Temat: cognitive manufacturing

Skocz do pozycji: 1.

Tytuł:: Efficient practices of cognitive technology application for smart manufacturing
Autorzy:: Sira, Mariya
Tematy:: cognitive manufacturing
cognitive technology
Industry 4.0; Pokaż więcej
Wydawca:: STE GROUP
Powiązania:: https://bibliotekanauki.pl/articles/2204125.pdf Link otwiera się w nowym oknie
Opis:: Cognitive manufacturing (CM) provides for the merging of sensor-based information, advanced analytics, and cognitive technologies, mainly machine learning in the context of Industry 4.0. Manufacturers apply cognitive technologies to review current business metrics, solve essential business problems, generate new value in their manufacturing data and improve quality. The article investigates four powerful applications for cognitive manufacturing and their influence on a company`s maintenance. The study aims to observe kinds of cognitive technology applications for smart manufacturing, distinguish their prospective gains for manufacturers and provide successful examples of their adoption. The analysis is based on the literature and report review. Assessment of the cases of technology adoption proves that cognitive manufacturing provides both enhanced knowledge management and helps organizations improve fundamental business measurements, such as productivity, product reliability, quality, safety, and yield while reducing downtime and lowering costs.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Artificial intelligence-based decision-making algorithms, Internet of Things sensing networks, and sustainable cyber-physical management systems in big data-driven cognitive manufacturing
Autorzy:: Lazaroiu, George
Androniceanu, Armenia
Grecu, Iulia
Grecu, Gheorghe
Neguriță, Octav
Tematy:: cognitive manufacturing
Artificial Intelligence of Things
cyber-physical system
big data-driven deep learning
real-time scheduling algorithm
smart device
sustainable product lifecycle management; Pokaż więcej
Wydawca:: Instytut Badań Gospodarczych
Powiązania:: https://bibliotekanauki.pl/articles/19322650.pdf Link otwiera się w nowym oknie
Opis:: Research background: With increasing evidence of cognitive technologies progressively integrating themselves at all levels of the manufacturing enterprises, there is an instrumental need for comprehending how cognitive manufacturing systems can provide increased value and precision in complex operational processes. Purpose of the article: In this research, prior findings were cumulated proving that cognitive manufacturing integrates artificial intelligence-based decision-making algorithms, real-time big data analytics, sustainable industrial value creation, and digitized mass production. Methods: Throughout April and June 2022, by employing Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, a quantitative literature review of ProQuest, Scopus, and the Web of Science databases was performed, with search terms including "cognitive Industrial Internet of Things", "cognitive automation", "cognitive manufacturing systems", "cognitively-enhanced machine", "cognitive technology-driven automation", "cognitive computing technologies", and "cognitive technologies". The Systematic Review Data Repository (SRDR) was leveraged, a software program for the collecting, processing, and analysis of data for our research. The quality of the selected scholarly sources was evaluated by harnessing the Mixed Method Appraisal Tool (MMAT). AMSTAR (Assessing the Methodological Quality of Systematic Reviews) deployed artificial intelligence and intelligent workflows, and Dedoose was used for mixed methods research. VOSviewer layout algorithms and Dimensions bibliometric mapping served as data visualization tools. Findings & value added: Cognitive manufacturing systems is developed on sustainable product lifecycle management, Internet of Things-based real-time production logistics, and deep learning-assisted smart process planning, optimizing value creation capabilities and artificial intelligence-based decision-making algorithms. Subsequent interest should be oriented to how predictive maintenance can assist in cognitive manufacturing by use of artificial intelligence-based decision-making algorithms, real-time big data analytics, sustainable industrial value creation, and digitized mass production.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Wykorzystanie kognitywnych programów agentowych we wspomaganiu procesu zarządzania produkcją
Using cognitive agents for the manufacturing process management supporting
Autorzy:: Bytniewski, Andrzej
Hernes, Marcin
Tematy:: manufacturing management
cognitive agents
business processes; Pokaż więcej
Wydawca:: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Powiązania:: https://bibliotekanauki.pl/articles/432372.pdf Link otwiera się w nowym oknie
Opis:: The article presents a conception of manufacturing process management support by using cognitive agents. The analysis existing IT solution for supporting manufacturing management process is presented in the first part of the article. Next the architecture of cognitive agent named Learning Intelligent Distribution Agent (LIDA) is described. The last part of the article presents a conception of using the LIDA agent in relation to the operations of manufacturing process management realization.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Enabling federated learning services using OPC UA, linked data and GAIA-X in cognitive production
Autorzy:: Friedrich, Christian
Vogt, Stefan
Rudolph, Franziska
Patolla, Paul
Grützmann, Jossy Milagros
Hohmeier, Orlando
Richter, Martin
Wenzel, Ken
Reichelt, Dirk
Ihlenfeldt, Steffen
Tematy:: Industry 4.0
digital manufacturing
data space
cognitive production; Pokaż więcej
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Powiązania:: https://bibliotekanauki.pl/articles/59124054.pdf Link otwiera się w nowym oknie
Opis:: Value creation in production is based on collaboration of different stakeholders and requires the secure and sovereign exchange of knowledge. Today, knowledge has mostly been built up individually and is only exchanged in a proprietary manner. This paper presents an exemplary pipeline for federated services in cross-domain and cross-company value creation networks for cognitive production. On the example of collaboratively training of a federated machine learning model, machine tool lifetime is predicted in industrial manufacturing for high-end operating resources (high-quality cutting tools). From the shop floor to the cloud, all service relevant information is structured using existing digital twin standards and a linked data approach. In particular, the Industry 4.0 Asset Administration Shell (AAS) and OPC UA are used for collecting and referencing operational and engineering data. GAIA-X connectors transfer the service relevant data through a shared data space. The solution enables intelligent analysis and decision-making under the prioritization of data sovereignty and transparency and, therefore, acts as an enabler for future collaborative, data-driven manufacturing applications.
Dostawca treści:: Biblioteka Nauki

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