Management and Production Engineering Review

Content

Management and Production Engineering Review | 2023 | vol. 14 | No 1

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Abstract

Leadership research is an essential part of all areas of organisational science worldwide, and there is still a lack of studies in this research area. The paper aims to determine leadership competency perceptions and their sub-competencies characteristics and determinants in the fourth industrial revolution era. The research survey, conducted in 2018-2021, covered a sample of 100 respondents from organisations from the Czech Republic. The most important competencies for leadership are effective communication, innovation, cooperation, creativity, solving problems, lifelong learning, Information and Communication Technology (ICT) and motivation and support of others. We selected statistical methods ANOVA and linear regression for the characteristics of the respondents and the cluster analysis for the leaders’ 4.0 types determination. The linear regression results showed that age, the field of education, position in the organisation and tenure in the organisation of the respondents affect their assessment of the level of leadership competency. We identified three management types that are currently facing the challenges of Industry 4.0: ICT-oriented Junior Managers, Top 4.0 Prepared Leaders, and Non-Creative Unmotivated Senior Directors. The contribution of this paper is the in-depth study in the area of perceived levels of partial competencies for leadership for different criteria of respondents.
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Authors and Affiliations

Julie Čermáková
1
Michal Houda
2
Ladislav Rolínek
1
Martin Pech
1
ORCID: ORCID

  1. University of South Bohemia: Jihoceska Univerzita v Ceskych Budejovicich, Department of Management, Faculty of Economics, Czech Republic
  2. University of South Bohemia: Jihoceska Univerzita v Ceskych Budejovicich, Department of Applied Mathematicsand Informatics, Faculty of Economics, Czech Republic
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Abstract

The paper considers the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the makespan and the total tardiness. The multi-objective genetic algorithm is applied to solve this problem, which belongs to the non-deterministic polynomial-time (NP)-hard class. In the structure of the proposed algorithm, the initial population, neighborhood search structures and dispatching rules are studied to achieve more efficient solutions. The performance of the proposed algorithm compared to the efficient algorithm available in literature (known as NSGA-II) is expressed in terms of the data envelopment analysis method. The computational results confirm that the set of efficient solutions of the proposed algorithm is more efficient than the other algorithm.
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Authors and Affiliations

Seyyed Mostafa Mousavi
1
Parisa Shahnazari-Shahrezaei
2

  1. Department of Technical and Engineering, Nowshahr Branch, Islamic Azad University, Mazandaran, Iran
  2. Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
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Abstract

Nowadays, it is necessary to develop a conceptual framework for analysing the relationship between the implementation of Additive Manufacturing (AM) and Supply Chain Management (SCM). In this context, a gap in the research has been observed in the new approach to designing the importance of AM in SCM. The main contribution of this paper, therefore, is a new framework to formulate the role in adopting AM in SCM. The research methodology is based on detailed literature studies of AM in relation to the SCM process within a manufacturing company, as well on a case study, namely the COWAN GmbH manufacturing company who specialise in producing homewares for motorhome enthusiasts. As highlighted in the state-of-the-art analysis, no work, currently available, supports all the features presented.
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Authors and Affiliations

Justyna Patalas-Maliszewska
1 2
ORCID: ORCID
Katarzyna Kowalczewska
3
Matthias Rehm
2
ORCID: ORCID

  1. Institute of Mechanical Engineering, University of Zielona Góra, Poland
  2. Professorship Production Systems and Processes, Chemnitz University of Technology, Germany
  3. Germany, COWAN GmbH, Germany
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Abstract

The article deals with a widely used method of measuring the overall efficiency of equipment (OEE), which in combination with technologies and software tools is gaining in importance. The overall efficiency of OEE equipment is a key performance metric for machines and equipment to identify hidden capacities and increase production productivity. The intensification of Industry 4.0 in traditional manufacturing companies supports and creates the conditions for their transformation into a smart factory. The integration of intelligent machines and devices with complex human-machine communication network systems requires a new direction in measuring and increasing OEE. Mass customization, resp. personalization of production raises a high need to monitor, improve and further maintain productivity. The aim of the article is to create a simulation model of the production process and test the energy consumption of selected equipment using TX Plant Simulation software with a proposal of measures to increase the OEE of the company.
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Authors and Affiliations

Miriam Pekarcíková
1
Peter Trebuna
2
Marek Kliment
2
Jozef Trojan
1
Ján Kopec
1
Michal Dic
1
Jana Kronová
1

  1. Department of Industrial and Digital Engineering, Faculty of Mechanical Engineering, Technical University of Košice, Slovak Republic
  2. Department of Industrial and Digital Engineering, Technical University of Košice
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Abstract

Appropriate product categorization in distribution centres is important for business success because of the possibility of intuitive product finding by the picker and increased product movement. Both of these factors result in the operational efficiency of the distribution centre. The goal of this paper is to explore a model of shelf space dimensioning of storage location on a rack with vertical and horizontal product categorization in a distribution centre, where the aim is to increase total product movement/profit from all shelves of the rack. This is controlled by a packer who must complete orders by getting the goods from shelves and picking them to the container. In this problem, we develop two heuristics and compare the archived results to the CPLEX solver. The average profit ratios of both heuristics are high and approximately equal to 99%. In 10 cases, optimal solutions have been found by heuristics.
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Authors and Affiliations

Kateryna Czerniachowska
1
ORCID: ORCID
Radosław Wichniarek
2
ORCID: ORCID
Krzysztof Żywicki
2
ORCID: ORCID

  1. Wroclaw University of Economics and Business, Wroclaw, Poland
  2. Poznan University of Technology, Poznan, Poland
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Abstract

Nondestructive and contactless online approaches for detecting defects in polymer films are of significant interest in manufacturing. This paper develops vision-based quality metrics for detecting the defects of width consistency, film edge straightness, and specks in a polymeric film production process. The three metrics are calculated from an online low-cost grayscale camera positioned over the moving film before the final collection roller and can be implemented in real-time to monitor the film manufacturing for process and quality control. The objective metrics are calibrated to correlate with an expert ranking of test samples, and results show that they can be used to detect defects and measure the quality of polymer films with satisfactory accuracy.
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Authors and Affiliations

Nathir Rawashedeh
1 2
ORCID: ORCID
Paniz Hazaveh
1
Safwan Altarazi
2
ORCID: ORCID

  1. Michigan Technological University, College of Computing, USA
  2. German Jordanian University, School of Applied Technical Sciences, Jordan
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Abstract

Value stream mapping (VSM) is a well-known lean analytical tool in identifying wastes, value, value stream, and flow of materials and information. However, process variability is a waste that traditional VSM cannot define or measure since it is considered as a static tool. For that, a new model named Variable Value Stream Mapping (V-VSM) was developed in this study to integrate VSM with risk management (RM) using Monte Carlo simulation. This model is capable of generating performance statistics to define, analyze, and show the impact of variability within VSM. The platform of this integration is under Deming’s Plan-Do-Check-Act (PDCA) cycle to systematically implement and conduct V-VSM model. The model has been developed and designed through literature investigation and reports that lead in defining the main four concepts named as; Continuous Improvement, Data Variability, Decision-Making, and Data Estimation. These concepts can be considered as connecting points between VSM, RM and PDCA.
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Authors and Affiliations

Alaa Salahuddin Araibi
1
Mohamad Shaiful Ashrul Ishak
2
ORCID: ORCID
Muhanad Hatem Shadhar
1

  1. Civil Engineering Department, Dijlah University College, Iraq
  2. Faculty of Mechanical Engineering Technology, Universiti Malaysia Perlis, Malaysia
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Abstract

The purpose of this article is to present a proposal for an expert’s model of managerial competencies in the era of the fourth industrial revolution, called Industry 4.0. This revolution results in the emergence of new competency requirements for employees at every organizational level. In the article, we focused on the requirements for Engineers 4.0, in connection with managerial competencies expected from them. In order to answer the research questions, we conducted expert research by referring to our previous studies. Findings: The conducted research allowed to develop an expert’s model of managerial competencies for Engineer 4.0 (EMMCE). The results of the study allowed to determine the scope of managerial competencies for an engineer in the age of Industry 4.0, thus contributing, in a practical scope, to the creation of requirements for candidates applying for a managerial position in manufacturing enterprises. The model makes it possible for educational and training entities to adapt their teaching programmes and training offer to the modern requirements of the industry.
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Authors and Affiliations

Ewa Więcek-Janka
1
ORCID: ORCID
Karolina Werner-Lewandowska
1
ORCID: ORCID
Adam Radecki
1
ORCID: ORCID

  1. Faculty of Management Engineering, Poznań University of Technology, Poland
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Abstract

The rapid development of digital technologies have created unprecedented opportunities for the industrial world. Enterprises, especially small and medium sized companies, struggle to successfully implement these technologies, and there is scant literature to support this endeavor. The authors hypothesize that ERP (Enterprise Resource Management) implementation, being a mature field, can guide digital technology implementation, taking into considerations the similarities. A systematic literature review was conducted to determine the critical success factors (CSF) of ERP implementation in SMEs that were used to derive guidelines for digital technology implementation case study. The results of the case study is another list of CSF that more correctly mirror the digital technology implementation needs. They are: “digitalization strategic plan”; “project sponsor/leader”; “commitment to the workplace”; “involvement of top management”; “reasonable project scope”; “compatibility with existing processes/systems”; “progressing with small steps”; “use of correct competencies”; and “involving the users”.
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Authors and Affiliations

Dan Palade
1
ORCID: ORCID
Charles Møller
1
ORCID: ORCID

  1. Materials and Production, Aalborg University, Denmark
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Abstract

This paper aims to improve understanding of the drivers and barriers to digital transformation in asset management. Accordingly, this paper contributes to the literature by conducting a qualitative Delphi study with 15 experts (including academia, consultancy and industry) to identify, validate, and classify the drivers and barriers affecting digital transformation in asset management. As a result of the experts’ interactions, 20 barriers were identified. The main barriers to digital transformation in asset management are the following: Misunderstanding of the strategic importance of asset management, no clear vision/strategy, existing mindset and culture, inadequate asset management system, lack of understanding of digital trends, and lack of employee knowledge and skills. The study also highlights 12 drivers that are critical to the digital transformation of asset management. These include cost reductions, opportunities in condition monitoring of assets, expected benefits in asset management processes, expected benefits in risk management and others.
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Authors and Affiliations

Damjan Maletic
1
Marta Grabowska
2
Matjaž Maletic
1

  1. Faculty of Organizational Sciences, University of Maribor, Slovenia
  2. Management and Production Engineering Division, Poznan University of Technology, Poland
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Abstract

This paper highlights the storage charging and discharging issue. The study objective is to manage the energy inputs and outputs of the principal grid at the same time in order to maximize profit while decreasing costs, as well as to ensure the availability of energy according to demand and the decisions to either save or search for energy. A fuzzy logic control model is applied in MATLAB Simulink to deal with the system’s uncertainties in scheduling the storage battery technology and the charging- discharging. The results proved that the fuzzy logic model has the potential to efficiently lower fluctuations and prolong the lifecycle.
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Authors and Affiliations

Meryem Meliani
1
ORCID: ORCID
Abdellah El Barkany
1
Ikram El Abbassi
2
Rafik Absi
2
Faouaz Jeffali
3

  1. Mechanical Engineering Laboratory, Faculty of Science and Technology, Sidi Mohammed Ben Abdellah University, Morocco
  2. ECAM, EPMI, France
  3. Laboratory of Materials, Waves, Energy and Environment, Mohammed First University, Morocco
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Abstract

Maintenance is a key manufacturing function that contributes to a company’s productivity, profitability and sustainability. Unfortunately, many aspects of the contribution of maintenance to sustainability in manufacturing remain unexplored, and many enterprises are not yet ready to assess the maintenance impacts on their sustainability. Maturity models are useful tools for assessing maintenance practices; however, no maintenance maturity model that allows the evaluation of the contribution of maintenance to sustainable performance was found in literature. This paper proposes a model for assessing the maturity and sustainability of maintenance processes. The model outputs are: a measure of the maintenance and sustainability maturity level; recommendations for improvement to undertake to enhance maintenance maturity and, thus, meet sustainability standards. The model was applied in three manufacturing enterprises: the calculation of their maintenance maturity and sustainability indices made the maintenance stakeholders more aware of the need to implement effective strategies for more sustainable maintenance performance.
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Authors and Affiliations

Chiara Franciosi
1
ORCID: ORCID
Alessia Maria Rosaria Tortora
2
ORCID: ORCID
Salvatore Miranda
2

  1. Université de Lorraine, CNRS, CRAN, F-54000 Nancy, France
  2. Department of Industrial Engineering, University of Salerno, Italy

Instructions for authors

REVIEW PROCESS

Received manuscripts are first examined by the Management and Production Engineering Review Editors.
Manuscripts clearly not suitable for publication, incomplete or not prepared in the required style will be sent back to the authors without scientific review, but may be resubmitted as soon as they have been corrected.
The corresponding author will be notified by e-mail when the manuscript is registered at the Editorial Office (https://www.editorialsystem.com/mper/). The responsible editor will make the decision either to send the manuscript to another reviewer to resolve the difference of opinion or return it to the authors for revision. The ultimate decision to accept, accept subject to correction, or reject a manuscript lies within the prerogative of the Editor-in-Chief and is not subject to appeal. The editors are not obligated to justify their decision.
All manuscripts submitted to MPER editorial system ( https://www.editorialsystem.com/mper/) will be sent to at least two and in some cases three reviewers for passing the double-blind review process.
The material formatted in the MPER format must be unpublished and not under submission elsewhere.

REVIEWERS
Once a year a list of co-operating reviewers is publish in electronic version of MPER. All articles published in MPER are published in open access.


APC
In order to provide free access to readers, and to cover the costs of copyediting, typesetting, long-term archiving, and journal management, an article processing charge (APC) of 800 PLN (about 180 Euro, VAT included) for 10-page article applies to papers accepted after peer review. Each additional page of the article (over 10 pages) costs 80 PLN (about 18 Euro, VAT included).
Maximum length of the article is 18 pages (using MPER template).
There is no submission charge.

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Template for Authors





Additional info

The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on https://creativecommons.org/licenses/by/4.0/.

Publication Ethics Policy

The ethics statements for the journal Management and Production Engineering Review are based on the guidelines of Committee on publication ethics (COPE) and the ELSEVIER publishing ethics resource kit.
For Authors: All articles, published in the journal Management and Production Engineering Review have to comprise a list of references which correspond with the journal’s Instructions to authors for paper preparation. The authors should ensure that they have written entirely original works, and if the authors have used the work and/or words of others that this has been appropriately cited or quoted. All articles are tested using antyplagiarism programme. An author should not in general publish manuscripts describing essentially the same research in more than one journal or primary publication. Submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behaviour and is unacceptable. Authorship should be limited to those who have made a significant contribution to the conception, design, execution, or interpretation of the reported study. The corresponding author should ensure that all co-authors have seen and approved the final version of the paper and have agreed to its submission for publication. All authors should disclose in their manuscript any financial or other substantive conflict of interest that might be construed to influence the results or interpretation of their manuscript. All sources of financial support for the project should be disclosed.
For Editor-in-Chief: The editor is responsible for decision which of the articles submitted to the journal should be published. The editor and editorial board and office must not disclose any information about a submitted manuscript to anyone other than the corresponding author, reviewers, potential reviewers, other editorial advisers, and the publisher, as appropriate. Unpublished materials disclosed in a submitted manuscript must not be used in an editor's own research without the express written consent of the author.
For Reviewers: Peer review helps the editor in making editorial decisions and also assist the author in improving the paper. Any selected referee who feels unqualified to review the research reported in a manuscript or knows that its prompt review will be impossible should notify the editor and excuse himself from the review process. Any manuscripts received for review must be treated as confidential documents. They must not be shown to or discussed with others except as authorized by the editor. Reviews should be conducted objectively. Personal criticism of the author is inappropriate. Reviewers should identify relevant published work that has not been cited by the authors. Any statement that an observation, derivation, or argument had been previously reported should be accompanied by the relevant citation. A reviewer should also call to the editor's attention any substantial similarity or overlap between the manuscript under consideration and any other published paper of which they have personal knowledge. Information obtained through peer review must be kept confidential and not used for personal advantage. Reviewers should not consider manuscripts in which they have conflicts of interest resulting from competitive, collaborative, or other relationships or connections with any of the authors, companies, or institutions connected to the papers. Other sources: http://apem-journal.org/

Peer-review Procedure

Received manuscripts are first examined by the Management and Production Engineering Review Editors. Manuscripts clearly not suitable for publication, incomplete or not prepared in the required style will be sent back to the authors without scientific review, but may be resubmitted as soon as they have been corrected. The corresponding author will be notified by e-mail when the manuscript is registered at the Editorial Office (marta.grabowska@put.poznan.pl; mper@put.poznan.pl). The ultimate decision to accept, accept subject to correction, or reject a manuscript lies within the prerogative of the Editor-in-Chief and is not subject to appeal. The editors are not obligated to justify their decision. All manuscripts submitted to MPER editorial office (https://www.editorialsystem.com/mper/) will be sent to at least two and in some cases three reviewers for passing the double-blind review process. The responsible editor will make the decision either to send the manuscript to another reviewer to resolve the difference of opinion or return it to the authors for revision.

The average time during which the preliminary assessment of manuscripts is conducted - 14 days
The average time during which the reviews of manuscripts are conducted - 6 months
The average time in which the article is published - 8.4 months

Reviewers

Degree Name Surname Affiliation Dr. Hind Ali University of Technology, Iraq Prof. Katarzyna Antosz Rzeszow University of Technology, Poland Dr. Bagus Arthaya Mechatronics Engineering Universitas Parahyangan, Indonesia Dr. Sarini Azizan Australian National University, Australia Prof. Zbiegniew Banaszak Koszalin University of Technology, Poland Prof. Lucia Bednarova Technical University of Kosice, Slovak Republic Prof. Kamila Borsekova UNIVERZITA MATEJA BELA V BANSKEJ BYSTRICI, Slovak Republic Prof. Rachid Boutarfa Hassan First University, Morocco Prof. Anna Burduk Wrocław University of Science and Technology, Poland Dr. Virginia Casey Universidad Nacional de Rosario, Argentina Claudiu Cicea Bucharest University of Economic Studies Romania, Romania Prof. Ömer Cora Karadeniz Technical University, Turkey Prof. Wiesław Danielak Uniwersytet Zielonogórski, Poland Dr. Jacek Diakun Poznan University of Technology, Poland Dr. Ewa Dostatni Poznan University of Technology, Poland Prof. Marek Dźwiarek Central Institute for Labor Protection Dr. Milan Edl University of West Bohemia, Czech Republic Joanna Ejdys Bialystok University of Technology, Poland Prof. Abdellah El barkany Sidi Mohamed Ben Abdellah University, Morocco Francesco Facchini Università degli Studi di Bari, Italy Prof. Mária Magdolna Farkasné Fekete Szent István University, Hungary Prof. Çetin Fatih Başkent Üniversitesi, Turkey Mose Gallo University of Napoli Federico, Italy Dr. Mit Gandhi Gujarat Gas Limited, India Prof. Józef Gawlik Cracow University of Technology, Poland Dr. Andrzej Gessner Poznan University of Technology, Poland Dr. Pedro Glass Universitatea Valahia din Targoviste, Romania Dr. Arkadiusz Gola Lublin University of Technology, Poland Alireza Goli Yazd university, Iran Dr. Magdalena Graczyk-Kucharska Poznan University of Technology, Poland Dr. Damian Grajewski Poznan University of Technology, Poland Dr. Łukasz Grudzień Poznan University of Technology, Poland Patrik Grznár University of Žilina, Slovak Republic Dr. Anouar Hallioui Sidi Mohamed Ben Abdellah University, Morocco Prof. Ali Hamidoglu Turkey Prof. Adam Hamrol Poznan University of Technology, Poland Dr. ni luh putu hariastuti itats, Indonesia Dr. Christian Harito Bina Nusantara University, Indonesia Dr. Muatazz Hazza School of Engineering, United Arab Emirates Dr. Ali Jaboob Dhofar University, Oman Prof. Małgorzata Jasiulewicz-Kaczmarek Poznan University of Technology, Poland Prof. Oláh Judit University of Debrecen, Hungary Prof. Jan Klimek Szkoła Główna Handlowa, Poland Dr. Nataliia Klymenko National University of Life and Environmental Sciences of Ukraine Prof. Sławomir Kłos University of Zielona Góra, Poland Dr. Peter Kostal Slovenská Technická Univerzita V Bratislave, Slovak Republic Prof. Martin Krajčovič University of Žilina, Slovak Republic Prof. Robert Kucęba Politechnika Częstochowska, Poland Dr. Agnieszka Kujawińska Poznan University of Technology, Poland Dr. Edyta Kulej-Dudek Politechnika Częstochowska, Poland Prof. Christian Landschützer Graz University of Technology, Austria Dr. Anna Lewandowska-Ciszek Poznan University of Economics and Business, Poland Dr. Damjan Maletič University of Maribor, Slovenia Prof. Marcela Malindzakova Technical University, Slovak Republic Prof. Józef Matuszek The Silesian Technical University Prof. Janusz Mleczko University of Bielsko-Biala Dr. Rami Mokao MIS - Management Information Systems, HIAST, Syria Prof. Maria Elena Nenni University of Naples, Italy Dr. Nor Hasrul Akhmal Ngadiman Universiti Teknologi Malaysia, Malaysia Dr. Dinh Son Nguyen University of Science and Technology, Viet Nam Dr. Duc Duy Nguyen Ho Chi Minh Technology University (HCMUT), Viet Nam Dr. Filscha Nurprihatin Sampoerna University, Indonesia Prof. ass. Filip Osiński Poznan University of Technology, Poland Dr. Ivan Pavlenko Sumy State University, Ukraine Robert Perkin BorgWarner, United States Prof. Alin Pop University of Oradea, Romania Prof. Ravipudi Venkata Rao National Institute of Technology, India Marta Rinaldi University of Campania, Italy Dr. Michał Rogalewicz Poznan University of Technology, Poland Prof. David Romero Tecnológico de Monterrey, Mexico Prof. Elmadani Saad Hassan First university of Settat, Morocco Prof. Krzysztof Santarek Warsaw University of Technology, Poland Prof. shankar sehgal Panjab University Chandigarh, India Dr. Robert Sika Poznan University of Technology, Poland Dr. Chansiri Singhtaun Kasetsart University, Thailand Prof. Bożena Skołud Silesian University of Technology, Poland Lucjan Sobiesław Jagiellonian University, Poland Dr. Fabiana Tornese University of Salento, Italy Prof. Stefan Trzcielinski Poznan University of Technology, Poland Amit Kumar Tyagi Centre for Advanced Data Science, India Dr. Cang Vo Binh Duong University, Viet Nam Dr. Jaroslav Vrchota University of South Bohemia České Budějovice, Czech Republic Dr. Radosław Wichniarek Poznan University of Technology, Poland Prof. Ewa Więcek-Janka Poznan University of Technology, Poland Prof. Josef Zajac Uniwersytet Techniczny w Koszycach, Slovak Republic Dr. Aurora Zen Universidade Federal do Rio Grande do Sul, Brazil

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