Search in Publications

Found 6334 publications

Digital Twins in Sustainable Supply Chains: A Comprehensive Review of Current Applications and Enablers for Successful Adoption †

László Buics Lahiru Vimukthi Bandara

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

Digital Twins (DT) are an emerging trend in diversified industrial sectors and their value chains. This study aims to explore current DT applications within SCs, focusing on sustainable inbound and outbound logistics and identifying key enablers that will facilitate the successful adoption of DTs in SCs. Using the PEO model and employing the PRISMA framework, this study screened articles from the Scopus database to explore the existing knowledge related to this topic. A steep increase in articles related to DTs over the past 10 years indicates that there is growing attention in exploring and leveraging this technology for various applications. The successful adoption of DTs is driven by several key factors, including advanced technological infrastructure; standardized processes; continuous improvement; knowledge workers; technologies like IoT, IIoT, AR/VR; and managerial support.

Open Access: Yes

DOI: 10.3390/engproc2024079064

Courier, Express, Parcel market with a complex system interpretation-The Hungarian case

Edit Süle Csilla Bartucz

Publication Name: 2024 IEEE 15th International Colloquium of Logistics and Supply Chain Management Logistiqua 2024

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The parcel delivery market functions as a complex system, according to the authors of this article. By comprehending and outlining the unique characteristics of the complex system, the authors aim to substantiate their assertion. The Covid pandemic in Hungary's Courier, Express, and Parcel market in 2020 caused a previously unprecedented increase in parcel delivery demands similarly to other countries. The epidemic-related rise in e-commerce additionally resulted significant changes to the approach by which the parcel delivery industry operated. Unexpected collaboration amongst service providers started to emerge on the parcel market in 2021. These alterations are of a kind that suggests the behavioural characteristics of a complex system. Considering that the leading service providers' autonomous operations constitute the primary characteristic of the Hungarian parcel delivery market, an analysis from a scientific perspective of the events that transpired in the Hungarian parcel delivery market is imperative to understand the reasons for this shift. Two research questions have been formulated by the authors, one of which investigates whether the parcel delivery market is considered as a system (complex system), it is conceivable for collaboration to emerge spontaneously if this is the most effective form for the system. The other research question concerns whether cooperation can be established in a market without external interference. To provide an explanation for the developments that transpired between 2020 and 2022, the authors analyse the Hungarian parcel delivery market as a complex system. In complex systems, transformation and self-organization occur naturally when the system decides that a particular shape is best for it in its current environment. During the time under review, the equilibrium of the parcel delivery market in Hungary was disrupted by the unanticipated rise in e-commerce, and the increased demands of customers nearly brought the service providers to a state of chaos. Consequently, the behaviour of service providers started to shift from their previous standards. The article's uniqueness is in its classification of the parcel delivery market as a complex system, which can be used to anticipate the current and expected behaviour of the stakeholders.

Open Access: Yes

DOI: 10.1109/LOGISTIQUA61063.2024.10571534

Advanced Numerical Simulation and Modeling of Multi-Pass Welding Processes: Detailed Analysis of Temperature Distribution in Structural Elements

János Szép Majid Movahedi Rad Daniel Gosztola Péter Grubits

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 823-828

Description:

The growing importance of numerical simulations in the welding industry stems from their ability to enhance structural performance and sustainability by ensuring optimal manufacturing conditions. The use of the finite element method (FEM) allows for detailed and precise calculations of the mechanical and material changes caused by the welding process. Acquiring knowledge of these parameters not only serves to augment the quality of the manufacturing process but also yields consequential benefits, such as reducing adverse effects. Consequently, the enhancement of structural performance and prolonged lifespan becomes achievable, aligning with overarching sustainability goals. To achieve this goal, this paper utilizes numerical simulations of welding processes based on experimental tests, with a specific focus on analyzing temperatures generated within the structures. In the finite element analysis (FEA), a total of 12 welding cycles were systematically modeled to align with experimental conditions, incorporating cooling intervals, preheating considerations, and the relevant section of the connecting concrete structure with studs. The outcomes of this research exemplify the potential of numerical simulation in the welding industry, demonstrating a diverse range of results achieved through FEA to enhance the quality of structures within the context of sustainability.

Open Access: Yes

DOI: 10.3303/CET24114138

Predicting somatic cell count in milk samples using machine learning∗

István Szabó Bence Tarr János Tőzsér

Publication Name: Annales Mathematicae Et Informaticae

Publication Date: 2024-01-01

Volume: 60

Issue: Unknown

Page Range: 159-168

Description:

Milk quality is an important factor both for the farmers to be able to sell their products and for the milk industry to be able to plan its production based on quantity and quality. Milk quality has a direct link with cow health, more specifically with utter health. One of the most common utter diseases is mastitis. It always captures a lot of interest based on its frequency and cost as a dairy disease which eventually leads to an involuntary and premature culling of milking cows and decreased milk yield. The genetic evaluation of mastitis is very difficult as it is a low heritable trait and categorical in nature [2]. That is why it is necessary to find markers that could predict the occurrence of mastitis. One of the widely used such markers is the somatic cell count (SCC) [9] which is considered to be the most suitable indicator trait for mastitis resistance given its medium to high genetic correlation with mastitis and its greater heritability than mastitis. The SCC is also easy to record in the practice. The selection for lower SCC in milk has a positive effect on the incidence of mastitis. The selection against high SCC also does not deteriorate the immune system of cattle and decreases the risk of infection at the same time. The genetic evaluation [1] of this trait is mostly based on somatic cell score (SCS), a logarithmic transformation of SCC to achieve normality of distribution. In our study, we used the milk database of Holstein cows from 3 different farms. From each farm, we had altogether 8000 samples tested. The samples were analyzed using chemical methods every month for a year. 11 different types of data were recorded from each sample. Our aim was to find the best mixture of recorded data that would predict the value of linearized somatic cell count. After the logarithmic linearization the SCC results were divided into 3 main groups (based on the probability of mastitis). Thus our prediction problem turned into a classification problem. We used machine learning to train our algorithm. We experimented with different types of classification methods and found good results for the prediction of SCC in milk samples. We changed the input variables as not all the 9 measured input variables will be necessary for good prediction results. Our preliminary results show that using machine learning it is possible to build a model that can be used to predict mastitis in dairy cows based on variables generally analyzed during milk quality checking tests.

Open Access: Yes

DOI: 10.33039/ami.2024.02.004

Optimizing Human Resources for Efficiency and Sustainability through Business Process Modelling with Large Language Models

Boglárka Eisingerné Balassa Dániel Csikor Réka Koteczki

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 499-504

Description:

In today's business situations, effective use of human resources is critical to organisational performance and long-term growth. Employees frequently squander important time on monotonous jobs that take up their time. This problem negatively affects not only business efficiency but also labour market satisfaction and economic growth, contrary to the goals of Sustainable Development Goals (SDGs) 8 (Decent work and economic growth) and 9 (Industry, innovation and infrastructure). The aim of the research was to see how large language models (LLM) can help to optimise human resources by automating less skill-intensive, time-consuming tasks. For the analysis, a case study was conducted using the methodology of business process modelling (BPM) to compare the efficiency of a project management task ('reporting') with and without the use of ChatGPT technology. The model was used to analyse quantitative data such as process duration, labour costs, overhead costs and overhead volume. The research shows that LLM can significantly reduce the time workers spend on routine tasks, allowing them to focus on higher-value jobs that match their skills. In the case where ChatGPT was used by the participants to prepare the report, the whole process took 455.5 h less. The time savings contributed to a reduction in wage costs and overheads, which in total represents a saving of € 8,046.30. Based on the results, it is believed that LLMs have the potential to increase efficiency and sustainability.

Open Access: Yes

DOI: 10.3303/CET24114084

Bifurcations and Application of the Vallis - Model

Antal Joos Bálint Nagy Eniko Nagy Gyorgy Molnar

Publication Name: Iccc 2024 IEEE 11th International Conference on Computational Cybernetics and Cyber Medical Systems Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 55-60

Description:

Investigating chaotic systems is a fertile field considering that chaos is an exotic chapter in the theory of differential equations, and it has useful applications in the theory of communications. In this work a well-known chaotic system is investigated from the bifurcation point of view and some applications are also introduced. The data studied are also visualized for better clarity. The results observed can be helpful in the encryption methods of the implementation of different communication channels.

Open Access: Yes

DOI: 10.1109/ICCC62278.2024.10583106

How to Develop a Sustainable Innovation Ecosystem? Example of ZalaZONE

András Háry Leticia Pekk Virag Meszaros Csilla Toth

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 883-888

Description:

The purpose of the paper is to analyse the typical research trends along the current challenges of the social, environmental and business aspects of sustainability and discuss the issues of geographically concentrated, park-like innovation ecosystems. At ZalaZONE Park as a consciously built innovation ecosystem, sustainability aspects are organically integrated into its development and into the operation approach, giving the empiric case for the research question. The ZalaZONE Energy Ecosystem Program connects the subject of sustainability with the innovation ecosystem on system level through innovative technologies and future-oriented environmental initiatives in various energy projects. In connection with this, it is also investigated is how new technologies support and ensure the long-term sustainability of the innovation ecosystem, and how the features of this relationship can be interpreted. Since ZalaZONE Park shows the characteristics of complex systems, the overall framework of the analysis is provided by the ecosystem model previously developed by the authors and further developed in the present analysis. Such a model contributes to each development step of the innovation ecosystem for sake of balanced and sustainability-oriented growth. Finally, an aggregated system model was presented including aspects of sustainability, with particular regard to the characteristics of complex systems.

Open Access: Yes

DOI: 10.3303/CET24114148

Transforming Public Services Management: a P-Graph Methodology Case Study and Scenario Analysis

Boglárka Eisingerné Balassa László Buics

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 475-480

Description:

This study advances university enrolment optimization in Public Services Management towards sustainability, utilizing case studies, scenario analyses, and P-Graph methodology. The study evaluates administrative workloads across three intensity levels—low, average, and highly overloaded—and enhance our methodology by incorporating data that influences the process's inception and conclusion in all scenarios. Our research is further expanded with qualitative alongside quantitative methods for a thorough perspective. Our findings indicate substantial overtime and high turnover rates among administrators due to enrolment demands. The P-Graph methodology exposes significant inefficiencies and difficulties in meeting standard hour targets. It also reveals the optimal process flow and resource allocation, promoting its wider application in public service sectors for sustainable management practices. In collaboration with administrators to meticulously record task times and case revisits, the research offers an in-depth evaluation of administrative efficiency and resource utilization. The study concludes that managing an average enrolment of 4,200 students is inefficient for administrative employees, leading to high overtime rates that harm staff well-being. Our holistic approach, augmented with initial and final process impact data plus qualitative insights, highlights the P-Graph methodology's potential in transforming Public Services Management. This method not only enhances process efficiency and resource allocation but also aligns with sustainability objectives, marking a significant stride in sustainable public service practices.

Open Access: Yes

DOI: 10.3303/CET24114080

The Effect of Lubricant Viscosity Variation on Tooth Friction and Hence on the Energetic Behaviour of Gear Unit

József Polák

Publication Name: Chemical Engineering Transactions

Publication Date: 2024-01-01

Volume: 114

Issue: Unknown

Page Range: 853-858

Description:

Earlier this year, I created a mathematical model of a gear unit that allowed me to investigate the energy performance of a vehicle gear unit over its full operating range. In the model created, the value of the tooth friction was determined during a precalculation and then entered into the model as a constant parameter. The problem with this approach is that it is not automated, so during the energy analysis or a possible optimisation of the gear unit, the tooth friction is always present in the model as a constant value, whereas in reality, the value of the tooth friction is different for different working points (wheel torque: Mw, wheel speed: nw) and different geometries. The viscosity of the selected lubricant has a significant influence on tooth friction, which varies partly due to temperature and partly due to load. In this paper, I will investigate the viscosity of the oil required by the gear unit at different operating points for proper operation and how this affects tooth friction and, hence, the gear unit energy loss. Since the studies showed that the effect of oil viscosity is not significant but not negligible, the determination of tooth friction can be incorporated into the gear unit model using a MATLAB function so that it is re-determined at each operating point and for each geometry change. With this modification, the estimation generated by the mathematical model describing the energetic behavior of the gear unit can be made more accurate.

Open Access: Yes

DOI: 10.3303/CET24114143