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Autonomiczny transport w Przemyśle 4.0

100%

Malaka J.

tom Nr 1

50--54

Czwarta rewolucja przemysłowa wiąże się z określonymi rozwiązaniami charakteryzującymi nowoczesną fabrykę. Technika wewnątrzzakładowego obiegu rzeczy jest nieustannie rozwijana w kierunku wpasowania się w obowiązujące trendy. Czy postęp w tym zakresie doprowadził już do poziomu autonomiczności, który można sygnować dopiskiem „4.0”? W artykule przedstawiono pewne cechy współczesnych maszyn transportowych warunkujące spełnienie przyjętych standardów.

The Internet of Things and AI-based optimization within the Industry 4.0 paradigm

100%

Mikołajewski D. , Czerniak J. M. , Piechowiak M. , Węgrzyn-Wolska K. , Kacprzyk J.

tom Vol. 72, nr 1

art. no. e147346

By reviewing the current state of the art, this paper opens a Special Section titled “The Internet of Things and AI-driven optimization in the Industry 4.0 paradigm”. The topics of this section are part of the broader issues of integration of IoT devices, cloud computing, big data analytics, and artificial intelligence to optimize industrial processes and increase efficiency. It also focuses on how to use modern methods (i.e. computerization, robotization, automation, machine learning, new business models, etc.) to integrate the entire manufacturing industry around current and future economic and social goals. The article presents the state of knowledge on the use of the Internet of Things and optimization based on artificial intelligence within the Industry 4.0 paradigm. The authors review the previous and current state of knowledge in this field and describe known opportunities, limitations, directions for further research, and industrial applications of the most promising ideas and technologies, considering technological, economic, and social opportunities.

Three methods of selecting a smart meter for data concentration in the automatic meter reading last mile network

80%

Kiedrowski P.

tom Vol. 72, nr 1

art. no. e146476

This paper proposes three methods of the optimal smart meter selection for acting as a data concentrator in the automatic meter reading last mile network. The study explains the reasons why the selected smart meter should also act as a data concentrator, in addition to its basic role. To select the smart meter, either the reliability of communication or the speed of the automatic meter reading process was considered. Graph theory is employed to analyse the last mile network, described as sets of nodes and unreliable links. The frame error ratio was used to assess the unreliability whilst the number of hops was used to describe the speed of the reading process. The input data for the analysis are qualitative parameters determined based on observations in the real, operated last mile networks as well as their typical topological arrangements. The results of the research can be useful in the last mile network migration process, which uses concentrators to the networks without them, or during the process of newer last mile network implementation, where data concentrators are no longer applicable. The efficiency of the proposed methods is assessed measurably.