Temat: Cyber - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Cyber-physical test environment for the identification of interacting wear effects in feed axes
Autorzy:: Bott, Alexander
Stöbel, Robin
Osen, Gregor
Fleischer, Jürgen
Powiązania:: https://bibliotekanauki.pl/articles/2200264.pdf
Data publikacji:: 2023
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: machine dynamics
wear effect
feed axes
cyber-physical system
Opis:: For a comprehensive optimization and control of production processes, cyber-physical systems are necessary to include machines' time-dependent properties. These wear effects in machine tools, especially the feed axes, can significantly influence the process quality and are a steady research focus. However, the interaction of wear effects between different feed axes has received little attention. Especially models that represent the combined wear influence of different interacting feed axes on the control parameters and machine dynamics hold great potential. To close this knowledge gap, this paper proposes a cyber-physical test environment to identify the interaction of wear effects in feed axes. For this test environment, the relevant boundary conditions of different feed axes in machine tools and their systematic interaction are presented. Through these conditions, a physical test setup is derived and, analogous to this, a virtual model is created. This holistic approach represents the physical and virtual interaction between different components.
Źródło:: Journal of Machine Engineering; 2023, 23, 1; 123--132
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Towards safe service ecosystems for production for value networks and manufacturing monitoring
Autorzy:: Lemme, Gordon
Lemme, Diana
Nölscher, Kilian Armin
Ihlenfeldt, Steffen
Powiązania:: https://bibliotekanauki.pl/articles/100173.pdf
Data publikacji:: 2020
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: distributed ledger
service ecosystem
cyber-pysical production system
value networks
Opis:: In a global sales market with networked production steps and increasing complex machine tools, scaling service ecosystems for production provide an adequate solution for handling the generated data. The existing sensor equipment at current and the extension possibility by the System-of-Systems approach for existing machine tools can offer value-added services by the smart handling of production-related data. It is important to make these data validatable and exchangeable, taking into account to different protection goals. The trust of the individual actors in such a volatile value chain and the different (partly cross-border) value creation partners play an important role. The participation of a large number of these actors creates an attractive overall system (ecosystem) with lots of services and network effects. Concerning data security there are numerous aspects, which have not been adequately answered or taken into account in the use of a service ecosystem in the production environment. The paper discusses a distributed ecosystem for production on a distributed ledger-based service ecosystem, in which services can be mapped in the machine tool environment (e.g. calibration). This technology can be used for secure data exchange in order to discuss traceability and unchangeability of data while maintaining data sovereignty.
Źródło:: Journal of Machine Engineering; 2020, 20, 1; 117-126
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: A new generation of production with Cyber-Physical Systems – enabling the biological transformation in manufacturing
Autorzy:: Neugebauer, Reimund
Ihlenfeldt, Steffen
Schließmann, Ursula
Hellmich, Arvid
Noack, Marian
Powiązania:: https://bibliotekanauki.pl/articles/99713.pdf
Data publikacji:: 2019
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: biological transformation
Cyber-Physical Production Systems
future manufacturing systems
machine tools
Opis:: Within 200 years since the industrial revolution manufacturing systems have often changed their faces. Emerging nations, new markets, new inventions and the changing needs of the society forced them to adapt. Until today, the arising challenges are immensely diverse: highly individualized products, decreasing manufacturing time, limited resources and critical ecological footprints are only a few of them. Oftentimes solutions for these issues and other future requirements can be found by interrogating nature. Applying knowledge of biological principles to industrial manufacturing processes is recently referred to as "biological transformation of manufacturing systems". Hereby three levels of a biological transformation are introduced, starting from inspiration over integration to the interaction of biological and technical systems. The paper illustrates the idea of biological transformation with specific examples for each level. On the inspiration-level the design of manufacturing systems with elements of natural ecosystems is described. Thus flexibility is increased, material cycles are closed and waste will be reduced. Furthermore the integration-level is illustrated by the use of microorganisms in cutting fluids. Finally, evolutionary computing within an automatic joining cell is shown as an example for the interaction-level.
Źródło:: Journal of Machine Engineering; 2019, 19, 1; 5-15
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Integration of Advanced Monitoring in Manufacturing Systems
Autorzy:: Oborski, P.
Powiązania:: https://bibliotekanauki.pl/articles/99709.pdf
Data publikacji:: 2015
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: integrated monitoring system
manufacturing
multiagent systems
cyber-physical systems
shop floor control
Opis:: Novel concept of monitoring systems integration, reference models and test application for manufacturing are presented in the paper. Research results are an answer for industry needs for development of IT solutions that will allow to integrate information flow in production systems. The idea of standalone advanced monitoring devices connection with Shop Floor Control, MRP/ERP and machine operators is discussed. The concept of monitoring systems integration has been formally described by reference models. They corresponds with original multilayer data structure proposed on the base of data tree. Data model allows to describe orders, products, processes and to save monitoring results. Both kind of models has been the base for implementation of the integrated monitoring system demonstrator. The demonstrator developed in the frame of research was built on the base of multiagent technology. It allows to keep high flexibility and openness of the system, as well as easy implementation of various intelligent algorithms for data processing. Currently, an application of integrated monitoring system for real production system is developed. The main problems and future development of monitoring integration in discrete production are presented and discussed in the article.
Źródło:: Journal of Machine Engineering; 2015, 15, 2; 55-68
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

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

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Skocz do pozycji: 6.

Tytuł:: Intelligent production systems in the era of Industrie 4.0 – changing mindsets and business models
Autorzy:: Uhlmann, E.
Hohwieler, E.
Geisert, C.
Powiązania:: https://bibliotekanauki.pl/articles/99773.pdf
Data publikacji:: 2017
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: Industrie 4.0
internet of things (IoT)
cyber-physical systems
Industrial Product-Service Systems
condition monitoring
predictive maintenance
Opis:: Industrie 4.0 has been becoming one of the most challenging topic areas in industrial production engineering within the last decade. The increasing and comprehensive digitization of industrial production processes allows the introduction of innovative data-driven business models using cyber-physical systems (CPS) and Internet of Things (IoT). Efficient and flexible manufacturing of goods assumes that all involved production systems are capable of fulfilling all necessary machining operations in the desired quality. To ensure this, production systems must be able to communicate and interact with machines and humans in a distributed environment, to monitor the wear condition of functionally relevant components, and to self-adapt their behaviour to a given situation. This article gives an overview about the historical development of intelligent production systems in the context of value-adding business models. The focus is on condition monitoring and predictive maintenance in an availability oriented business model. Technical as well as organizational prerequisites for an implementation in the production industry are critically analysed and discussed on the basis of best practice examples. The paper concludes with a summary and an outlook on future research topics that should be addressed.
Źródło:: Journal of Machine Engineering; 2017, 17, 2; 5-24
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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