Wszystkie pola: artificial intelligent - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Integration of product design and manufacturing with the use of artificial intelligent methods
Autorzy:: Kutschenreiter-Praszkiewicz, I.
Powiązania:: https://bibliotekanauki.pl/articles/99801.pdf
Data publikacji:: 2011
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: product design
manufacturing
artificial intelligence
Opis:: Product and process design is time- and cost consuming [15]. To reduce the cost of product development, it is necessary to integrate product and process design. The proposed product planning approach integrates activities involved in product design and manufacturing process. The aim of this paper is to develop a method of knowledge integration about customer needs, product and process characteristics. The range of analyses is limited to mechanical product type manufacturing for institutional customers. Customer needs are focused on functional characteristics of the product and the trade characteristics include product price, timing and warranty. Integration of functional requirements, product and process characteristics is needed to select the best product from a catalogue and adapt it to particular customer needs. From the given set of products, where a product is described by a set of attributes, the subset is chosen which roughly satisfies customer needs. Basing on artificial intelligent (AI) methods, data related to redesign and production processes is estimated.
Źródło:: Journal of Machine Engineering; 2011, 11, No. 1-2; 46-53
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Intelligent cyber-physical monitoring and control of I4.0 machining systems – an overview and future perspectives
Autorzy:: Hassan, Mahmoud
Sadek, Ahmad
Attia, M. Helmi
Powiązania:: https://bibliotekanauki.pl/articles/2052195.pdf
Data publikacji:: 2022
Wydawca:: Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:: machining process
artificial intelligence
modelling
optimisation
tool condition monitoring
Opis:: Rapid evolution in sensing, data analysis, and industrial internet of things technologies had enabled the manufacturing of advanced smart tooling. This has been fused with effective digital inter-connectivity and integrated process control intelligence to form the industry I4.0 platform. This keynote paper presents the recent advances in smart tooling and intelligent control techniques for machining processes. Self-powered wireless sensing nodes have been utilized for non-intrusive measurement of process-born phenomena near the cutting zone, as well as tool wear and tool failure, to increase confidence in the process and tool condition monitoring accuracy. Cyber-physical adaptive control approaches have been developed to optimize the cycle time and cost while eliminating machined part defects. Novel artificial intelligence AI-based signal processing and modeling approaches were developed to guarantee the generalization and practicality of these systems. The paper concludes with the outlook for future work needed for seamless implementation of these developments in industry.
Źródło:: Journal of Machine Engineering; 2022, 22, 1; 5-24
1895-7595
2391-8071
Pojawia się w:: Journal of Machine Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

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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