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 manufacturing" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-9 z 9
    Tytuł:
    The Influence of Industry 4.0 on the Enterprise Competitiveness
    Autorzy:
    Stasiak-Betlejewska, R.
    Parv, L.
    Gliń, W.
    Powiązania:
    https://bibliotekanauki.pl/articles/2065005.pdf
    Data publikacji:
    2018
    Wydawca:
    STE GROUP
    Tematy:
    production
    organization
    intelligent manufacturing
    industry 4.0
    Opis:
    Contemporary enterprises are focused on the following dynamic economic, social and technical changes on the market having a big influence on the consumers and producers. Enterprises development is linked with continuous improvement of the entire organization what result in the shaping production organization. Paper presents research results on the effects of an Industry 4.0 implementing within creating Polish enterprise competiveness.
    Źródło:
    Multidisciplinary Aspects of Production Engineering; 2018, 1, 1; 641--648
    2545-2827
    Pojawia się w:
    Multidisciplinary Aspects of Production 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:
    Maintenance as a combination of intelligent IT systems and strategies: a literature review
    Autorzy:
    Metso, L.
    Baglee, D.
    Marttonen-Arola, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/406710.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    eMaintenance
    information systems
    intelligent manufacturing systems
    decision support systems
    Opis:
    This study provides a systematic review of the existing academic literature describing the key components of eMaintenance. The current literature is reviewed by utilizing a number of academic databases including Scopus, SpringerLink and ScienceDirect, and Google Search is used to find relevant academic and peer-reviewed journal articles concerning eMaintenance. The literature describes eMaintenance as an advanced maintenance strategy that takes advantage of the Internet, information and communication technologies, wireless technologies and cloud computing. eMaintenance systems are used to provide real time analyses based on real time data to offer a number of solutions and to define maintenance tasks. The collection and analysis of appropriate maintenance and process data are critical to create robust ‘maintenance intelligence’ and finally improvements in manufacturing costs, safety, environmental impact, and equipment reliability. This paper describes how the scientific discussion on eMaintenance has expanded significantly during the last decade, creating a need for an up-to-date review. As a conclusion, three research gaps in the area of eMaintenance are identified, including evaluating the benefits of eMaintenance, agreeing on a comprehensive definition, and developing tools and structures for cooperative eMaintenance.
    Źródło:
    Management and Production Engineering Review; 2018, 9, 1; 51-64
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Intelligent management in the age of Industry 4.0 – an example of a polymer processing company
    Autorzy:
    Łukasik, Katarzyna
    Stachowiak, Tomasz
    Powiązania:
    https://bibliotekanauki.pl/articles/407205.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    intelligent manufacturing
    Industry 4.0
    modern technologies
    polymer processing company
    Opis:
    In the article, the significance and essence of management of intelligent manufacturing in the era of the fourth industrial revolution has been presented. The current revolution has a large impact on the operation of the company. Through the changes resulting from the application of modern technologies, production processes are also undergoing revolutions, which results in changes in such indicators of business development. Management of intelligent manufacturing is also a challenge for socially responsible activities; due to solutions of Industry 4.0, enterprises directly and indirectly influence environmental protection, which results in benefits for all mankind. In the article, the analysis and assessment of management of intelligent manufacturing, using modern technologies during the production process, has been carried out, with particular emphasis on the components of management such as: monitoring, control, autonomy, optimization. Moreover, the impact of the above components of management on changes in the following indicators (KPI – Key Performance Indictors) has been evaluated, i.e. (1) quality, (2) rapidity of the production process implementation, (3) performance and (4) productivity, (5) decrease in waste generated during the technological process and (6) amount of consumed electricity. For the purposes of conducting the research, a case study has been used, developed due to the information shared by the company manufacturing machinery and equipment for the polymer processing industry, in which intelligent solutions of Industry 4.0 are being applied. The presented article is a significant contribution to the current development of knowledge in the field of implementing Industry 4.0 solutions for polymer processing. The article is a combination of theoretical and practical knowledge in the field of management and practical industrial applications. It refers to the most current research trends.
    Źródło:
    Management and Production Engineering Review; 2020, 11, 2; 38-49
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Intelligence in manufacturing systems: the pattern recognition perspective
    Autorzy:
    Zaremba, M. B.
    Powiązania:
    https://bibliotekanauki.pl/articles/971032.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    Intelligent Manufacturing Systems
    pattern recognition
    computational intelligence
    neural networks
    distributed systems
    spatial filtering
    feature selection
    dimensionality reduction
    Opis:
    The field of Intelligent Manufacturing Systems (IMS) has been generally equated with the use of Artificial Intelligence and Computational Intelligence methods and techniques in the design and operation of manufacturing systems. Those methods and techniques are now applied in many different technological domains to deal with such pervasive problems as data imprecision and nonlinear system behavior. The focus in IMS is now shifting to a broader understanding of the intelligent behavior of manufacturing systems. The questions debated by researchers today relate more to what kind and what level of adaptability to instill in the structure and operation of a manufacturing system, with the discussions increasingly gravitating to the issue of system self-organization. This paper explores the changing face of IMS from the perspective of the pattern recognition domain. It presents design criteria for techniques that will allow us to implement manufacturing systems exhibiting adaptive and intelligent behaviour. Examples are given to show how incorporating pattern recognition capabilities can help us build more intelligence and self-organization into the manufacturing systems of the future.
    Źródło:
    Control and Cybernetics; 2010, 39, 1; 233-258
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Integration of OPC UA information models into Enterprise Knowledge Graphs
    Autorzy:
    Weiss, Arno
    Ihlenfeldt, Steffen
    Powiązania:
    https://bibliotekanauki.pl/articles/2086280.pdf
    Data publikacji:
    2022
    Wydawca:
    Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
    Tematy:
    digital twin
    manufacturing system
    machining 4.0
    machine tool
    intelligent function
    Opis:
    Building repositories of data relevant for enterprise operations requires harmonization of formats and semantics. OPC UA’s nodes-and-references data model shares basic elements with well-established semantic modeling technologies like RDF. This paper suggests the use of transformed OPC UA information models on the higher level of Enterprise Knowledge Graphs. It proposes good practice to integrate the separate domains by representing OPC UA servers as RDF-graphs and subsequently attaching them to Digital Twins embedded in Enterprise Knowledge Graph structures. The developed practice is implemented, applied to combine a server’s structure with an existing knowledge graph containing an Asset Administration Shell and released open source.
    Źródło:
    Journal of Machine Engineering; 2022, 22, 2; 138--147
    1895-7595
    2391-8071
    Pojawia się w:
    Journal of Machine Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Development and optimization of an Automated Irrigation System
    Autorzy:
    Daniyan, Lanre
    Nwachukwu, Ezechi
    Daniyan, Ilesanmi
    Bonaventure, Okere
    Powiązania:
    https://bibliotekanauki.pl/articles/384401.pdf
    Data publikacji:
    2019
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    additive manufacturing
    automation
    irrigation
    intelligent system
    microcontroller
    produkcja dodatkowa
    automatyzacja
    nawadnianie
    mikrokontroler
    Opis:
    The deployment of appropriate technologies to enhance modern agricultural practices and improve crop yields is imperative for sustainability. This paper presents the development of a standalone automated irrigation system. The system design features good automation and control, which was achieved using an array of electronic timing system, soil feedback sensor and wireless communication system. Autonomous irrigation events are based on the states of the timing system, the soil feedback system and the wireless communication system. The control and automation of these systems was done using an AVR microcontroller, which was programmed to trigger intelligent and independent farm irrigation operation through a water pump attached to the system. The system also operates remotely via SMS command from mobile device and sends operational status feedback via SMS to preprogrammed mobile user(s). It also sends soil moisture condition to a remote user upon query. The system package was produced using additive manufacturing technique. The power supply system was implemented using solar power system in order to achieve a standalone, autonomous and reliable power supply necessary for an independent operation. The performance evaluation of the developed system show impressive response time, good reliability and excellent stability. Furthermore, the numerical experiment conducted using the Response Surface Methodology (RSM) produced a mathematical model for the optimization of the irrigation process for optimum performance and cost effectiveness.
    Źródło:
    Journal of Automation Mobile Robotics and Intelligent Systems; 2019, 13, 1; 37-45
    1897-8649
    2080-2145
    Pojawia się w:
    Journal of Automation Mobile Robotics and Intelligent Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Machine Learning in Cyber-Physical Systems and manufacturing singularity – it does not mean total automation, human is still in the centre: Part II – In-CPS and a view from community on Industry 4.0 impact on society
    Autorzy:
    Putnik, Goran D.
    Shah, Vaibhav
    Putnik, Zlata
    Ferreira, Luis
    Powiązania:
    https://bibliotekanauki.pl/articles/1428709.pdf
    Data publikacji:
    2021
    Wydawca:
    Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
    Tematy:
    human role
    artificial intelligence
    machine learning
    manufacturing singularity
    intelligent machine architecture
    cyber-physical systems
    Industry 4.0
    Opis:
    In many discourses, popular as well as scientific, it is suggested that the "massive" use of Artificial Intelligence (AI), including Machine Learning (ML), and reaching the point of "singularity" through so-called Artificial General Intelligence (AGI), and Artificial Super-Intelligence (ASI), will completely exclude humans from decision making, resulting in total dominance of machines over human race. Speaking in terms of manufacturing systems, it would mean that the intelligence and total automation would be achieved (once the humans are excluded). The hypothesis presented in this paper is that there is a limit of AI/ML autonomy capacity, and more concretely, the ML algorithms will be not able to become totally autonomous and, consequently, the human role will be indispensable. In the context of the question, the authors of this paper introduce the notion of the manufacturing singularity and present an intelligent machine architecture towards the manufacturing singularity, arguing that the intelligent machine will always be human dependent. In addition, concerning the manufacturing, the human will remain in the centre of Cyber-Physical Systems (CPS) and in Industry 4.0. The methodology to support this argument is inductive, similarly to the methodology applied in a number of texts found in literature, and based on computational requirements of inductive inference based machine learning. The argumentation is supported by several experiments that demonstrate the role of human within the process of machine learning. Based on the exposed considerations, a generic architecture of intelligent CPS, with embedded ML functional modules in multiple learning loops, is proposed in order to evaluate way of use of ML functionality in the context of CPS. Similar to other papers found in literature, due to the (informal) inductive methodology applied, considering that this methodology does not provide an absolute proof in favour of, or against, the hypothesis defined, the paper represents a kind of position paper. The paper is divided into two parts. In the first part a review of argumentation from literature in favour of and against the thesis on the human role in future was presented, as well as the concept of the manufacturing singularity was introduced. Furthermore, an intelligent machine architecture towards the manufacturing singularity was proposed, arguing that the intelligent machine will be always human dependent and, concerning the manufacturing, the human will remain in the centre. The argumentation is based on the phenomenon related to computational machine learning paradigm, as intrinsic feature of the AI/ML1, through the inductive inference based ML algorithms, whose effectiveness is conditioned by the human participation. In the second part, an architecture of the Cyber-Physical (Production) Systems (CPPS) with multiple learning loops is presented, together with a set of experiments demonstrating the indispensable human role. Finally, a discussion of the problem from the manufacturing community point of view on future of human role in Industry 4.0 as the environment for advanced AI/ML applications is registered.
    Źródło:
    Journal of Machine Engineering; 2021, 21, 1; 133-153
    1895-7595
    2391-8071
    Pojawia się w:
    Journal of Machine Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Tabu Search and genetic algorithm for production process scheduling problem
    Tabu Search i algorytmy genetyczne w harmonogramowaniu procesów produkcyjnych
    Autorzy:
    Burduk, Anna
    Musiał, Kamil
    Kochańska, Joanna
    Górnicka, Dagmara
    Stetsenko, Anastasia
    Powiązania:
    https://bibliotekanauki.pl/articles/361796.pdf
    Data publikacji:
    2019
    Wydawca:
    Wyższa Szkoła Logistyki
    Tematy:
    production process scheduling
    Tabu Search
    genetic algorithm
    heuristic methods
    intelligent methods
    manufacturing
    harmonogramowanie procesów produkcyjnych
    algorytm genetyczny
    metody heurystyczne
    metody inteligentne
    wytwarzanie
    Opis:
    Background: The paper deals with production process scheduling problem. In large companies, the decision-making process about operators' work, machines availability and production flow is a very difficult task, which is often being done by employees. Thus, not always the decision made is optimal in terms of cost, production time, etc. Methods: As a solution, two intelligent methods: Tabu Search and the genetic algorithm have been analyzed in field of production scheduling. The aim of this work was to examine the possibility of improving presented decision-making process that is being performed when scheduling, using Tabu Search and genetic algorithms. As a result of experimental research, it has been confirmed that the use of appropriately selected and parameterized intelligent methods allows for the optimization of the analyzed production process due to its duration. The research was case of study performed in cooperation with company that produces components for automotive industry. Results: Basing on collected and analyzed data, considered methods can be more or less successfully used in production process scheduling. Comparing both used algorithms, Tabu Search twice proposed worse solutions, the average operational time was 1.63% shorter than the actual one. In this case, better results were reached by using genetic algorithm - potential operational time was always shorter than the actual one, and it was reduced by 6.3% in total on average. Conclusion: Using algorithms allowed to achieve lower workload of employees and to reduce of operational time, which were the evaluation criteria in performed research. Managers of the analyzed company were pleased with the proposed solution and declared interest in developing these methods for future. This shows that intelligent methods can find, in relatively short time, the solution that is close to the optimal and acceptable from the problem point of view.
    Wstęp: Artykuł opisuje problem harmonogramowania procesów produkcyjnych. W dużych przedsiębiorstwach proces podejmowania decyzji dotyczących pracy operatorów, maszyn, dostępności zasobów i przepływu produkcji jest bardzo złożonym zadaniem, często wykonywanym przez pracowników. W związku z tym podjęte decyzje nie zawsze są optymalne w kontekście kosztów, czasu produkcji itp. Metody: Jako rozwiązanie, przeanalizowane zostało użycie, w obszarze harmonogramowania produkcji, dwóch metod inteligentnych: Tabu Search i algorytmów genetycznych. Celem pracy było zbadanie możliwości doskonalenia procesu podejmowania decyzji, który jest wykonywany przy harmonogramowaniu produkcji, przy pomocy Tabu Search i algorytmów genetycznych. Jako wynik eksperymentu przeprowadzonego podczas badań, potwierdzono, że użycie odpowiednio wybranych oraz sparametryzowanych metod inteligentnych pozwala na optymalizację analizowanego procesu produkcji. Badania zostały wykonane we współpracy z przedsiębiorstwem zajmującym się produkcją komponentów dla branży motoryzacyjnej, jako studium przypadku. Wyniki: Zgodnie z zebranymi i przeanalizowanymi danymi, wybrane metody mogą być z mniejszym bądź większym powodzeniem stosowane w procesie harmonogramowania produkcji. Porównując zastosowane algorytmy, Tabu Search dwukrotnie zaproponował rozwiązanie gorsze od aktualnego podejścia przedsiębiorstwa, jednak czas produkcji został skrócony średnio o 1.63%. W tym przypadku, lepsze wyniki pozwoliło osiągnąć zastosowanie algorytmu genetycznego - potencjalny czas produkcji był zawsze krótszy od aktualnie stosowanego rozwiązania, a średni czas produkcji został zredukowany o 6.3%. Wnioski: Zastosowanie algorytmów pozwoliło na osiągnięcie niższego obciążenia pracą operatorów oraz zredukowanie czasu operacyjnego, co stanowiło kryteria oceny w przeprowadzonych badaniach. Kierownictwo analizowanego przedsiębiorstwa było zadowolone z zaproponowanych rozwiązań. Zdecydowali się na stosowanie omawianych metod w codziennym harmonogramowaniu produkcji oraz zadeklarowali zainteresowanie rozwojem stosowania metod w przyszłości. Metody inteligentne pozwalają znaleźć, w relatywnie krótkim czasie, rozwiązanie bliskie optymalnemu i akceptowalne z punktu widzenia analizowanego problemu.
    Źródło:
    LogForum; 2019, 15, 2; 181-189
    1734-459X
    Pojawia się w:
    LogForum
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-9 z 9

      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