Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "intelligent production systems" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-3 z 3
    Tytuł:
    Production Optimization by Cognitive Technologies
    Autorzy:
    Schmitt, R.
    Wagels, C.
    Isermann, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/971238.pdf
    Data publikacji:
    2009
    Wydawca:
    Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
    Tematy:
    cognitive tolerance matching
    self-optimization
    SOAR
    cognition
    intelligent production systems
    Opis:
    Today, value chains are considered fractionally and on the basis of simplified model assumptions. Interactions between processes, materials, means of production and individuals acting in this environment as well as the effect of changes on the product usually are not known exhaustively. In order to take corrective actions towards these deficits, self-optimizing production system technologies can be used. They provide systems that emulate the "human" ability of reaching a decision with technical architectures. The goal of these approaches is to steadily analyze and evaluate the actual status in technological as well as in organisational areas and conduct a system adaptation to alternating objectives. Central questioning in this field of research is how to survey production data in order to detect correlations of production parameters and their influence on product parameters, how to derive decisions from this knowledge and how to learn from the consequences. Application technologies capable of taking on these tasks of self-optimization to emulate intelligent behaviour are analysed. The aim is to identify the competencies of these technologies, in order to build a cognitive system architecture based on applications especially suited for each task that has to be fulfilled to emulate cognitive human decision making processes.
    Źródło:
    Journal of Machine Engineering; 2009, 9, 1; 78-90
    1895-7595
    2391-8071
    Pojawia się w:
    Journal of Machine Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Basics of the management system for transformations of production planning and control processes
    Autorzy:
    Łopatowska, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/409542.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
    Tematy:
    Intelligent Manufacturing Systems
    production
    production planning and control
    Opis:
    Intensive development of technologies, in particular of the spinotronics, nanotechnology, robotics, and ICT, shapes the new generation production systems. Their distinctive feature is the flexibility associated with production intelligence. It is required from all processes, including the production planning and control processes (PPCP). The article is of conceptual character. It was prepared based on literature research. It encompasses issues related to Next Generation Manufacturing Systems, including Intelligent Manufacturing Systems in particular, covering solutions for PPCP. The article was also built upon the results of research on the level of automation of Polish manufacturing enterprises. The research results in the development of general assumptions of an informatic management system for the transformation of PPCP for technologically advanced and organizational production systems. The system has a modular structure resulting from its functions, which include identifying the need for transformation, its goals and vision, planning, design, implementation and evaluation of transformation. It takes the technical, organizational, socio-psychological and economic aspects of transformation into account. Choosing the right solutions for PPCP purposes allows for flexible adaptation to the requirements and needs of the environment. Its essential part is the knowledge database, thanks to which it is possible to shape the system’s intelligence.
    Źródło:
    Research in Logistics & Production; 2018, 8, 4; 317-328
    2083-4942
    2083-4950
    Pojawia się w:
    Research in Logistics & Production
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Solving scheduling problems with integrated online sustainability observation using heuristic optimization
    Autorzy:
    Burduk, Anna
    Musiał, Kamil
    Balashov, Artem
    Batako, Andre
    Safonyk, Andrii
    Powiązania:
    https://bibliotekanauki.pl/articles/2173719.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    production scheduling
    sustainable development
    genetic algorithm
    meta-heuristics
    intelligent optimization methods of production systems
    tabu search
    harmonogramowanie produkcji
    zrównoważony rozwój
    algorytm genetyczny
    przeszukiwanie tabu
    metaheurystyki
    inteligentne metody optymalizacji systemów produkcyjnych
    Opis:
    The paper deals with the issue of production scheduling for various types of employees in a large manufacturing company where the decision-making process was based on a human factor and the foreman’s know-how, which was error-prone. Modern production processes are getting more and more complex. A company that wants to be competitive on the market must consider many factors. Relying only on human factors is not efficient at all. The presented work has the objective of developing a new employee scheduling system that might be considered a particular case of the job shop problem from the set of the employee scheduling problems. The Neuro-Tabu Search algorithm and the data gathered by manufacturing sensors and process controls are used to remotely inspect machine condition and sustainability as well as for preventive maintenance. They were used to build production schedules. The construction of the Neuro-Tabu Search algorithm combines the Tabu Search algorithm, one of the most effective methods of constructing heuristic algorithms for scheduling problems, and a self-organizing neural network that further improves the prohibition mechanism of the Tabu Search algorithm. Additionally, in the paper, sustainability with the use of Industry 4.0 is considered. That would make it possible to minimize the costs of employees’ work and the cost of the overall production process. Solving the optimization problem offered by Neuro-Tabu Search algorithm and real-time data shows a new way of production management.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 6; art. no. e143830
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies