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    Wyświetlanie 1-6 z 6
    Tytuł:
    Smart tool-related faults monitoring system using process simulation-based machine learning algorithms
    Autorzy:
    Ebrahimi Araghizad, Arash
    Tehranizadeh, Faraz
    Kilic, Kemal
    Budak, Erhan
    Powiązania:
    https://bibliotekanauki.pl/articles/28407322.pdf
    Data publikacji:
    2023
    Wydawca:
    Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
    Tematy:
    Industry 4.0
    machining
    machine learning
    monitoring
    Opis:
    In this paper a novel approach for monitoring tool-related faults in milling processes by utilizing process simulation-based machine learning algorithms, specifically Random Forest algorithms, for fault detection is presented. In order to train machine learning models in tool condition monitoring, laboratory tests have traditionally been required. This method eliminates the need for costly, time-consuming laboratory tests. The training process has been simplified by utilizing analytical simulation data and provides a more cost-effective solution by leveraging analytical simulation data. Based on the results of this study, the proposed approach has been demonstrated to be 94% accurate at predicting tool-related faults, demonstrating its potential to serve as an efficient and viable alternative to conventional methods. These findings have been supported by actual measurement data, with a notable accuracy rate of 93% in the predictions. Furthermore, the results indicate that process simulation-based machine learning algorithms will have a significant impact on the tools condition monitoring and the efficiency of manufacturing processes more generally. To further enhance the capabilities of the proposed fault monitoring system, process-related and machine-related faults will be investigated in future research. Several machine learning algorithms will be explored as well as additional data sources will be integrated in order to enhance the accuracy and reliability of fault detection.
    Źródło:
    Journal of Machine Engineering; 2023, 23, 4; 18--32
    1895-7595
    2391-8071
    Pojawia się w:
    Journal of Machine Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Relationship Between the Implementation Levels of Industry 4.0 Technologies and Advanced Manufacturing Technologies
    Autorzy:
    Sari, Tuğba
    Powiązania:
    https://bibliotekanauki.pl/articles/2172185.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    advanced manufacturing technologies
    AMTs
    industry 4.0
    machine learning
    Opis:
    Industry 4.0 is expected to provide high quality and customized products at lower costs by increasing efficiency, and hence create a competitive advantage in the manufacturing industry. As the emergence of Industry 4.0 is deeply rooted in the past industrial revolutions, Advanced Manufacturing Technologies of Industry 3.0 are the precursors of the latest Industry 4.0 technologies. This study aims to contribute to the understanding of technological evolution of manufacturing industry based on the relationship between the usage levels of Advanced Manufacturing Technologies and Industry 4.0 technologies. To this end, a survey was conducted with Turkish manufacturers to assess and compare their manufacturing technology usage levels. The survey data collected from 424 companies was analyzed by machine learning approach. The results of the study reveal that the implementation level of each Industry 4.0 technology is positively associated with the implementation levels of a set of Advanced Manufacturing Technologies.
    Źródło:
    Management and Production Engineering Review; 2022, 13, 3; 52--60
    2080-8208
    2082-1344
    Pojawia się w:
    Management and Production Engineering Review
    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:
    Significance of Manufacturing Process Parameters in a Glassworks
    Autorzy:
    Paśko, Łukasz
    Powiązania:
    https://bibliotekanauki.pl/articles/175653.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    neural networks
    glass industry
    glass packaging
    significance of variables
    sensitivity analysis
    machine learning
    Opis:
    The article presents the use of artificial neural networks (multilayer perceptrons) to examine the significance of production process parameters. The considered problem relates to the occurrence of production periods with an increased number of defective products. The research aims to determine which of the 69 parameters of the manufacturing process most affect the number of defects. Two ways of expressing the parameters significance were used: using the sensitivity analysis and exploring the weights of connections between neurons. The results were determined using both single neural networks and a set of networks. The outcome from the research is the rankings of significance of the manufacturing process parameters. The analyzed data were obtained from a glassworks producing glass packaging.
    Źródło:
    Advances in Manufacturing Science and Technology; 2020, 44, 2; 39-45
    0137-4478
    Pojawia się w:
    Advances in Manufacturing Science and Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Logistyka wyprzedzająca, czyli innowacyjne podejście do branży e-commerce
    Anticipatory logistics – an innovative approach to the e-commerce industry
    Autorzy:
    Sczaniecka, E.
    Smarzyńska, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/2058349.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    e-commerce
    przemysł 4.0
    logistyka wyprzedzająca
    Big Data
    sztuczna inteligencja
    uczenie maszynowe
    industry 4.0
    anticipatory logistics
    artifical inteligence
    machine learning
    Opis:
    Tematem referatu jest zastosowanie logistyki wyprzedzającej w zarządzaniu przedsiębiorstwami, w szczególności w branży e-commerce. Wstęp traktuje o postępie technologicznym, który określony został mianem Przemysłu 4.0. Następnie wyjaśnione zostało pojęcie logistyki wyprzedzającej, oraz narzędzi które służą do jej skutecznego wprowadzenia. Kolejno zostały przytoczone przykłady firm, stosujących opisane rozwiązania. Na końcu znajduje się analiza SWOT wprowadzenia logistyki wyprzedzającej w przedsiębiorstwie.
    The subject of this paper is the use of anticipatory logistics in company management, particurarly in e-commerce industry. The introduction treats about technological development known as the Industry 4.0. Next, the concepts of anticipatory logistics and tools used for its effective implementation are explained. Subsequently, examples of companies using the given solutions are adduced. Finally, there is a SWOT analysis, which describes introducing anticipatory logistics in a company.
    Źródło:
    Journal of TransLogistics; 2018, 4, 1; 119--128
    2450-5870
    Pojawia się w:
    Journal of TransLogistics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A classification of real time analytics methods. An outlook for the use within the smart factory
    Autorzy:
    Trinks, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/321330.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
    Tematy:
    real time analytics
    smart factory
    Industry 4.0
    smart manufacturing
    internet of things
    machine learning
    analiza w czasie rzeczywistym
    inteligentna fabryka
    Przemysł 4.0
    inteligentna produkcja
    Internet rzeczy
    uczenie maszynowe
    Opis:
    The creation of value in a factory is transforming. The spread of sensors, embedded systems, and the development of the Internet of Things (IoT) creates a multitude of possibilities relating to upcoming Real Time Analytics (RTA) application. However, already the topic of big data had rendered the use of analytical solutions related to a processing in real time. Now, the introduced methods and concepts can be transferred into the industrial area. This paper deals with the topic of the current state of RTA having the objective to identify applied methods. In addition, the paper also includes a classification of these methods and contains an outlook for the use of them within the area of the smart factory.
    Źródło:
    Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2018, 119; 313-329
    1641-3466
    Pojawia się w:
    Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-6 z 6

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