EAI Endorsed Transactions on Digital Transformation of Industrial Processes

A Two-Phase Hybrid GWO:TP-AB Algorithm for Solving Optimization Problems

2025-02-18T16:57:38+00:00

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.

Study of the process of purifying potassium humate suspension from suspended particles using industrial centrifuges

2025-07-06T17:33:50+00:00

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.

Digitization of civil architecture objects during wartime using photogrammetry: A case study of Sumy State University

2025-07-10T09:45:35+00:00

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.

A Practical Approach to Industrial Digitalization through Data Acquisition and Systems Integration for Predictive Maintenance

2025-07-10T21:12:15+00:00

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.

Identification of circulation effects in a closed loop of a hydrostatic-mechanical transmissions with a planetary mechanism on the input and output links

2025-08-01T18:10:43+00:00

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 transmission's operation in a closed loop with the planetary mechanism located on the input and output links. The presented mathematical equations describe changes in the kinematic and power indicators of the transmission. These equations are used to structure the internal gear ratio equation of the closed loop of the HMCVT with the planetary mechanism located on the input and output links of the transmission.

METHODS: The study used methods of differential and integral calculus to create a mathematical model of the operation of the hydrostatic-mechanical transmission. This model is based on fundamental equations that describe the kinematic, power and energy indicators of continuously variable transmissions with planetary mechanisms. Due to the means of digitization, namely three-dimensional (3D) technologies, it is possible to determine the patterns of distribution of the internal gear ratio by the hydraulic pump control parameter and the planetary mechanism design parameter. This increases the accuracy of the results obtained.

RESULTS: The main results of this study are the development of a mathematical model for analyzing changes in the internal gear ratio of the closed loop HMCVT, based on the control parameter of the hydraulic machine and the design parameter of the planetary mechanism. In addition, the analysis of the obtained results using modern digitalization tools, namely spatial drawings, demonstrated the effectiveness of 3D technologies in determining the optimal combinations of transmission schemes that avoid circulation effects.

CONCLUSION: This article concludes that, by using spatial illustration, dependencies of the internal gear ratio on the hydraulic pump control parameter and the design parameter of the planetary mechanism have been constructed. This provides the possibility of a broader analysis of patterns. Based on the analysis of circulation effects in the closed loop of the HMCVT, the range of changes to the planetary mechanism's design parameter has been obtained, which alters the internal gear ratio of the closed loop over a wide range.

Stress Factors in Technical Education: Digital Transformation as a Source of Emerging Challenges and Strategic Interventions

2025-07-16T10:26:09+00:00

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.

A Low-Cost Framework for Textile Yarn Characterization Using Image Processing

2025-08-02T13:37:27+00:00

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.

The Impact of generative artificial intelligence on students and teachers in the educational process

2025-04-08T21:41:11+00:00

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.

Research on the Monitoring of Selected Parameters of Technological Devices in the Conditions of a Digital Enterprise

2025-07-16T08:45:02+00:00

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.

A Structured Methodology for Synthesizing Parameters and Architecture of Robotic Technological Systems in the Digital Transformation of SME Engineering Production

2025-07-28T08:22:14+00:00

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 further enhanced by integrating artificial intelligence tools for decision-making during system design and optimization. This structured framework contributes to the digital resilience of SME manufacturing and aligns with Industry 4.0 principles.