is carried out in this field. New strategies, on the other hand, that yield greater classification accuracy have yet to be developed. With the use of artificial intelligence approaches, this research article attempts to offer an effective defect detection method for rolling element bearings. To illustrate the practical applications, the technique is used on real datasets which were developed by Case Western Reserve University, which is regarded as a gold standard for testing diagnostic algorithms.
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Zhang, Longqing, Xinwei Zhang, Lei Yang, Yungui Chen, Yanghong Zhang, and Qianwen Wang. "Teaching Reform of Computer Science in Combination with Artificial Intelligence." International Journal of Education and Humanities 5, no. 3 (November 16, 2022): 152–55. http://dx.doi.org/10.54097/ijeh.v5i3.2792.
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In recent years, with the rapid landing application of artificial intelligence in various industries and the strong demand for artificial intelligence professionals, many colleges and universities nowadays respond to national policies and compete to open courses and majors related to artificial intelligence. In order to build first-class application-oriented undergraduate institutions and cultivate first-class talents, higher education institutions should actively cultivate application-oriented and compound skilled talents for the development of the whole society and local economy and industrial transformation and upgrading. In order to promote the intelligence and development of computer majors, this teaching reform proposes the teaching concept of AI + software, project-based teaching reform for courses and independent practical links, introduction of AI, reflecting engineering quality and job competence training, and strengthening the mastery, application and innovation of professional knowledge.
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Liu, Yu, Sepehr Mousavi, Zhibo Pang, Zhongjun Ni, Magnus Karlsson, and Shaofang Gong. "Plant Factory: A New Playground of Industrial Communication and Computing." Sensors 22, no. 1 (December 27, 2021): 147. http://dx.doi.org/10.3390/s22010147.
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Plant Factory is a newly emerging industry aiming at transforming crop production to an unprecedented model by leveraging industrial automation and informatics. However, today’s plant factory and vertical farming industry are still in a primitive phase, and existing industrial cyber-physical systems are not optimal for a plant factory due to diverse application requirements on communication, computing and artificial intelligence. In this paper, we review use cases and requirements for future plant factories, and then dedicate an architecture that incorporates the communication and computing domains to plant factories with a preliminary proof-of-concept, which has been validated by both academic and industrial practices. We also call for a holistic co-design methodology that crosses the boundaries of communication, computing and artificial intelligence disciplines to guarantee the completeness of solution design and to speed up engineering implementation of plant factories and other industries sharing the same demands.
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Vetrov, Alexey S., and Alina A. Eliseeva. "ARTIFICIAL INTELLIGENCE IS A UNIVERSAL TOOL IN THE HANDS OF AN EXPERT." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 4/4, no. 145 (2024): 184–90. http://dx.doi.org/10.36871/ek.up.p.r.2024.04.04.021.
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The article examines the impact of artificial intelligence on the development of the modern Russian economy, industrial enterprises and companies, marketing centers and firms. The authors not only make a narrative review and analysis of the use of artificial intelligence, but also highlight its advantages and disadvantages when implemented in the domestic economy. Banks and scientific manufacturing enterprises and companies were the first to introduce artificial intelligence into their work. Users of mobile applications and systems are almost daily confronted with modern innovations in the banking sector. Today, artificial intelligence is firmly gaining its position and is widely implemented by many large enterprises and companies, as well as small firms. It’s no secret that the future of the economy, banking, insurance, medicine, education, space and other industries lies with artificial intelligence, but you need to use its benefits with great caution, taking into account all the risks.
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Jung, Ae Ryung. "Artificial Intelligence Decision Making and the infringement of human rights: Focusing on the recruitment process." Korea Association for Corruption Studies 28, no. 1 (March 31, 2023): 5–30. http://dx.doi.org/10.52663/kcsr.2023.28.1.5.
Full textAbstract:
The key word in the era of the Fourth Industrial Revolution is definitely AI(Artificial Intelligence). Artificial intelligence's decision based on big data increases the efficiency of work processing by quickly reviewing a large amount of data and reducing time and cost. As a result, artificial intelligence technology has begun to be used in all areas of society, and it is expected to be an anti-corruption policy tool against hiring-related corruption and irregularities that raise doubts about trust and process. However, if there is no proper control over artificial intelligence, artificial intelligence can rather strengthen prejudice and infringe on job seekers' personal information. This is because the data based on artificial intelligence's decisions have been accumulated for a long time, so discrimination and prejudice against race, gender, or certain groups in the past can be revealed or reflected in algorithm design. Moreover, since artificial intelligence's decision-making process is difficult to present procedures and grounds that can be generally understood through self-learning, there is a situation in which humans have to accept machine decisions as they are in a difficult state to refute or correct. Therefore, while maximizing the utility of high-tech technology, it is necessary to find a way to use artificial intelligence without damaging human dignity and value.
As a way to guarantee the personal rights of artificial intelligence's decision-making, the exclusive decision of artificial intelligence should be limited by referring to the European Personal Information Protection Regulations and the final decision authority should be placed on humans. In addition, it is necessary to set guidelines based on careful analysis by audit agencies, the government, ethics committees, and psychological experts for legal and ethical problems that arise in the hiring process using artificial intelligence. It is more urgent to prepare effective specific procedures to prevent and monitor the risks of technology. As the hiring process is the first step in getting a job, which is a means of self-realization, evaluation according to equality of opportunities and job competency is important. We hope that practical and balanced clear laws will be created through intense discussions by legal, philosophical and technical experts. The most important proposition is that artificial intelligence is a tool that helps humans make decisions, and its ethics always depend on the person who makes the tool.