Showing papers by "Wrocław University of Technology published in 2023"

Maintenance Performance in the Age of Industry 4.0: A Bibliometric Performance Analysis and a Systematic Literature Review

Abstract: Recently, there has been a growing interest in issues related to maintenance performance management, which is confirmed by a significant number of publications and reports devoted to these problems. However, theoretical and application studies indicate a lack of research on the systematic literature reviews and surveys of studies that would focus on the evolution of Industry 4.0 technologies used in the maintenance area in a cross-sectional manner. Therefore, the paper reviews the existing literature to present an up-to-date and content-relevant analysis in this field. The proposed methodology includes bibliometric performance analysis and a review of the systematic literature. First, the general bibliometric analysis was conducted based on the literature in Scopus and Web of Science databases. Later, the systematic search was performed using the Primo multi-search tool following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The main inclusion criteria included the publication dates (studies published from 2012–2022), studies published in English, and studies found in the selected databases. In addition, the authors focused on research work within the scope of the Maintenance 4.0 study. Therefore, papers within the following research fields were selected: (a) augmented reality, (b) virtual reality, (c) system architecture, (d) data-driven decision, (e) Operator 4.0, and (f) cybersecurity. This resulted in the selection of the 214 most relevant papers in the investigated area. Finally, the selected articles in this review were categorized into five groups: (1) Data-driven decision-making in Maintenance 4.0, (2) Operator 4.0, (3) Virtual and Augmented reality in maintenance, (4) Maintenance system architecture, and (5) Cybersecurity in maintenance. The obtained results have led the authors to specify the main research problems and trends related to the analyzed area and to identify the main research gaps for future investigation from academic and engineering perspectives.

Traffic-aware service relocation in software-defined and intent-based elastic optical networks

Abstract: The paper focuses on the efficient dynamic routing of unicast and data center (dc)-related requests in elastic optical networks (eons) implementing software-defined networking (sdn) and intend-based networking (ibn) paradigms. To improve the network performance (measured as a ratio of the accepted traffic), we apply the service relocation (i.e., the adaptive process of changing the assigned dc for an anycast request). To enable a realistic case study, we propose a novel traffic model for dc-oriented and intent-based transport networks. The model reflects patterns observed in real networks and relates them with the economic and demographic parameters of the cities associated with network nodes. Then, we propose a dedicated allocation algorithm and introduce 21 different service relocation policies. These are traffic- and network-aware approaches, which use three data types for decision-making — traffic prediction, bit-rate rejection history, and topological network characteristics. Finally, we perform extensive simulations to: (i) tune the proposed optimization approaches, (ii) compare their efficiency and select the best one, (iii) determine benefits provided by the traffic- and network-aware service relocation in sdn/ibn optical networks. The results prove a high efficiency of the proposed policies, which allowed to serve up to 5.39% more traffic compared to the network with the fixed dc assignment. They also reveal that the most efficient policy makes its decisions based on traffic prediction.

RAFEN – Regularized Alignment Framework for Embeddings of Nodes

Abstract: Learning representations of nodes has been a crucial area of the graph machine learning research area. A well-defined node embedding model should reflect both node features and the graph structure in the final embedding. In the case of dynamic graphs, this problem becomes even more complex as both features and structure may change over time. The embeddings of particular nodes should remain comparable during the evolution of the graph, what can be achieved by applying an alignment procedure. This step was often applied in existing works after the node embedding was already computed. In this paper, we introduce a framework – RAFEN – that allows to enrich any existing node embedding method using the aforementioned alignment term and learning aligned node embedding during training time. We propose several variants of our framework and demonstrate its performance on six real-world datasets. RAFEN achieves on-par or better performance than existing approaches without requiring additional processing steps.

Angular Backlashes Monitoring in Heavy Industrial Machines

Abstract: The heavy industrial machines are subjected to intensive wear of critical parts in the drivelines, which resulted in angular backlashes, causing high dynamic loads and abrupt failures. Backlash diagnostics is a complicated task for maintenance personnel. A comprehensive analysis of methods and instrumentation for the angular backlashes measurements in the drivelines of heavy machines in different industries is represented. The advantages and shortcomings have been shown of different principles of wear measurement in the teeth couplings, universal spindles and gearboxes of drivelines with a complex structure. The principle of backlashes measurement by the reversal motion of drives is illustrated by the computer simulation. The digital device for angular backlashes measurement is developed and created. Accuracy is estimated depending on the rotation speed and sampling rate of the signals. Results of industrial testing in the drivelines of industrial machines of different designs are demonstrated. The conditions for further implementation of this method and sensor requirements in the online monitoring systems of industrial plants are discussed.

Experiences from Pilot Implementation of AMI Systems in Poland

Abstract: For ten years Polish distribution companies have implemented several AMR and AMI pilot projects. In Poland, the Distribution System Operator (DSO) equips households with smart energy meters (e.g. in the United Kingdom – the energy supplier, which can be changed by the customer). Over these years the operators collected a lot of experience with these pilot projects. The author of this publication describes his personal experience in the research projects in which he was involved, directly or indirectly, as well ones of which he has received information about from the DSOs. This article does not present the experiences from all major AMI system projects in Poland, but only from few projects in which the author of this article participated. The author participated in projects in which the smart meters utilize a variety of different technologies: PLC, GPRS, HSCSD, RS-232, etc. In this article, however, he focuses only on his experience in working with PLC technology. This paper presents the requirements, considerations and experience gained in the development and pilot implementation of AMI systems in Poland.

Analyzing the Attitudes of Consumers to Electric Vehicles Using Bayesian Networks

Abstract: Road transport, as ‘a producer’ of carbon dioxide (CO2), causes high levels of air pollution, especially in cities. A suggested solution to this situation is the effective diffusion of electric vehicles (EVs). Regulations in the European Union aim to encourage consumers to buy electric cars. In addition, car manufacturers are constantly expanding their range of hybrid vehicles (HEVs) and EVs. Nonetheless, consumers have still many doubts regarding adopting an EV. Our survey among social media users investigates the attitudes and readiness of consumers to adopt HEVs and EVs. To investigate the factors underlying consumers’ attitudes to such vehicles, Bayesian networks were used as an exploratory tool. This paper presents results of this analysis.

O poprawie wsppracy pracodawcw z podmiotamiedukacyjnymi w sektorze budownictwa

Abstract: Artyku dotyczy problemu wsppracy pracodawcwz podmiotami edukacyjnymi w sektorze budownictwa. Odnosisi do aktualnie niezadowalajcego stanu tej wsppracy,zdiagnozowanego przez Grup Robocz ds. barier edukacyjnychi zaangaowania pracodawcw w proces ksztacenia kadr dla budownictwaSektorowej Rady ds. Kompetencji w Budownictwie.Sygnalizuje dziaania rnej wagi, ktre warto podj dla poprawytej wsppracy.

Forbidden trajectories for path integrals

Abstract: The problem of the availability of trajectories for the Feynman path integral is considered. Forbidden trajectories for single particle integrals are featured in the case of quantum tunneling across barriers. In the case of multiparticle systems of indistinguishable identical particles, some limits for the availability of cyclotron braid trajectories are demonstrated, which leads to the explanation of statistics and correlation in quantum Hall systems of interacting 2D electrons. The homotopy-type restrictions for trajectories close to general-relativity singularities are discussed with indication of quantum properties of black holes manifesting themselves at quasar luminosity or at neutron star merger collapses. The related supplementation to conventional models of accretion disk luminosity in the close vicinity of the event horizon of a super massive black hole is proposed and compared with observations.

Simulation‒Based Optimisation Model as an Element of a Digital Twin Concept for Supply Chain Inventory Control

Abstract: Supply chain management is a critical success factor for many manufacturing companies. During the pandemic period, the problem of meeting delivery on time according to customer needs has intensified in many companies around the world. Companies would like to keep inventories at a level that ensures smooth order fulfilment while minimising their own costs. Determining the optimal parameters is, however, a major challenge for Supply Chain inventory policy (SC). Combining simulation methods with optimisation techniques offers a methodology for obtaining an acceptable solution and, at the same time, provides a high degree of flexibility in the formulation of assumptions and the possibility of improving the decision-making process with respect to risk management. In this paper we present a simulation-based optimisation model to improve the quality of inventory management decisions in SC design and planning. Finally, we refer to the benefits of implementing the model in the concept of digital twins.

Optical markers of magnetic phase transition in CrSBr

Abstract: Here, we investigate the role of the interlayer magnetic ordering of CrSBr in the framework of ab initio calculations and by using optical spectroscopy techniques.

The Role of Conformity in Opinion Dynamics Modelling with Multiple Social Circles

Abstract: Interaction with others influences our opinions and behaviours. Our activities within various social circles lead to different opinions expressed in various situations, groups, and ways of communication. Earlier studies on agent-based modelling of conformism within networks were based on a single-layer approach. Contrary to that, in this work, we propose a model incorporating conformism in which a person can share different continuous opinions on different layers depending on the social circle. Afterwards, we extend the model with more components that are known to influence opinions, e.g. authority or openness to new views. These two models are then compared to show that only sole conformism leads to opinion convergence.

Towards Modification of Polyurethane Paint Coatings for Softwood Protection: Preliminary Studies of the Use of Multi Walled Carbon Nanotubes

Abstract: This article presents the results of polyurethane coatings modified with the addiction of multi walled carbon nanotubes (MWCNTs). The study investigated how the addition of MWCNTs to polyurethane paint coating in various proportions (0, 1, 2 and 4%) affects the adhesive properties of polyurethane coatings on a softwood substrate. In this study, a pull-off strength tests were performed on pine wood samples. The tests were performed 7 days after applying the last layer of varnish. The average pull-off strength for samples without the use of carbon nanotubes were 2.58 MPa, while on samples with 4% carbon nanotubes 2.62 MPa. Results revealed that the addiction of MWCNTs had no significant effect on pull-off strength.