EAI Endorsed Transactions on Digital Transformation of Industrial Processes
type: channel
description: Digital transformation has given rise to a series of new innovative production processes, integration of supply chains for decision making, performance evaluation, optimization and adaptation, as well as greater complexity in the development of innovative products, simulation of complex behaviors and development of sophisticated equipment, on using advanced techniques and tools, as machine learning, artificial intelligence, Big Data And Analytics, Autonomous Robots, Industrial Internet Of Things (IIoT), Design of Cyber-Physical Production Systems (CPPS), Simulation/ Digital Twin, e-Maintenance, Augmented Reality, Additive Manufacturing and Systems Interoperability. All the papers developed on the mentioned above topics are welcome to this journal. Indexing: Journal recently launched (pending)
publisher: European Alliance for Innovation (EAI)
language: en
publication name: EAI Endorsed Transactions on Digital Transformation of Industrial Processes
issn: 3106-0536
copyright: This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
items: Breaking Barriers: Digital Personal Assistants for the Inclusion of Workers with Disabilities in Production
items: Circular Economy and Its Place in a Modern Manufacturing Enterprise
items: A Low-Cost Framework for Textile Yarn Characterization Using Image Processing
items: Identification of circulation effects in a closed loop of a hydrostatic-mechanical transmissions with a planetary mechanism on the input and output links
items: Integrating Human Factors into Protocol Design: Decision Strategies in Digitalized Simulation Environments
items: A Structured Methodology for Synthesizing Parameters and Architecture of Robotic Technological Systems in the Digital Transformation of SME Engineering Production
items: Modular Internet of Things system for monitoring, control and alerting in refrigeration systems using ESP32 and Raspberry Pi 4
items: Reviewing Manufacturing Execution System in Industry 4.0: A Global Approach
items: Stress Factors in Technical Education: Digital Transformation as a Source of Emerging Challenges and Strategic Interventions
items: Research on the Monitoring of Selected Parameters of Technological Devices in the Conditions of a Digital Enterprise
items: A Practical Approach to Industrial Digitalization through Data Acquisition and Systems Integration for Predictive Maintenance
items: Digitization of civil architecture objects during wartime using photogrammetry: A case study of Sumy State University
items: Study of the process of purifying potassium humate suspension from suspended particles using industrial centrifuges
items: Integrated Manufacturing Management Platform
items: The Impact of generative artificial intelligence on students and teachers in the educational process
items: Modeling and Simulation of a Ground Mobile Rover for Inspection Tasks
items: Investigation of the impact of force majeure circumstances as a market instability factor on the flexibility and sustainability of engineering SMEs
items: Exoskeleton-type medical rehabilitation system with embedded sensors, designed using digital-twin solutions
items: Wearable Devices in Dementia Monitoring: A Systematic Review of Technologies, Design, and Future Directions
items: Modelling an Electro-hydraulic Proportional Valve in a Closed-Loop Control System using Matlab/Simulink
items: Development of a digital model for cooling efficiency of metal working fluids in machining
items: A Two-Phase Hybrid GWO:TP-AB Algorithm for Solving Optimization Problems
items: Soft Robotics in Industrial Automation: Adaptive Industrial Gripper Design and Evaluation
items: Cloud-Based Data-Driven Behavior Model Recovery for Distributed Automation Systems
items: Solving Facility Location and Supply Chain Management Problems Using Modified Population-Based TP-AB Algorithm

Breaking Barriers: Digital Personal Assistants for the Inclusion of Workers with Disabilities in Production
type: item
description: INTRODUCTION: This paper introduces Digital Personal Assistants (DPAs) as tools to support inclusive employment for workers with disabilities in industrial production. OBJECTIVES: The aim is to design a DPA that enables barrier-free access to work-related information. METHODS: DPAs are developed for multiple devices, focusing on accessibility, and task support—co-designed with workers with disabilities. RESULTS: A possible implementation of a DPAs is shown in this paper. CONCLUSION: User-centered DPAs can help reduce barriers and support inclusion in production.
subject: Research Articles
  topic: section
subject: Disabilities in Production
  topic: keywords
subject: Digital Personal Assistance
  topic: keywords
subject: Cognitive Production
  topic: keywords
creator: Markus Brillinger
creator: I. Unterkircher
creator: F. Lackner
creator: C. Zwickl
creator: P. Eisele
creator: D. Peraković
creator: M. Periša
creator: I. Cvitić
creator: P. Teskera
creator: S. Teixeira
creator: J. C. Teixeira
rights: Copyright (c) 2025 Markus Brillinger, I. Unterkircher, F. Lackner, C. Zwickl, P. Eisele, D. Peraković, M. Periša, I. Cvitić, P. Teskera, S. Teixeira, J. C. Teixeira https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-09-12
publication date: 2025-09-12
doi: 10.4108/dtip.9848

Circular Economy and Its Place in a Modern Manufacturing Enterprise
type: item
description: The circular economy is a key tool for addressing problems associated with excessive consumption of natural resources and environmental pollution. In the context of a manufacturing enterprise, implementing circularity principles represents not only ecological responsibility but also an opportunity to enhance the enterprise's efficiency and competitiveness. Research article aims to examine how a specific enterprise uses these principles in practice and what impact they have on its production processes and costs. It presents an opportunity to explore how an enterprise reduces waste, recycles materials, and optimises production, thereby contributing to environmental protection and enhancing its competitiveness. In addition, the circular economy enables enterprises to plan more effectively and manage their resources, thereby reducing the need for new raw materials and energy inputs, which has a direct impact on costs and profitability. The implementation of these principles can also positively impact the enterprise's image on the market, as an increasing number of consumers and partners prefer companies that prioritise sustainability and responsible environmental behaviour.
subject: Research Articles
  topic: section
subject: Circular Economy
  topic: keywords
subject: Manufacturing Enterprise
  topic: keywords
subject: Waste
  topic: keywords
subject: Efficiency
  topic: keywords
creator: Lucia Knapčíková
creator: Rebeka Tauberová
creator: Ivana Klačková
creator: Annamária Behúnová
rights: Copyright (c) 2025 Lucia Knapčíková, Rebeka Tauberová, Ivana Klačková, Annamária Behúnová https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-12
publication date: 2025-08-12
doi: 10.4108/dtip.9784

A Low-Cost Framework for Textile Yarn Characterization Using Image Processing
type: item
description: The textile industry increasingly demands innovative and cost-effective solutions for yarn quality assessment, as conventional equipment is costly and occupies substantial space. This work presents a compact, low-cost image processing framework to characterize key yarn parameters, providing a foundation for future automated quality control systems. The framework employs classical image processing techniques—smoothing, thresholding, segmentation, and morphological operations—implemented with open-source tools such as Visual Studio and OpenCV. An experimental setup using low-cost hardware enabled the acquisition of high-quality images under controlled conditions. The system extracted parameters including linear mass, average diameter, specific volume, defect quantification, hairiness coefficient, and twist direction and pitch. Tests on three yarn types (cotton and polyester) produced results comparable to the industrial reference Uster Tester 3, with error rates below 7%. The proposed solution offers an affordable alternative for small industries and research laboratories, with potential for future integration of advanced computer vision and artificial intelligence to enhance defect detection and classification.
subject: Research Articles
  topic: section
subject: Image Processing
  topic: keywords
subject: Yarn Characterization
  topic: keywords
subject: Quality Control
  topic: keywords
subject: Hairiness
  topic: keywords
subject: Digitalization
  topic: keywords
subject: Defects
  topic: keywords
subject: Low-Cost System
  topic: keywords
creator: Filipe Pereira
creator: Miguel Oliveira
creator: Filomena Soares
creator: Rosa Vasconcelos
creator: Vítor Carvalho
rights: Copyright (c) 2025 Filipe Pereira, Miguel Oliveira, Filomena Soares, Rosa Vasconcelos, Vítor Carvalho https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-12
publication date: 2025-08-12
doi: 10.4108/dtip.9846

Identification of circulation effects in a closed loop of a hydrostatic-mechanical transmissions with a planetary mechanism on the input and output links
type: item
description: INTRODUCTION: Modern trends in the development of mobile machinery, particularly heavy tracked vehicles, tractors and military vehicles, focus on improving the energy efficiency, controllability and reliability of transmission systems. In this context, hydrostatic-mechanical transmissions (HMCVTs) with a closed energy transmission loop demonstrate significant potential as an alternative to traditional mechanical and hydrodynamic systems by combining smooth speed control with increased efficiency. A key feature of closed HMCVTs is circulation power transmission, which arises from the interaction of the hydraulic and mechanical circuits. Using planetary mechanisms on both the input and output links of the transmission creates internal closed power flows, or circulations, which affect torsional rigidity, energy losses and dynamic stability. Currently, the scientific literature pays insufficient attention to identifying circulation effects in transmissions with such a layout. This complicates the design and optimisation of HMCVTs that take internal circulation loads into account, as this can lead to the overloading of individual transmission elements, increasing the temperature in the circuit or reducing efficiency. Therefore, this study is relevant because it provides an in-depth analysis of circulation effects in closed HMCVTs with planetary mechanisms at the input and output of the transmission system. The results of such an analysis could inform the development of methods for identifying and compensating for harmful circulation flows. This would contribute to extending the service life, improving the energy efficiency and enhancing the control accuracy of HMCVTs. OBJECTIVES: This work aims to develop and analyse the mathematical basis for describing circulation effects in the closed loop of the HMCVT, with the planetary mechanism located on the input and output links. This goal can be achieved by identifying patterns and forming a mathematical model of the transmiss…
subject: Research Articles
  topic: section
subject: vehicle
  topic: keywords
subject: transmission
  topic: keywords
subject: HMCVT
  topic: keywords
subject: speed
  topic: keywords
subject: power
  topic: keywords
subject: simulation
  topic: keywords
subject: circulation effects
  topic: keywords
subject: digitalization
  topic: keywords
creator: Ievgenii Veretennikov
rights: Copyright (c) 2025 Ievgenii Veretennikov https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-08
publication date: 2025-08-08
doi: 10.4108/dtip.9731

Integrating Human Factors into Protocol Design: Decision Strategies in Digitalized Simulation Environments
type: item
description: INTRODUCTION: In high-stakes industrial and operational contexts, such as aerospace, human factors heavily influence effectiveness under uncertain and dynamic conditions. Integrating simulation-based environments and digital tools in protocol development provides a valuable lens through which to assess cognitive and behavioural responses. As digitalization and Industry 4.0 accelerate the shift toward cyber-physical and human-in-the-loop systems, it becomes essential to understand how decision-making is affected in such digitalized settings. OBJECTIVES: This study aims to analyse the impact of uncertainty, time pressure, and cognitive complexity on human decision-making during protocol implementation in a simulated space mission. It also explores the implications of these insights for the design of digitalized, human-centred protocols pertinent to industrial transformation scenarios. METHODS: A mixed-methods approach was employed. Participants took part in a simulated space mission scenario using pre-defined protocols within a controlled, uncertainty-driven environment. Behavioural responses, timing, deviations, and verbal feedback were recorded and analysed. The quantitative data were supplemented with qualitative insights from participant interviews and session logs. RESULTS: Findings indicate operational uncertainty and time constraints significantly influenced participants’ decision pathways. Deviations from scripted protocols revealed how stress and perceived role clarity influence real-time choices. Furthermore, the analysis contextualizes these findings within Industry 4.0 frameworks, highlighting parallels with decision-making challenges in smart manufacturing, digital twin monitoring, and automated safety systems. CONCLUSION: The results underscore the necessity of embedding human-centred principles in protocol design, particularly when deploying digital technologies in complex, mission-critical environments. The study provides strategic recommendations for …
subject: Research Articles
  topic: section
subject: Analog Missions
  topic: keywords
subject: Communication Delay
  topic: keywords
subject: Decision-Making
  topic: keywords
subject: Digital Twins
  topic: keywords
subject: Human-Machine Interaction
  topic: keywords
subject: Industry 4.0.
  topic: keywords
subject: Interface Design
  topic: keywords
subject: Protocol Design
  topic: keywords
creator: Mariana Pereira
creator: Celina P. Leão
creator: Susana Costa
rights: Copyright (c) 2025 Mariana Pereira, Celina P. Leão, Susana Costa https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-26
publication date: 2025-08-26
doi: 10.4108/dtip.9821

A Structured Methodology for Synthesizing Parameters and Architecture of Robotic Technological Systems in the Digital Transformation of SME Engineering Production
type: item
description: INTRODUCTION: Robotic automation has become a key driver of digital transformation in the engineering sector, especially for small and medium-sized enterprises (SMEs), which face increasing demands for flexibility, efficiency, and cost optimization. However, most classical automation frameworks do not address the structural and economic limitations specific to SMEs. Despite recent advances in modular automation, a gap remains in methodologies tailored to low-volume, high-mix environments typical of SMEs. OBJECTIVES: This paper aims to develop a structured methodology for synthesizing the parameters and architecture of robotic technological systems adapted to the production realities of SME engineering environments. The goal is to balance automation effectiveness with practical investment constraints. METHODS: The proposed approach integrates a multi-level automation model with production system analysis, considering object-specific constraints, part characteristics, and process parameters. The methodology was validated through an expert- and data-driven case study of a Ukrainian SME engaged in serial plastic part machining. Functional-cost analysis and feasibility modeling were used to evaluate automation options. In addition, investment-efficiency mapping was introduced to support strategic planning of implementation phases. RESULTS: The implementation of the proposed system, based on a six-axis robotic manipulator with digital control and vacuum clamping devices, led to a 50% reduction in auxiliary processing time, improved consistency, and reduced labor intensity. The workplace-level automation enabled flexible part handling without the need for major structural changes or high capital investment. The system demonstrated high adaptability to part variations and required minimal operator intervention. CONCLUSION: The developed methodology provides a scalable and economically viable path to robotic automation for SMEs. It supports gradual implementation and can be …
subject: Technical Article
  topic: section
subject: Robotic Automation
  topic: keywords
subject: SME Engineering
  topic: keywords
subject: Process Synthesis
  topic: keywords
subject: Digital Transformation
  topic: keywords
subject: Technological Systems
  topic: keywords
subject: Workplace Design
  topic: keywords
subject: Industry 4.0.
  topic: keywords
creator: Ihor Yakovenko
creator: Yevheniia Basova
creator: Alexander Permyakov
creator: Andrii Pokhil
creator: Victor Sotnychenko
creator: Luís Freitas
rights: Copyright (c) 2025 Ihor Yakovenko, Yevheniia Basova, Alexander Permyakov, Andrii Pokhil, Victor Sotnychenko, Luís Freitas https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-07
publication date: 2025-08-07
doi: 10.4108/dtip.9681

Modular Internet of Things system for monitoring, control and alerting in refrigeration systems using ESP32 and Raspberry Pi 4
type: item
description: With the rapid development of Internet of Things (IoT) systems and the increasing need for smart monitoring and control, this paper presents a fully functional platform for collecting, analyzing and controlling data from an experimental setup based on a refrigeration system. The main goal is the development of a modular architecture that gathers data from multiple sensors in real time, processes it, and displays it through a web interface. The system detects when key parameters deviate from nominal parameters and automatically sends email alerts to prevent failures and reduce system downtime. The system uses embedded programming on the ESP32-S3 microcontroller to collect data from temperature and pressure sensors. Simultaneously, a Single Board Computer (SBC) Raspberry Pi 4 runs Python scripts that process the data and collect electrical parameters via a dedicated module. Communication between the microcontroller and the SBC is conducted through a Universal Asynchronous Receiver-Transmitter (UART) serial interface. The ESP32-S3 microcontroller handles data acquisition and sends it to the Raspberry Pi 4, which processes and stores the information in a local Stuctrured Query Language Lite (SQLite) database. The platform supports dynamic thermodynamics calculations using the CoolProp library and visualizes results through the web interface. The experimental setup includes a refrigeration system with R404A refrigerant, featuring a square coil evaporator and an air-cooled condenser. The implemented platform gathers real-time data from sensors and the electrical energy measurement module, processes it, and displays it on the web interface. The system enables dynamic monitoring and component control by running a logic-based algorithm that continuously checks values and automatically triggers corrective actions, including email notifications, based on system status. The ESP32-S3 microcontroller includes Pulse Width Modulation (PWM) pins reserved for future connection of fre…
subject: Technical Article
  topic: section
subject: Iot system
  topic: keywords
subject: Refrigeration system
  topic: keywords
subject: Real-time data acquisition
  topic: keywords
subject: Alerting and notification
  topic: keywords
subject: industrial automation
  topic: keywords
creator: Mihai Florin Bizdadea
creator: George Daniel Ghita
creator: Valentin Gheorghe Apostol
creator: Horatiu Lucian Pop
creator: Bogdan Gramescu
rights: Copyright (c) 2025 Mihai Florin Bizdadea, George Daniel Ghita, Valentin Gheorghe Apostol, Horatiu Lucian Pop, Bogdan Gramescu https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-09-02
publication date: 2025-09-02
doi: 10.4108/dtip.9792

Reviewing Manufacturing Execution System in Industry 4.0: A Global Approach
type: item
description: INTRODUCTION: Manufacturing Execution Systems (MES) have evolved from basic production tracking tools into intelligent, AI-driven platforms integrated with IoT, cloud computing, and cyber-physical systems. In the context of Industry 4.0, MES play a key role in enabling real-time decision-making and operational efficiency. However, research in this field remains fragmented, with ongoing challenges related to interoperability, cybersecurity, and system integration. OBJECTIVES: This study aims to map the MES research landscape within Industry 4.0 through a systematic literature review and bibliometric analysis. It identifies core research themes, technological trends, and persistent challenges, offering insights to guide future developments in MES. METHODS: A Systematic Literature Review (SLR) was conducted using the Scopus database, applying specific search terms and strict inclusion/exclusion criteria. A total of 47 peer-reviewed articles (2010–2024) were analysed using VOSviewer to perform co-authorship, bibliographic coupling, and keyword co-occurrence mapping. RESULTS: The analysis revealed three main research clusters: MES core technologies, MES integration with Industry 4.0, and comparisons with ERP and SCADA systems. Key trends include the integration of AI, digital twins, and blockchain. Barriers such as interoperability, cybersecurity risks, and adoption costs—especially for SMEs—remain prevalent. CONCLUSION: MES research is advancing toward intelligent, scalable, and interconnected systems. Future work should prioritise standardisation, secure data exchange, and cost-effective models to support broader Industry 4.0 adoption. Cross-disciplinary collaboration will be essential to achieve sustainable and resilient MES implementations.
subject: Review Article
  topic: section
subject: Manufacturing Execution Systems (MES)
  topic: keywords
subject: Industry 4.0
  topic: keywords
subject: IoT
  topic: keywords
subject: AI
  topic: keywords
subject: Cyber-Physical Systems
  topic: keywords
subject: Smart Manufacturing
  topic: keywords
creator: Teresa Dieguez
creator: José Machado
rights: Copyright (c) 2025 Teresa Dieguez, José Machado https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-12
publication date: 2025-08-12
doi: 10.4108/dtip.9768

Stress Factors in Technical Education: Digital Transformation as a Source of Emerging Challenges and Strategic Interventions
type: item
description: INTRODUCTION: Technical educators face both long-standing and emerging stressors amplified by the digital transformation of industrial processes. The introduction of Industry 4.0/5.0 technologies (AI tools, VR/AR labs, digital platforms) increases cognitive and administrative burdens. OBJECTIVES: This study aims to identify shared and technology-specific stressors in technical education and propose evidence-based strategies to mitigate them. METHODS: We performed a systematic review of peer-reviewed articles and conducted a focus groups with 60 technical educators. Data were analyzed using thematic coding. RESULTS: The most frequently reported stressors were administrative overload, curriculum volatility, safety responsibilities, and insufficient digital training. Digital tools like VR and AI systems present both stress-inducing and stress-reducing potential. CONCLUSION: Supporting educators through targeted digital interventions and training programs is vital to sustaining quality technical education during ongoing digitalization.
subject: Research Articles
  topic: section
subject: technological education
  topic: keywords
subject: teacher well-being
  topic: keywords
subject: digitalization
  topic: keywords
subject: resilience
  topic: keywords
subject: intervention programs
  topic: keywords
creator: Andrea Hlubuckova
creator: Monika Dobiášová
creator: Petr Valášek
rights: Copyright (c) 2025 Andrea Hlubuckova, Monika Dobiášová, Petr Valášek https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-05
publication date: 2025-08-05
doi: 10.4108/dtip.9738

Research on the Monitoring of Selected Parameters of Technological Devices in the Conditions of a Digital Enterprise
type: item
description: Digitization is a key concept of the Fourth Generation Industrial Revolution. In industrial enterprises, digitization allows for the study of various influences on production processes without the need to intervene in real production. Thanks to technologies such as augmented reality, virtual reality, 3D printing, digital twins, and artificial intelligence, it is possible to conduct research activities monitoring selected parameters without interfering with the production process. Financial resources invested in transforming a traditional company into a digital enterprise ultimately save production costs. Simulation programs enable quick and easy planning of production changes, resulting in more efficient processes and savings in raw materials. The concept of digitization has gained greater importance, especially in connection with events like COVID-19, which affected daily life worldwide. Many companies realized the significant advantage of digitizing production. The pressure of events and economic impacts accelerated the implementation of digitization and intelligent automation. The use of artificial intelligence tools in production enables remote control of manufacturing.
subject: Review Article
  topic: section
subject: Additive manufacturing
  topic: keywords
subject: Granulate
  topic: keywords
subject: Polyvinyl Butyral
  topic: keywords
subject: Recycling
  topic: keywords
subject: Circular Economy
  topic: keywords
creator: Rebeka Tauberová
creator: Lucia Knapčíková
rights: Copyright (c) 2025 Rebeka Tauberová, Lucia Knapčíková https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-07-29
publication date: 2025-07-29
doi: 10.4108/dtip.9737

A Practical Approach to Industrial Digitalization through Data Acquisition and Systems Integration for Predictive Maintenance
type: item
description: The digital transformation of industrial environments requires the ability to collect, process, and integrate data from production systems in real time. However, many manufacturing facilities operate with legacy equipment that is perfectly functional and operational but lacks native connectivity or standardized interfaces for data acquisition. This paper presents an approach to enable industrial digitalization through the implementation of a network architecture at the Operational Technology (OT) level that facilitates the collection of structured data from legacy and modern machines. The proposed solution ensures integration between production systems and supervisory platforms, supporting real-time monitoring through SCADA systems and providing relevant information for predictive maintenance strategies. The proposal is based on the implementation of a standardized and secure communication infrastructure between the shop floor and higher-level Information Technology (IT) systems, aligning with the principles of Industry 4.0. The solution has been implemented in a real industrial scenario, is fully operational and the results demonstrate significant benefits of integrating heterogeneous industrial assets into a unified data ecosystem, improving process insight, operational efficiency and supporting maintenance decision-making.
subject: Research Articles
  topic: section
subject: Industry 4.0.
  topic: keywords
subject: OPC UA
  topic: keywords
subject: Legacy Equipment Integration
  topic: keywords
subject: Industrial Digitalization
  topic: keywords
creator: Nikita Bocharov
creator: Pedro Torres
creator: João Matos
rights: Copyright (c) 2025 Nikita Bocharov, Pedro Torres, João Matos https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-07
publication date: 2025-08-07
doi: 10.4108/dtip.9700

Digitization of civil architecture objects during wartime using photogrammetry: A case study of Sumy State University
type: item
description: INTRODUCTION: In the context of the ongoing war in Ukraine, the preservation of architectural heritage has become critically important. In this regard, the documentation and preservation of architectural heritage have become crucial. OBJECTIVES: The study employs drone-based aerial imaging and terrestrial photography to generate accurate 3D models of a partially destroyed historic building. METHODS: A photogrammetric technique was employed to create an accurate 3D model of Campus K-2 of Sumy State University, destroyed by russian missiles on April 13, 2025, in Sumy, Ukraine. A comprehensive approach for involving photogrammetric reconstruction, texture processing, and building information modeling (BIM) integration was described. The research also outlines the challenges of restoring during wartime, discusses data acquisition and processing workflow, and evaluates the effectiveness of low-cost equipment and open-source software in achieving high-quality results. RESULTS: The resulting digital model captures structural deformations and facade details. The implemented approach enables documentation and monitoring of damaged structures. It also provides valuable fundamentals for the studied object’s future restoration, structural analysis, and memorialization. CONCLUSION: The research shows photogrammetry as a fast, reliable tool for documenting cultural heritage in wartime and emphasizes its social value for education and preservation. It also suggests adding protective architectural features to reconstructed heritage buildings to improve resilience in conflict zones.
subject: Research Articles
  topic: section
subject: digital reconstruction
  topic: keywords
subject: cultural heritage preservation
  topic: keywords
subject: resilient infrastructure design
  topic: keywords
subject: sustainable reconstruction of war-damaged sites
  topic: keywords
subject: digital documentation for historical memory
  topic: keywords
subject: post-conflict recovery planning
  topic: keywords
creator: Ihor Tytarenko
creator: Ivan Pavlenko
rights: Copyright (c) 2025 Ihor Tytarenko, Ivan Pavlenko https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-08-04
publication date: 2025-08-04
doi: 10.4108/dtip.9697

Study of the process of purifying potassium humate suspension from suspended particles using industrial centrifuges
type: item
description: Potassium humate suspensions obtained by alkaline extraction of peat using cavitation dispersion contain suspended solid particles that require effective separation to improve product quality. The separation of suspended solid particles larger than 20 μm is particularly important to ensure product purity. The main objectives of the study were to determine the possibility of removing suspended solid particles from potassium humate suspension and to evaluate the efficiency of the separation process on a laboratory and industrial scale. Laboratory tests included sedimentation under the action of Earth's gravity for two months, centrifugation in a laboratory cup centrifuge at different speeds, and analysis of solid content, particle size distribution, pH, and conditional viscosity. Industrial tests were carried out on an Ecomash SHS 311 centrifuge in both batch and continuous modes at different rotor speeds and flow rates. The purified product (fuga) was analysed by sieving through 20 and 40 μm sieves and measuring viscosity. Laboratory sedimentation showed the formation of a compact sediment layer, confirming the presence of suspended solids. Industrial tests demonstrated effective removal of suspended solids at a separation factor (Fr) ≥ 1550, with no visually detectable particles larger than 20 μm in the filtrate. Viscosity measurements correlated well with suspended solids content and were proposed as a rapid control method. Centrifugation effectively removes suspended solids from potassium humate suspensions in both laboratory and industrial conditions. The separation factor significantly affects the efficiency of purification. For operational quality control, sieving in combination with viscosity measurement is recommended. Further laboratory studies are needed to establish the dependence of viscosity on solids content and temperature to improve process control.
subject: Research Articles
  topic: section
subject: potassium humate
  topic: keywords
subject: suspension separation
  topic: keywords
subject: centrifugal clarification
  topic: keywords
subject: industrial centrifugation
  topic: keywords
subject: suspended solids removal
  topic: keywords
subject: sedimentation efficiency
  topic: keywords
creator: A.O. Shkop
creator: N.G. Ponomarova
creator: Alona Bosiuk
creator: O.V. Shestopalov
rights: Copyright (c) 2025 A.O. Shkop, N.G. Ponomarova, Alona Bosiuk, O.V. Shestopalov https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-07-25
publication date: 2025-07-25
doi: 10.4108/dtip.9678

Integrated Manufacturing Management Platform
type: item
description: INTRODUCTION: This paper presents a brief overview of the Integrated Manufacturing Management Platform (IMMP), designed to enable dynamic, real-time integration of supply chain and manufacturing management across multiple factories, workstations, and external business partners. The platform fosters interoperability and shared decision-making across strategic, tactical, and operational levels, leveraging integrated middleware comprising both hardware and software components, as well as associated technologies and tools. OBJECTIVES: The primary objective of this work is to describe the development and capabilities of the IMMP, highlighting how it supports collaborative and integrated manufacturing planning, scheduling, monitoring, and control. The platform aims to enhance joint manufacturing management by enabling information sharing and process coordination among a distributed set of stakeholders. METHODS: The IMMP was developed using Microsoft Visual Studio to facilitate dynamic updates to its information, tools, and functionalities. The underlying databases were implemented in SQL Server Management Studio and iteratively refined to accommodate evolving platform requirements. The system architecture is based on modular components deployed across participating factories and work centers, supported by smart objects and appropriate interfaces for seamless integration and communication. RESULTS: The resulting platform offers a fully integrated environment comprising multiple modules and functions provided by each collaborating entity. These modules support various tasks such as integrated manufacturing planning and scheduling, leveraging smart technologies and networked organizational structures. Data collected from the participating network of factories and facilities enabled the validation of the platform's core functionalities and guided successive improvements. CONCLUSION: The IMMP demonstrates strong potential to support real-time, collaborative manufacturing manag…
subject: Research Articles
  topic: section
subject: integrated management
  topic: keywords
subject: monitoring
  topic: keywords
subject: control
  topic: keywords
subject: dynamic and real time based platform
  topic: keywords
creator: Gaspar Vieira
creator: Miguel Ângelo Pereira
creator: Leonilde Varela
creator: Goran Putnik
creator: Manuela Cruz-Cunha
rights: Copyright (c) 2025 Gaspar Vieira, Miguel Ângelo Pereira, Leonilde Varela, Goran Putnik, Manuela Cruz-Cunha https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-05-12
publication date: 2025-05-12
doi: 10.4108/dtip.9080

The Impact of generative artificial intelligence on students and teachers in the educational process
type: item
description: In the last 10–15 years, significant investments have been made in the integration of modern technologies into the educational process. These investments have been driven by the rapid development of the internet and information technologies, as well as global challenges such as the COVID-19 pandemic, which necessitated a shift toward online learning. The primary objective of these efforts is to improve the efficiencntialy of the educational process by enabling students to develop essential skills, such as problem-solving, teamwork, and analytical thinking, all supported by technology. When discussing modern technologies, special attention must be given to Artificial Intelligence (AI) and its subfield, Generative Artificial Intelligence (GAI), which are increasingly integrated into the educational environment. In this context, Generative Artificial Intelligence has the potential to significantly reshape teaching and learning by offering personalized learning experiences, dynamic instructional content, and tools that foster creative thinking. For educators, GAI offers new possibilities for interactive teaching, tracking student achievements, and analyzing academic performance. These tools, designed for both students and teachers, are easily accessible, intuitive to use, and constantly evolving. This paper presents a theoretical review of the implementation of GAI in education and examines how its application influences the work of students and teachers. Furthermore, the paper will explain the potential of GAI to enhance digital literacy, analytical thinking, and adaptive learning strategies necessary for competitiveness in the 21st-century labor market.
subject: Review Article
  topic: section
subject: Generative Artificial Intelligence
  topic: keywords
subject: Impact of GAI on learning process
  topic: keywords
subject: Student Competencies
  topic: keywords
creator: Vladan Čolić
creator: Enes Sukić
rights: Copyright (c) 2025 Vladan Čolić, Enes Sukić https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-05-20
publication date: 2025-05-20
doi: 10.4108/dtip.9052

Modeling and Simulation of a Ground Mobile Rover for Inspection Tasks
type: item
description: This paper proposes design improvements and simulations for an inspection rover developed for inspection tasks. The proposed system is suitable for both indoor and outdoor surveys and, due to its compact size and ability to overcome obstacles, is particularly well-suited for use in confined spaces where human intervention is difficult or nearly impossible. Autonomous or teleoperated systems can replace experienced personnel, navigating complex, unstructured environments that are often hard to access. These systems carry appropriate sensors and manage data, which can then be transmitted for further analysis. The survey uses advanced mechatronic systems consisting of robots, instrumentation, and a networking system to operate both internal and external sensors. The former is used for navigation, while the latter provides data from the area of interest. This paper focuses on the robotic structure designed for inspection tasks. Building on an existing hybrid rover, the paper examines the mechanical design and simulation of the system to optimize its functionality in terms of motion smoothness and compactness, all while adhering to a low-cost design philosophy.
subject: Research Articles
  topic: section
subject: Mobile Robots
  topic: keywords
subject: Robotic Inspection
  topic: keywords
subject: Mechatronics
  topic: keywords
subject: Mechanical Design
  topic: keywords
subject: Simulation
  topic: keywords
subject: Structural Health Monitoring
  topic: keywords
creator: Pierluigi Rea
creator: Erika Ottaviano
creator: Maurizio Ruggiu
rights: Copyright (c) 2025 Pierluigi Rea, Erika Ottaviano, Maurizio Ruggiu https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-04-30
publication date: 2025-04-30
doi: 10.4108/dtip.9048

Investigation of the impact of force majeure circumstances as a market instability factor on the flexibility and sustainability of engineering SMEs
type: item
description: INTRODUCTION: Modern manufacturing operates under complex natural, economic, and political conditions. Small and medium-sized enterprises (SMEs), as the most flexible representatives of the engineering industry, small and medium-sized enterprises (SMEs) must account for potential stress factors in their current and future development. Research indicates that enterprises must respond rapidly to such stressors to maintain competitiveness and stability in domestic and international markets. Management decisions to ensure SME resilience should adopt a comprehensive approach, considering economic indicators such as productivity, product quality, logistics, and cost, as well as social aspects like employee safety, workplace conditions, and resource-efficient technologies. This study develops and analyzes a mathematical model describing the impact of various stress factors on the stability of SMEs in the engineering sector under force majeure conditions. The research identifies key stressors, formulates a mathematical model to assess their influence on enterprise resilience, and evaluates the model’s effectiveness over time. The integral flexibility functional serves as the foundation for this model, incorporating market fluctuations, production costs, and force majeure impacts, including quarantine restrictions and enterprise relocation. To optimize this functional, the study employs the automated planning method PPLAN, which is rooted in artificial intelligence. This approach enables the generation of adaptive strategies to mitigate stress factors affecting SME stability. The findings reveal that relocation due to force majeure is the most detrimental factor, leaving minimal time for recovery actions, while demand fluctuations exert a more cyclical influence. The proposed methodology provides a structured framework for enhancing SME resilience in dynamic and unpredictable environments OBJECTIVES: The objective of this paper is to develop a mathematical model that quantif…
subject: Research Articles
  topic: section
subject: enterprise stability
  topic: keywords
subject: stress factors
  topic: keywords
subject: integral flexibility functional
  topic: keywords
subject: automatic planning
  topic: keywords
subject: PPLAN (planning based on preferences method)
  topic: keywords
subject: digital transformation
  topic: keywords
creator: Yevheniia Basova
creator: Sergey Dobrotvorskiy
creator: Ihor Yakovenko
rights: Copyright (c) 2025 Yevheniia Basova, Sergey Dobrotvorskiy, Ihor Yakovenko https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-04-22
publication date: 2025-04-22
doi: 10.4108/dtip.8951

Exoskeleton-type medical rehabilitation system with embedded sensors, designed using digital-twin solutions
type: item
description: INTRODUCTION: Exoskeleton-type medical rehabilitation systems are the main solution for recovery of the mobility of patients affected by strokes, spinal cord injuries, or muscular atrophy. These systems feature detection and actuation components, such as sensors and actuators, whose typology and integration are essential for the device's ability to withstand wear under intensive use conditions. OBJECTIVES: To increase the lifespan of exoskeletons, the main objective of the project presented in this article is to integrate sensors into the exoskeleton’s structure, for them to be better protected from external factors, such as shocks or moisture. METHODS: A virtual model of an exoskeleton component for the lower limb that ensures the plantar flexion (movement of the sole), made of polyurethane, was designed using a digital-twin modelling solution, namely the SolidWorks Simulation software. Our choice was motivated by the fact that the use of digital twin solutions allows functional testing, by simulating the impact factors existing in real systems, of the exoskeleton with embedded sensors, by coating with polyethylene and ethylene vinyl acetate (EVA) layers. Thus, it will be possible to observe the inconsistencies and defects that can appear on the surface of the materials used and to determine the best choice of material that can protect against wear. RESULTS: The values ​​of all parameters analyzed following the simulations demonstrate that polyethylene and EVA are materials that can be used to embedd sensors into the structure of exoskeletons. Layers with thicknesses of 0.5 mm, 1 mm, and 1.5 mm are resistant and display stable structures during the patient's walking, thus protecting the sensors integrated into a lower limb exoskeleton from wear factors. CONCLUSION: Following the comparative analysis of the results obtained from testing by digital simulations, the main conclusion is that the 1.5 mm thick ethylene vinyl acetate layer is the one that presents superior…
subject: Research Articles
  topic: section
subject: exoskeleton
  topic: keywords
subject: digital twin
  topic: keywords
subject: sensors
  topic: keywords
creator: Liliana-Laura Badita-Voicu
creator: Adrian Catalin Voicu
rights: Copyright (c) 2025 Liliana-Laura Badita-Voicu, Adrian Catalin Voicu https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-04-14
publication date: 2025-04-14
doi: 10.4108/dtip.8817

Wearable Devices in Dementia Monitoring: A Systematic Review of Technologies, Design, and Future Directions
type: item
description: INTRODUCTION: Dementia affects over 55 million people worldwide, impacting patient autonomy and increasing caregiver burden. Wearable technology offers new possibilities for monitoring and intervention. However, existing solutions often lack usability, adaptability, and caregiver integration. This study focuses on ear-based wearable devices, such as hearing aids and smart earphones, assessing their role in dementia care. OBJECTIVES: This research aims to review wearable technologies for dementia monitoring, identify key user requirements, and define guidelines for future device development. METHODS: A systematic literature review was conducted using Scopus, PubMed, IEEE Xplore, and ScienceDirect, focusing on studies from 2020-2025. Relevant articles were analysed to identify technological advancements, design considerations, and gaps in existing research. RESULTS: Findings show that ear-based wearables effectively track physiological and behavioural data. Non-invasiveness, usability, and real-time data transmission are key factors. Despite advancements, gaps remain in device adaptability, user experience, and security. A set of physical, emotional, and cognitive requirements was established to guide future development. CONCLUSION: Wearable technology can transform dementia care, but improvements in ergonomics, AI-driven analytics, and caregiver integration are needed. Future research should focus on secure data transmission and clinical validation to ensure real-world effectiveness.
subject: Review Article
  topic: section
subject: Dementia
  topic: keywords
subject: Wearables
  topic: keywords
subject: Requirements
  topic: keywords
subject: Design
  topic: keywords
subject: Medical Devices
  topic: keywords
subject: Healthcare
  topic: keywords
subject: Monitoring
  topic: keywords
creator: Ana Freitas
creator: José Soares
creator: Marcelo Arantes
creator: Inês Rocha
creator: Mariana Carvalho
creator: Marta Pinto
creator: Demétrio Matos
creator: Pedro Morais
creator: Vìtor Carvalho
rights: Copyright (c) 2025 Ana Freitas, José Soares, Marcelo Arantes, Inês Rocha, Mariana Carvalho, Marta Pinto, Demétrio Matos, Pedro Morais, Vìtor Carvalho https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-04-22
publication date: 2025-04-22
doi: 10.4108/dtip.8856

Modelling an Electro-hydraulic Proportional Valve in a Closed-Loop Control System using Matlab/Simulink
type: item
description: In this paper the main components of a hydraulic positioning unit are modelled and simulated using the software Matlab/Simulink. That includes the actuator, the pressure relief valve, connecting pipes and of course the proportional directional control valve. With this model the positioning unit was tested under different conditions to make predictions on how the system is going to react. The simulation of the proportional directional control valve was divided into a static and dynamic part. Based on flow, pressure and leakage curves given by the manufacturer, pseudo-section functions have been created. These functions characterize the relationship between normalized spool position and flow rate. For simulating dynamic behaviour, a non-linear Simulink model was created. The model was fitted to non-linear frequency response analysis (NFR) data points by using a Nelder-Mead simplex optimization algorithm. Several experiments were carried out to test the methodologies as well as the models with the manufacturer's data and experimentally verifying the adjustability of the results and the validation of the approach. The valve model shows high positioning accuracy and robust behaviour in both simulation and experimentation. The amplitude response curves for 10% and 25% showed some oscillation, but with a stable behaviour around the measurement. On the other hand, the amplitude curve for 100% of the coil path showed a very acceptable approximation and even coincided with the manufacturer's curve.
subject: Research Articles
  topic: section
subject: Control
  topic: keywords
subject: Electro-hydraulic actuators
  topic: keywords
subject: Mathematical model
  topic: keywords
subject: Non-linear
  topic: keywords
subject: Position control
  topic: keywords
subject: Proportional valves
  topic: keywords
subject: Simulation
  topic: keywords
creator: António Ferreira da Silva
creator: Adriano A. Santos
creator: Filipe Pereira
creator: Carlos Felgueiras
creator: António M. Lopes
creator: Fernando G. de Almeida
creator: Paulo J. Silva
creator: António Ramos Silva
rights: Copyright (c) 2025 António Ferreira da Silva, Adriano A. Santos, Filipe Pereira, Carlos Felgueiras, António M. Lopes, Fernando G. de Almeida, Paulo J. Silva, António Ramos Silva https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-04-13
publication date: 2025-04-13
doi: 10.4108/dtip.8837

Development of a digital model for cooling efficiency of metal working fluids in machining
type: item
description: In this manuscript, cutting temperature generated in machining process, it’s sources and dissipation directions are studied. Energy consumption in metal cutting process and metal working fluids have taken as an object of the study. Moreover, the effect of metal working fluids in heat dissipation process and the importance of their cooling capacity is theoretically researched. As a result of the study, dependence model of temperature gradient between cutting face and fluid on fluid’s density and viscosity is mathematically developed. The developed digital model gives an easy way to predict metal working fluid’s cooling capacity before it’s use. It can be concluded that the reduction cutting fluids’ viscosity causes an increase in the cooling capacity of the fluids while high dense fluids show a better cooling capacity.
subject: Research Articles
  topic: section
subject: cutting temperature
  topic: keywords
subject: digital model
  topic: keywords
subject: heart dissipation
  topic: keywords
subject: heat transfer
  topic: keywords
subject: machining
  topic: keywords
subject: metal working fluid
  topic: keywords
subject: process digitalization
  topic: keywords
creator: Umidjon Mardonov
creator: O. A. Khasanov
creator: D. D. Norkhurozov
creator: A. A. Khushmuhammadov
rights: Copyright (c) 2025 Umidjon Mardonov, O. A. Khasanov, D. D. Norkhurozov, A. A. Khushmuhammadov https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-04-17
publication date: 2025-04-17
doi: 10.4108/dtip.8449

A Two-Phase Hybrid GWO:TP-AB Algorithm for Solving Optimization Problems
type: item
description: INTRODUCTION: Population-based algorithms are popular stochastic algorithms used for solving optimization problems. Grey Wolf Optimizer (GWO) proposed in 2014 is one of the most studied algorithms in the past decade. Population-based two-phase trigonometric AB (TP-AB) is a recently proposed algorithm for handling optimization problems. OBJECTIVES: The objective of this work is to propose one new hybrid algorithm combining the strengths of two better performing algorithms in two different phases. The performance is analysed using popular benchmarks and the results are compared with a few popular algorithms available in the literature. METHODS: One new two-phase hybrid algorithm is designed by taking GWO in its first phase and the second phase of the TP-AB algorithm in the second phase. In the second phase, the Levy Strategy is introduced which was not in the original TP-AB algorithm. RESULTS: The performance of the new hybrid GWO:TP-AB algorithm is analysed using 23 classic mathematical functions, 10 numbers of the CEC2019 dataset and 18 real-world engineering problems In addition, to demonstrate its capability to handle higher dimension problems, 13 scalable problems are solved. These include unimodal and multimodal instances with dimensions 30, 100, 500 and 1000. CONCLUSION: The results demonstrate the better performance of the GWO:TP-AB algorithm when compared to several optimization algorithms of recent times.
subject: Research Articles
  topic: section
subject: Metaheuristic
  topic: keywords
subject: Hybrid Algorithm
  topic: keywords
subject: Grey Wolf Optimizer
  topic: keywords
subject: Two-Phase AB Algorithm
  topic: keywords
subject: TP-AB Algorithm
  topic: keywords
subject: Real-World Applications
  topic: keywords
subject: Industrial Optimization
  topic: keywords
creator: Baskar A
creator: Anthony Xavior Michael
rights: Copyright (c) 2025 Baskar A, Anthony Xavior Michael https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-05-20
publication date: 2025-05-20
doi: 10.4108/dtip.8741

Soft Robotics in Industrial Automation: Adaptive Industrial Gripper Design and Evaluation
type: item
description: The rapid evolution of industrial automation demands more versatile gripping solutions beyond conventional vacuum, magnetic, and fingered grippers. This study introduces the development and evaluation of an adaptive Universal Jamming Gripper (UJG) optimized for industrial applications. Utilizing a flexible membrane filled with granular materials, the UJG transitions between soft and rigid states under vacuum pressure, enabling secure and adaptive grasping of objects with diverse shapes and materials. Three types of membrane fillings—ground coffee, polystyrene microspheres (EPS), and thermoplastic elastomer granules (TPE)—were assessed for grip stability and force efficiency. Experimental results demonstrate that EPS microspheres provide superior adaptability and stability, offering the highest gripping force across various object geometries. Performance tests on a universal testing machine further validate the gripper’s capability to handle differently shaped objects with minimal adjustments. The findings underscore the potential of adaptive gripping technologies in enhancing automation flexibility, reducing operational downtime, and increasing overall industrial efficiency. Future research will focus on long-term durability, integration with robotic automation, and performance assessment in real-world manufacturing environments.
subject: Research Articles
  topic: section
subject: universal jamming gripper
  topic: keywords
subject: industrial automation
  topic: keywords
subject: soft robotics
  topic: keywords
subject: variable stiffness
  topic: keywords
subject: robotic grasping
  topic: keywords
subject: automation flexibility
  topic: keywords
subject: adaptive gripper
  topic: keywords
creator: J. Turek
creator: L. Miskarik
creator: Jiri Vojtesek
creator: L. Kopecek
creator: L. Svacinova
creator: Ales Mizera
rights: Copyright (c) 2025 J Turek, L Miskarik, Jiri Vojtesek, Ales Mizera, L Kopecek, L Svacinova https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-04-01
publication date: 2025-04-01
doi: 10.4108/dtip.8719

Cloud-Based Data-Driven Behavior Model Recovery for Distributed Automation Systems
type: item
description: Industrial cyber-physical systems provide a bridge between legacy controllers and new edge devices that are usually equipped with massive computing power and storage capacity. The migration from legacy control systems to industrial cyber-physical systems is facing challenges as control code and design documents of legacy systems may not be available. This paper proposes a data-driven behavior model recovery method for the black-box distributed manufacturing system based on cloud computing. This method adopts the IEC 61499 function blocks as meta-models to describe system behaviors. The proposed framework includes three parts: data mining, logic restoration, and application construction. Raw collected data are processed and encapsulated into function block sets, then execution control charts, and finally function block types. This model recovery method is validated with a process control system of the food and beverage industry. A deployable function block network is generated by instantiating and connecting these function blocks.
subject: Research Articles
  topic: section
subject: Model-Driven Engineering
  topic: keywords
subject: IEC 61499 Function Blocks
  topic: keywords
subject: Model Recovery
  topic: keywords
subject: Finite-State Machine
  topic: keywords
subject: Data-Driven Model Generation
  topic: keywords
creator: Xian Wu
creator: Chuanyang Yu
creator: Likuan Zhang
creator: Hui Zhang
creator: Wenbin Dai
rights: Copyright (c) 2025 Xian Wu, Chuanyang Yu, Likuan Zhang, Hui Zhang, Wenbin Dai https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-03-19
publication date: 2025-03-19
doi: 10.4108/dtip.8591

Solving Facility Location and Supply Chain Management Problems Using Modified Population-Based TP-AB Algorithm
type: item
description: Locating optimal supply/ storage/ distribution facilities is critical in minimizing the establishment, transportation and distribution costs. This paper proposes one model for estimating the facility centres based on any specific criterion. A modified TP-AB algorithm solves the popular "Mini-Sum" and "Mini-Max" facility location problems by considering 36 European countries. The required population and Gross Domestic Product per capita data for the years 2013, 2018 and 2023 are extracted from the European Union portal. Capital cities of these 36 countries are taken as the representative demand points in the supply chain network and facility centres are located using unweighted and weighted Great Circle Distance. Since the data points are spread over the Earth's surface, Great Circle Distance is preferred over Euclidean Distance. It is observed that the “population centre”, “economic centre" and the "access centre" do not merge showing the variations in the population spread and economic strength among the European countries considered. Also, the feasibility of grouping the countries into any number of clusters based on the need is demonstrated.
subject: Research Articles
  topic: section
subject: Facility Location
  topic: keywords
subject: Access Centre
  topic: keywords
subject: Population Centre
  topic: keywords
subject: Economic Centre
  topic: keywords
subject: TP-AB Algorithm
  topic: keywords
creator: A. Baskar
creator: Michael Anthony Xavior
rights: Copyright (c) 2025 A. Baskar, Michael Anthony Xavior https://creativecommons.org/licenses/by-nc-sa/4.0
date: 2025-04-01
publication date: 2025-04-01
doi: 10.4108/dtip.8561