János Abonyi

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Verified

János verified their affiliation via an institutional email.

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• PhD, DSc
• Professor (Full) at University of Pannonia

The identification of process faults is a complex and challenging task due to the high amount of alarms and warnings of control systems. To extract information about the relationships between these discrete events, we utilise multitemporal sequences of alarm and warning signals as inputs of a recurrent neural network–based classifier and visualise...

The fast development of smart sensors and wearable devices has provided the opportunity to develop intelligent operator workspaces. The resultant Human-Cyber-Physical Systems (H-CPS) integrate the operators into flexible and multi-purpose manufacturing processes. The primary enabling factor of the resultant Operator 4.0 paradigm is the integration...

The design and retrofit of Heat Exchanger Networks (HENs) can be based on several objectives and optimisation algorithms. As each method results in an individual network topology that has a significant effect on the operability of the system, control-relevant HEN design and analysis are becoming more and more essential tasks. This work proposes a n...

Network analysis can be applied to understand organizations based on patterns of communication, knowledge flows, trust, and the proximity of employees. A multidimensional organizational network was designed, and association rule mining of the edge labels applied to reveal how relationships, motivations, and perceptions determine each other in diffe...

This work presents how recent trends in Industry 4.0 (I4.0) solutions are influencing the development of manufacturing execution systems (MESs) and analyzes what kinds of trends will determine the development of the next generation of these technologies. This systematic and thematic review provides a detailed analysis of I4.0-related requirements i...

Hypergraphs provide a robust framework for modeling complex, multi-actor interactions that traditional graphs struggle to represent. In many real-world applications, interactions involve more than just pairs of entities, which makes hypergraphs an essential tool for capturing these multidimensional relationships. Although there are various visualiz...

Background Interval estimates are a common way to express uncertain knowledge of experts. To model them and aggregate multiple judgments, both the probability and possibility theories are applicable. Previous studies have shown that the performances of the aggregated distributions obtained by these two approaches are similar on average; however, th...

This study investigates the learning curve in an assembly process under distraction, highlighting the use of video‐based monitoring to evaluate changes in human performance over time. The experimental setup involving camera‐ and timer‐based monitoring to evaluate operator performance in different metrics, including time‐based indicators and accurac...

The study aims to optimize internal logistics processes by applying Lean philosophy and data science tools, with a primary focus on qualifying processes to determine their value-added contribution within the logistics context. Utilizing a novel two-step methodology, the research first employs a modified DBSCAN algorithm to analyze indoor positionin...

The effect of work content on workload, stress, and performance was not well addressed in the literature, due to the lack of comprehensive conceptualization, problem definition, and relevant dataset. The gap between laboratory-simulated studies and real-life working conditions delays the generalization, hindering the development of performance mana...

This paper introduces a methodology for handling different types of uncertainties during robust optimization. In real-world industrial optimization problems, many types of uncertainties emerge, e.g., inaccurate setting of control variables, and the parameters of the system model are usually not known precisely. For these reasons, the global optimum...

In the context of hierarchical system modeling, ensuring constraints between different hierarchy levels are met, so, for instance, ensuring the aggregation constraints are satisfied, is essential. However, modelling and forecasting each element of the hierarchy independently introduce errors. To mitigate this balance error, it is recommended to emp...

This study presents a model-based parameter estimation method for integrating and validating uncertainty in expert knowledge and simulation models. The parameters of the models of complex systems are often unknown due to a lack of measurement data. The experience-based knowledge of experts can substitute missing information, which is usually imprec...

Machine learning (ML) revolutionized traditional machine fault detection and identification (FDI), as complex-structured models with well-designed unsupervised learning strategies can detect abnormal patterns from abundant data, which significantly reduces the total cost of ownership. However, their opaqueness raised human concern and intrigued the...

Supply chain optimization and resource allocation are challenging because of the complex dynamics of flows. We can classify these flows based on whether they perform value-added or nonvalue-added activities in our process. The aim of this article is to present a multilayered temporal network-based model for the analysis of network flows in supply c...

This article focuses on improving indoor positioning data through data reconciliation. Indoor positioning systems are increasingly used for resource tracking to monitor manufacturing and warehouse processes. However, measurement errors due to noise can negatively impact system performance. Redundant measurement involves the use of multiple sensor t...

This paper highlights that metrics from the machine learning field (e.g., entropy and information gain) used to qualify a classifier model can be used to evaluate the effectiveness of separation systems. To evaluate the efficiency of separation systems and their operation units, entropy- and information gain-based metrics were developed. The receiv...

The Operator 5.0 concept calls for the self-resilience of operators in Industry 5.0, including the cognitive aspect. Despite attempts to develop supporting technologies, achieved results are loosely connected without a comprehensive approach. Looking for novel expectations, this study seeks inspiration from a chaotic environment, where cognitive re...

Identifying communities in multilayer networks is crucial for understanding the structural dynamics of complex systems. Traditional community detection algorithms often overlook the presence of overlapping edges within communities, despite the potential significance of such relationships. In this work, we introduce a novel modularity measure design...

Model-based assessment of the potential impacts of variables on the Sustainable Development Goals (SDGs) can bring great additional information about possible policy intervention points. In the context of sustainability planning, machine learning techniques can provide data-driven solutions throughout the modeling life cycle. In a changing environm...

Frequent sequence pattern mining is an excellent tool to discover patterns in event chains. In complex systems, events from parallel processes are present, often without proper labelling. To identify the groups of events related to the subprocess, frequent sequential pattern mining can be applied. Since most algorithms provide too many frequent seq...

In real-world classification problems, it is important to build accurate prediction models and provide information that can improve decision-making. Decision-support tools are often based on network models, and this article uses information encoded by social networks to solve the problem of employer turnover. However, understanding the factors behi...

The importance of highly monitored and analyzed processes, linked by information systems such as knowledge graphs, is growing. In addition, the integration of operators has become urgent due to their high costs and from a social point of view. An appropriate framework for implementing the Industry 5.0 approach requires effective data exchange in a...

This paper presents a methodology that aims to enhance the accuracy of probability density estimation in mobility pattern analysis by integrating prior knowledge of system dynamics and contextual information into the particle filter algorithm. The quality of the data used for density estimation is often inadequate due to measurement noise, which si...

The parameter identification of failure models for composite plies can be cumbersome, due to multiple effects as the consequence of brittle fracture. Our work proposes an iterative, nonlinear design of experiments (DoE) approach that finds the most informative experimental data to identify the parameters of the Tsai-Wu, Tsai-Hill, Hoffman, Hashin,...

We analyzed a special class of graph traversal problems, where the distances are stochastic, and the agent is restricted to take a limited range in one go. We showed that both constrained shortest Hamiltonian pathfinding problems and disassembly line balancing problems belong to the class of constrained shortest pathfinding problems, which can be r...

As the environmental aspects become increasingly important, the disassembly problems have become the researcher’s focus. Multiple criteria do not enable finding a general optimization method for the topic, but some heuristics and classical formulations provide effective solutions. By highlighting that disassembly problems are not the straight inver...

The utility function-based sum of ranking differences (uSRD) method is proposed as a utility function-based multi-criteria decision analysis tool. Our idea is that the transformation functions can be represented by a utility function that can be aggregated with multi-attribute utility functions. We present a framework incorporating utility values a...

The design and functionality of the human–machine interface (HMI) significantly affects operational efficiency and safety related to process control. Alarm management techniques consider the cognitive model of operators, but mainly only from a signal perception point of view. To develop a human-centric alarm management system, the construction of a...

Detecting chemical, biological, radiological and nuclear (CBRN) incidents is a high priority task and has been a topic of intensive research for decades. Ongoing technological, data processing, and automation developments are opening up new potentials in CBRN protection, which has become a complex, interdisciplinary field of science. According to i...

This paper proposes a monitoring procedure based on characterizing state probability distributions estimated using particle filters. The work highlights what types of information can be obtained during state estimation and how the revealed information helps to solve fault diagnosis tasks. If a failure is present in the system, the output predicted...

Well-being is a critical element of the 2030 Agenda for Sustainable Development Goals. Given the complexity of the concept of well-being, it follows that its measurement requires complex, multivariate methods that can characterize the physical, economic, social and environmental aspects along with the mental state of a city. Although it is not suff...

The paramount importance of proficient information management for the progression of manufacturing processes, particularly within the purview of smart manufacturing, necessitates suitable modeling and comprehensive examination of crucial, interacting elements. The objective of this book is to propose a framework predicated on an ontology model for...

Adequate information management is critical for the development of manufacturing processes. Therefore, this chapter aims to provide a systematic overview of ontologies that can be utilized in building Industry 4.0 applications and highlights that ontologies are suitable for manufacturing management. Additionally, industry-related standards and othe...

This chapter introduces a novel, combined analytic hierarchy process and multilayer network-based method for assembly line balancing. Assembly line balancing improves the efficiency of production systems by the optimal assignment of tasks to operators. The optimization of this assignment requires models that provide information about the activity t...

This chapter aims to verify that ontology-based modeling can be utilized to create structured and contextualized models that can support the development of the manufacturing process. The applicability of ontology-based process modeling and data analysis is demonstrated on a wire-harness assembly-based benchmark, where semantic modeling and data que...

This Chapter aims to serve as a source list for researchers and engineers interested in the topic of ontology-based modeling and optimization. Each tools are explained briefly and the sources for the software tools are provided.

The concept of a data ecosystem and Industry 4.0 requires high-level vertical and horizontal interconnectivity across the entire value chain. Its successful realisation demands standardised data models to ensure transparent, secure and widely integrable data sharing within and between enterprises. This chapter provides a PRISMA method-based systema...

This chapter presents how communities in networks can be detected by integrating barycentric serialization with bottom-up segmentation. Because nodes are efficiently ordered according to their neighbors by barycentric serialization, the segmentation algorithm provides modules in a computationally more efficient manner than the most frequently used...

This chapter aims to present a hypergraph-based analysis method. The design of these Operator 4.0 solutions requires a problem-specific description of manufacturing systems, the skills, and states of the operators, as well as of the sensors placed in the intelligent space for the simultaneous monitoring of the collaborative work. The design of a co...

This chapter proposes the Human-Centric Knowledge Graph (HCKG) framework by adapting ontologies and standards that can model the operator-related factors such as monitoring movements, working conditions or collaboration with robots. Furthermore, graph-based data queries, visualization and analytics are also presented in the form of an industrial ca...

The previous part of this book showed a variety of applications and highlighted the advantages of semantic technologies in modern industry. Following the advised graph-based data access approach, this chapter aims to give an overview of some of the possible analytic methods and optimization procedures that can be utilized on graph networks. The mot...

The rapid advancement of technology related to Industry 4.0 has brought about a paradigm shift in the way we interact with assets across various domains. This progress has led to the emergence of the concept of a Human Digital Twin (HDT), a virtual representation of an individual’s cognitive, psychological, and behavioral characteristics. The HDT h...

This article aims to integrate k-NN regression, false-nearest neighborhood (FNN), and trustworthiness and continuity (T&C) neighborhood-based measures into an efficient and robust feature selection method to support the identification of nonlinear regression models. The proposed neighborhood ranking-based feature selection technique (NRFS) is valid...

This study highlights how particle filter optimization (PFO) algorithms can explore objective functions and their robustness near optimums. Improvements of the general algorithm are also introduced to increase search efficiency. Population-based optimization algorithms reach outstanding performance by propagating not only one but many candidate sol...

Understanding the level of local loyalty is crucial for urban planners, as individuals who exhibit higher levels of loyalty are more likely to adopt a “voice” strategy and act in the interest of their community, while being less likely to relocate. This study aims to develop a methodology for assessing and determining the factors influencing local...

The analysis of event sequences with temporal dependencies holds substantial importance across various domains, including healthcare. This study introduces a novel approach that combines sequential rule mining and survival analysis to uncover significant associations and temporal patterns within event sequences. By integrating these techniques, we...

italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Background: Human workers are indispensable in the human–cyber-physical system in the forthcoming Industry 5.0. As inappropriate work content induces stress and harmful effects on human performance, engineering applications search for a physiological i...

This research was motivated by the need for detailed information about the spatial and contextualized distribution of occupational exposures, which can be used to improve the layout of the workspace. To achieve this goal, the study emphasizes the need for position-related information and contextualized data. To address these concerns, the study pro...

The human worker is an in-disposable factor in manufacturing processes. Traditional observation methods to assess their performance is time-consuming and expert-dependent, while it is still impossible to diagnose the detailed movement trajectory with the naked eye. Industry 4.0 technologies can innovate that process with smart sensors paired with d...

Technology-driven Industry 4.0 (I4.0) paradigm combined with human-centrism, sustainability, and resilience orientation, forms the Industry 5.0 (I5.0) paradigm, providing support for the workforce and enabling the Operator 4.0 (O4.0) approach. The I5.0 focuses can face unforeseen challenges, as the applicability and readiness of I4.0 solutions are...

Comprehensive and objective assessment methods need to be developed to create inclusive, safe, resilient and sustainable cities. Monitoring the evolution of sustainability and well-being in the cities is important for researchers implementing the UN 2030 Agenda. This research explores and analyzes the climate change hazards, adaptation- and mitigat...

Vibrations in road vehicles cause several harmful effects, health problems can occur for the passengers, and mechanical damage can occur to the vehicle components. Given the health, safety, and financial issues that arise, keeping the road network in good condition and detecting road defects as early as possible requires an extensive monitoring sys...

While the primary focus of Industry 4.0 revolves around extensive digitalization, Industry 5.0, on the other hand, seeks to integrate innovative technologies with human actors, signifying an approach that is more value-driven than technology-centric. The key objectives of the Industry 5.0 paradigm, which were not central to Industry 4.0, underscore...

Az atom-, bio- és vegyi (ABV-) incidensek felderítése kiemelt fontosságú feladat, amely évtizedek óta intenzíven kutatott téma. A folyamatos technológiai, adatfeldolgozási és automatizálási vívmányok újabb és újabb fejlesztési potenciált nyitnak az ABV-védelem terén is, amely napjainkra komplex, interdiszciplináris tudományterületté vált. Ennek meg...

Non-negative matrix factorization (NMF) efficiently reduces high dimensionality for many-objective ranking problems. In multi-objective optimization, as long as only three or four conflicting viewpoints are present, an optimal solution can be determined by finding the Pareto front. When the number of the objectives increases, the multi-objective pr...

Process mining is a technique for exploring models based on event sequences, growing in popularity in the process industry. Process mining algorithms assume that the processed log files contain events generated by only one unknown process, which can lead to extremely complex and inaccurate models when this assumption is not met. To address this iss...

This study introduces particle filtering (PF) for the tracking and fault diagnostics of complex process systems. In process systems, model equations are often nonlinear and environmental noise is non-Gaussian. We propose a method for state estimation and fault detection in a wastewater treatment system. The contributions of the paper are the follow...

This paper describes a framework for detecting welding errors using 3D scanner data. The proposed approach employs density-based clustering to compare point clouds and identify deviations. The discovered clusters are then classified according to standard welding fault classes. Six welding deviations defined in the ISO 5817:2014 standard were evalua...

Due to the limited tool magazine capacities of CNC machines, time-consuming tool changeovers result in inefficient equipment utilization. This study provides a method to minimize the changeovers by optimizing the allocation of the tools to the machines. The proposed algorithm is efficient as it approaches the tool assignment task as a multi-objecti...

The concept of a data ecosystem and Industry 4.0 requires high-level vertical and horizontal interconnectivity across the entire value chain. Its successful realization demands standardized data models to ensure transparent, secure and widely integrable data sharing within and between enterprises. This paper provides a PRISMA method-based systemati...

The complex interactions from anthropogenic activities, climate change, sedimentation and the input of wastewater has significantly affected the aquatic environment and entire ecosystem. Over the years, the researchers have investigated water monitoring approaches in terms of traditional monitoring or even integrated systems to handle such an envir...

One of the main challenges of Industry 4.0 is how advanced sensors and sensing technologies can be applied through the Internet of Things layers of existing manufacturing. This is the so-called Brownfield Industry 4.0, where the different types and ages of machines and processes need to be digitalized. Smart retrofitting is the umbrella term for so...

One of the significant problems in our society is the handling and processing of the vast amount of waste produced by households and industrial processes. Nowadays, packaging material regulations are constantly changing, which can significantly impact the quality of municipal waste, requiring the continuous development and redesign of waste process...

Quality function deployment (QFD) has been a widely-acknowledged tool for translating customer requirements into quality product characteristics based on which product development strategies and focus areas are identified. However, the QFD method considers the correlation and effect between development parameters, but it is not directly implemented...

A method for flexible vibration sensor-based retrofitting of CNC machines is proposed. As different states leave different fingerprints in the power spectrum plane, the states of the machine can be distinguished based on the features extracted from the spectrum map. Due to some states, like tool replacement, are less frequent than others, like prod...

The ERASMUS program is the most extensive cooperation network of European higher education institutions. The network involves 90% of European universities and hundreds of thousands of students. The allocated money and number of travelers in the program are growing yearly. By considering the interconnection of institutions, the study asks how the pr...

The Paris Climate Agreement and the 2030 Agenda for Sustainable Development Goals declared by the United Nations set high expectations for the countries of the world to reduce their greenhouse gas (GHG) emissions and to be sustainable. In order to judge the effectiveness of strategies, the evolution of carbon dioxide, methane, and nitrous oxide emi...

The discovery of human mobility patterns of cities provides invaluable information for decision-makers who are responsible for redesign of community spaces, traffic, and public transportation systems and building more sustainable cities. The present article proposes a possibilistic fuzzy c-medoid clustering algorithm to study human mobility. The pr...

Alarm management is an important task to ensure the safety of industrial process technologies. A well-designed alarm system can reduce the workload of operators parallel with the support of the production, which is in line with the approach of Industry 5.0. Using Process Mining tools to explore the operator-related event scenarios requires a goal-o...