Gergő Monek

57204670474

Publications - 6

A Novel Method for Simulation Model Generation of Production Systems Using PLC Sensor and Actuator State Monitoring

Szabolcs Fischer Norbert Szántó Gergő Monek

Publication Name: Journal of Sensor and Actuator Networks

Publication Date: 2025-06-01

Volume: 14

Issue: 3

Page Range: Unknown

Description:

This article proposes and validates a novel methodology for automated simulation model generation of production systems based on monitoring sensors and actuator states controlled by Programmable Logic Controllers during regular operations. Although conventional Discrete Event Simulation is essential for material flow analysis and digital experimentation in Industry 4.0, it remains a resource-intensive and time-consuming endeavor—especially for small and medium-sized enterprises. The approach introduced in this research eliminates the need for prior system knowledge, physical inspection, or modification of existing control logic, thereby reducing human involvement and streamlining the model development process. The results confirm that essential structural and operational parameters—such as process routing, operation durations, and resource allocation logic—can be accurately inferred from runtime data. The proposed approach addresses the challenge of simulation model obsolescence caused by evolving automation and shifting production requirements. It offers a practical and scalable solution for maintaining up-to-date digital representations of manufacturing systems and provides a foundation for further extensions into Digital Shadow and Digital Twin applications.

Open Access: Yes

DOI: 10.3390/jsan14030055

Expert Twin: A Digital Twin with an Integrated Fuzzy-Based Decision-Making Module

Szabolcs Fischer Gergő Monek

Publication Name: Decision Making Applications in Management and Engineering

Publication Date: 2025-04-01

Volume: 8

Issue: 1

Page Range: 1-21

Description:

Digitalization and the application of modern Industry 4.0 solutions are becoming increasingly important to remain competitive as product ranges expand and global supply chains grow. This paper presents a new Digital Twin framework to achieve robustness in manufacturing process optimization and enhance the efficiency of decision support. Most digital twins in the literature synchronously represent the real system without any control elements despite the bidirectional data link. The proposed approach combines the advantages of traditional process simulations with a real-time communication and data acquisition method using programmable logic controllers designed to control automated systems. In addition, it complements this by utilizing human experience and expertise in modeling using Fuzzy Logic to create a control-enabled digital twin system. The resulting "Expert Twin" system reduces the reaction time of the production to unexpected events and increases the efficiency of decision support; it generates and selects alternatives, therefore creating smart manufacturing. The Expert Twin framework was integrated, tested, and validated on an automated production sample system in a laboratory environment. In the experimental scenarios carried out, the method production increased production line utility by up to 28% and the number of re-schedules can be halved.

Open Access: Yes

DOI: 10.31181/dmame8120251181

DES and IIoT fusion approach towards real-time synchronization of physical and digital components in manufacturing processes

Szabolcs Fischer Gergő Monek

Publication Name: Reports in Mechanical Engineering

Publication Date: 2023-12-01

Volume: 4

Issue: 1

Page Range: 161-174

Description:

Today's manufacturing systems offer more products to meet specific needs. Complex production systems in rapidly changing environments result from product variation, shorter product life cycles, and supply chain expansion. A cyber-physical production system (CPPS) can use manufacturing and logistics data to plan, monitor, and control production. Discrete event simulation (DES) and digital twin (DT) technology can model and evaluate manufacturing and logistics processes using high-level decision support and process monitoring. The cost of collecting input data from different enterprise data sources and mapping it into models and the lack of qualified experts prevent the widespread use of these methods in industry, especially in small and medium-sized enterprises and larger multinational companies. This research aims to create a modular digital twin framework for manufacturing process optimization and real-time monitoring in an industrial environment with few components. The system can identify and track the product through the manufacturing cycle while updating the DT in real-time and can be used independently to collect input parameters for discrete event-driven simulations and even for automatic simulation building in the future. The framework's operation will be shown through an example. With the proposed IIoT (industrial internet of things) system integration, it can detect faults and warn of deviations from normal operation, and DT can drastically reduce data collection and model building and support model reusability, increasing sustainability.

Open Access: Yes

DOI: 10.31181/rme040115092023m

IIoT-Supported Manufacturing-Material-Flow Tracking in a DES-Based Digital-Twin Environment

Szabolcs Fischer Gergő Monek

Publication Name: Infrastructures

Publication Date: 2023-04-01

Volume: 8

Issue: 4

Page Range: Unknown

Description:

Manufacturing processes can be cited as significant research areas when examining infrastructure systems and infrastructure, as they are inextricably linked to both. Examples include automobile manufacturing, the production of traffic signs, etc. Connecting and utilizing Industry 4.0 technologies and processing simulation solutions to address industry challenges, such as process optimization and fault detection, are gaining in popularity. Cyber-physical systems and digital twins connect the physical and cyber worlds to enable intelligent manufacturing capabilities, increased system flexibility, decreased manufacturing-cycle times, and improved quality. This paper presents a solution that improves the synchronization between the real (physical) and simulation (digital) layers, using discrete-event-driven simulations to create more efficient and accurate digital-twin environments. Using a combination of inexpensive commercial microcontrollers and an inertial-measurement-unit sensor to enhance a standard programmable logic controller process, a discrete-event-simulation-based digital layer is updated in real time to produce a live digital twin. The system can accurately identify and track products throughout the production cycle while simultaneously updating the digital twin in real time. Even independently, the algorithm running on the microcontroller can be used to gather the input parameters required for the simulation of production processes. The implemented environment can serve as a suitable testing ground for investigating the practical applicability of digital-twin solutions.

Open Access: Yes

DOI: 10.3390/infrastructures8040075

Transformation of traditional assembly lines into interoperable CPPS for MES: An OPC UA enabled scenario

G. Pedone János Jósvai Norbert Szántó Gergő Monek B. Háy

Publication Name: Procedia Manufacturing

Publication Date: 2020-01-01

Volume: 54

Issue: Unknown

Page Range: 118-123

Description:

The exploitation of I4.0 paradigm requires the availability of adequate information across all engineering and production value chains, which is the result of aggregation and fusion of data from various heterogeneous sources, often under real-time conditions. On the one hand, this comprises a challenge for the provision of an efficient, secure and dependable information management infrastructure. On the other hand, system architects must find solutions to assure interoperability on both syntactical and semantic level with reasonable engineering costs. In this paper authors present the research outcomes related to the conceptualization of a generalized information model and a service architecture, for the transformation and integration of typical third-party, stand-alone industrial equipment-FESTO prolog-factory in the specific-into an OPC UA enhanced, Industry 4.0 interoperable CPPS for new generations of Manufacturing Execution Systems. Aim of the discussed approach is to define basic but general guidelines of applicability for the definition, modelling and provision of standardized, Industry 4.0 compliant, CPPS-based industrial services, starting off from a typical legacy industrial environment.

Open Access: Yes

DOI: 10.1016/j.promfg.2021.07.019

The role of digital twin in a cyber-physical production environment with prescriptive learning

András Pfeiffer János Jósvai Norbert Szántó Gergő Monek

Publication Name: 17th International Conference on Modeling and Applied Simulation Mas 2018

Publication Date: 2018-01-01

Volume: Unknown

Issue: Unknown

Page Range: 180-184

Description:

In this paper, we introduce the establishing of digital twins for cyber-physical production systems. Using industrial PLC network and a discrete event simulation tool a live and interactive connection is made between the physical and cyber world. Based on this achievement a modified proactive framework with prescriptive simulation will be presented.

Open Access: Yes

DOI: DOI not available