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.


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Maximum length of the article is 18 pages (using MPER template).
There is no submission charge.

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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/.

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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.
Authors are accountable for the originality, validity and integrity of the content of their submissions. In choosing to use AI tools, authors are expected to do so responsibly and in accordance with our editorial policies on authorship and principles of publishing ethics. Authorship requires taking accountability for content, consenting to publication via an author publishing agreement, giving contractual assurances about the integrity of the work, among other principles. These are uniquely human responsibilities that cannot be undertaken by AI tools. Therefore, AI tools must not be listed as an author. Authors must, however, acknowledge all sources and contributors included in their work. Where AI tools are used, such use must be acknowledged and documented appropriately.
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

2024
No Name Surname Affiliation
1 Abd El-Rahman Abd El-Raouf Ahmed Agricultural Engineering, Agricultural Engineering Research Institute, Giza , Egypr
2 Wiktor Adamus Jagiellonian University, Poland
3 Shoaib Akhtar Fatima Jinnah Women University, Pakistan
4 Mohammad Al-Adaileh "COLLEGE OF ENGINEERING Engineering, Technology, and Management Assistant Professor of Instruction, United States"
5 Hind Ali University of Technology, Iraq
6 Katarzyna Antosz Rzeszow University of Technology, Poland
7 Muhammad Asrol Binus University, Indonesia
8 Lucia Bednarova Technical University of Kosice, Slovak Republic
9 Haniyah Bilal Haverford university, United States
10 Berihun Bizuneh "Bahir Dar University Bahir Dar Univ, Ethiopian Inst Text & Fash Technol, Bahir Dar, Ethiopia, Ethiopia"
11 Łukasz Brzeziński Katedra Organizacji i Zarządzania, Wyższa Szkoła Logistyki w Poznaniu, Poland
12 Waldemar Budner Katedra Logistyki, Uniwersytet Ekonomiczny w Poznaniu, Poland
13 Anna Burduk Wrocław University of Science and Technology, Poland
14 Vishnu C R Department of Humanities and Social Sciences, Indian Institute of Technology Tirupati, India
15 Fatih Çetin Başkent Üniversitesi, Turkey
16 Danylo Cherevatskyi Institute of Industrial Economics of NAS of Ukraine: Kiev, UA, Ukraine
17 Claudiu Cicea Bucharest University of Economic Studies Romania, Romania
18 Hasan Huseyin Coban Department of Electrical Engineering, Bartin University, Turkey
19 Juan Cogollo-Florez Universidad Nacional de Colombia, Colombia
20 David Coopler Universitat Politècnica de València, Romania
21 Ömer Cora Karadeniz Technical University, Turkey
22 Margareta Coteata Gheorghe Asachi Technical University of Iasi, Department of Manufacturing Engineering, Romania
23 Szymon Cyfert Poznań University of Economics and Business, Poland
24 Valentina Di Pasquale Department of Industrial Engineering, University of Salerno, Italy
25 Milan Edl University of West Bohemia, Czech Republic
26 Luis Edwards Cornell University, United States
27 Joanna Ejdys Bialystok University of Technology, Poland
28 Abdellah El barkany Sidi Mohamed Ben Abdellah University Faculty of Science and Technology of Fez, Morocco
29 Chiara Franciosi CRAN UMR 7039, Université de Lorraine, France
30 Mose Gallo Materials and Industrial Production Engineering, University of Napoli Federico, Italy
31 Tetiana Galushkina State Ecological Academy of Postgraduate Education and Management, Ukraine
32 Józef Gawlik Cracow University of Technology, Institut of Production Engineering, Poland
33 Rohollah Ghasemi, College of Management, University of Tehran, Iran
34 Arkadiusz Gola, Lublin University of Technology, Faculty of Mechanical Engineering, Poland
35 Alireza Goli Department of industrial engineering, Yazd university, Yazd, Iran
36 Magdalena Graczyk-Kucharska, Politechnika Poznańska, Poland
37 Adriana Grenčíková Industry 4.0, Human factor, Ergonomic, Slovak Republic
38 Patrik Grznár, Department of Industrial Engineering, University of Žilina Faculty of Mechanical Engineering, Slovak Republic
39 Anouar Hallioui INTI International University, Malaysia
40 Adam Hamrol Mechanical Engineering, Poznan University of Technology, Poland
41 ni luh putu hariastuti itats, Indonesia
42 Paula Heliodoro, Polytechnic Institute of Setubal, Portugal
43 Vitalii Ivanov Department of Manufacturing Engineering, Machines and Tools, Sumy State University, Ukraine
44 Ali Jaboob Dhofar University, Oman
45 Zamberi Jamaludin Universiti Teknikal Malaysia Melaka, Malaysia
46 Izabela Jonek-Kowalska, Wydział Organizacji i Zarządzania Politechnika Śląska, Poland
47 Satishbabu ACE India
48 Prasad Kanaka Institute of Industrial Relations and Human Resource Development, India
49 Anna Karwasz Poznan University of Technology, Poland
50 Waldemar Karwowski University of Central Florida, United States
51 Osmo Kauppila University of Oulu, Finland
52 Tauno Kekale Merinova Technology Centre, Finland
53 Mahmoud Khedr Faculty of Engineering at Shoubra, Benha University, Cairo, Egypt, Egypt
54 Peter Kostal Department of Production Systems, Metrology and Asembly, Slovenská Technická Univerzita V Bratislave, Faculty of Material Science and Technology, Slovak Republic
55 Boris Kostow University of Angela Kyncheva in Ruse, Bulgaria
56 Martin Krajčovič, University of Žilina, Faculty of Mechanical Engineering, Slovak Republic
57 Caroline  Kristian Uppsala University, Sweden
58 Robert Kucęba Wydział Zarządzania, Politechnika Częstochowska, Poland
59 Agnieszka Kujawińska Poznan University of Technology
60 Edyta Kulej-Dudek Politechnika Częstochowska, Poland
61 Bhakaporn Kuljirundhorn Foxford University, Canada
62 Rajeev Kumar Doon University, India
63 Sławomir Kłos Institute of Mechanical Engineering, University of Zielona Góra, Poland
64 Yu Lee National Tsing Hua University, Taiwan
65 Anna Lewandowska-Ciszek Department of Logistics, Poznań University of Economics and Business, Poland
66 Wojciech Lewicki West Pomeranian University of Technology in Szczecin, Poland
67 Tetiana Likhouzova National Technical University of Ukraine, “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine
68 Damjan Maletič University of Maribor, Faculty of Organizational Sciences, Slovenia
69 Marcela Malindzakova Technical University, Slovak Republic
70 Ildiko Mankova Technical University of Košice, Slovakia
71 Arnaud  Marcelline University of Nantes, France
72 Józef Matuszek University of Bielsko-Biała, Poland
73 Marcin Matuszny Department of Production Engineering, Faculty of Mechanical Engineering and Computer Science, University of Bielsko-Biala, ul. Willowa 2, 43-300 Bielsko-Biała
74 Giovanni Mazzuto Università Politecnica Delle Marche, Italy
75 Tomasz Małkus Uniwersytet Ekonomiczny w Krakowie, Katedra Procesu Zarządzania, Poland, Poland
76 Rafał Michalski Katedra Systemów Zarządzania i Rozwoju Organizacji, Politechnika Wrocławska, Poland
77 Jerzy Mikulik AGH University of Krakow, Poland
78 Rami Mokao MIS - Management Information Systems, HIAST, Syria
79 Norsyahida Mokhtar International Islamic University Malaysia, Malaysia
80 Ig. Jaka Mulyana Industrial Engineering, Widya Mandala Surabaya Catholic University, Indonesia
81 Nor Hasrul Akhmal Ngadiman School of Mechanical Engineering, Universiti Teknologi Malaysia, Malaysia
82 Duc Duy Nguyen Department of Industrial Systems Engineering, Ho Chi Minh Technology University (HCMUT), Viet Nam
83 fernando Nino Polytechnic University of San Luis Potos, Mexico
84 Filscha Nurprihatin Sampoerna University, Indonesia
85 Rebecca Oliver Stockton University, United States
86 Anita Pavlenko Kryvyi Rih State University of Economics and Technology, Ukraine
87 Aleksandar Pesic, MB University, Faculty of Business and Law, Belgrade, Serbia, Serbia
88 Huy Phan Education Technology University, Vietnam, Viet Nam
89 Anna Piekarczyk Poznan School of Logistics (WSL), Poland
90 Alin Pop University of Oradea, Romania
91 Humiras Purba Industrial Engineering, Associate Professor, Universitas Mercu Buana, Jakarta, Indonesia, Indonesia
92 Tengku nur Azila Raja Mamat Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia
93 Silvijo  Renato University of Rijeka, Croatia
94 Piotr Rogala Department of Quality and Environmental Management, Wroclaw University of Economics and Business, Poland
95 Michał Rogalewicz, Faculty of Mechanical Engineering, Poznan University of Technology, Poland
96 Izabela Rojek Institute of Computer Science, Kazimierz Wielki University, Poland
97 Adam Sadowski Katedra Strategii i Zarządzania Wartością Przedsiębiorstwa, Uniwersytet Łódzki, Poland
98 Mansia Sadyrova Al-Farabi Kazakh National University, Kazakhstan
99 Nadia Saeed University of the Punjab, Pakistan
100 Sebastian Saniuk Uniwersytet Zielonogórski, Poland
101 Krzysztof Santarek Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, Poland
102 shankar sehgal Panjab University Chandigarh, India
103 Piotr Senkus University of Warsaw, Poland
104 Jarosław Sęp Politechnika Rzeszowska, Wydział Budowy Maszyn i Lotnictwa, Poland
105 Robert Sika Faculty of Mechanical Engineering and Management, Institute of Materials Technology, Poland
106 Dariusz Sobotkiewicz Instytut Nauk o Zarządzaniu i Jakości, Uniwersytet Zielonogórski, Poland
107 Beata Starzyńska Poznan University of Technology
108 Klaudia Tomaszewska Faculty of Management Engineering, Bialystok University of Technology, Poland
109 Stefan Trzcielinski Poznan University of Technology, Poland
110 Cang Vo Binh Duong University, Viet Nam
111 Somporn Vongpeang Faculty of Technical Education, Rajamangala University of Technology Thanyaburi, Thailand
112 Jaroslav Vrchota University of South Bohemia České Budějovice, Faculty of Economics, Czech Republic
113 Gerhard-Wilhelm Weber Poznań University of Technology, Poland
114 Ewa Więcek-Janka Wydział Inżynierii Zarządzania, Politechnika Poznańska, Poland
115 Linda Winters Czech University of Life Sciences, Czech Republic
116 Zbigniew Wisniewski Lodz University of Technology, Poland
117 Piotr Wróblewski Faculty of Engineering, University of Technology and Economics H. Chodkowska in Warsaw, Poland
118 Iseul  Young Hanyang University, Korea (South)
119 Chong Zhan Hubei University, China
120 Sylwia Łęgowik-Świącik Czestochowa University of Technology Poland, Poland


2025
No. Name Surname Affiliation
1 akshat gaurav akshat Asia University, Taiwan
2 luma Al-kindi University of Technology, Iraq
3 Hind Ali University of Technology, Iraq
4 Katarzyna Antosz Rzeszow University of Technology, Poland
5 Gilmar Batalha Universidade de Sao PauloUniv Sao Paulo, Mech Engn Dept, Escola Politecn, Sao Paulo, SP, Brazil, Brazil
6 Lucia Bednarova Technical University of Kosice, Slovak Republic
7 Anna Burduk Wrocław University of Science and Technology, Poland
8 Danylo Cherevatskyi Institute of Industrial Economics of NAS of Ukraine: Kiev, UA, Ukraine
9 Dorota Czarnecka-Komorowska Faculty of Mechanical Engineering, Poznan University of Technology, Poland
10 SUGANYA Devi National Institute of Technology,Silchar, India
11 Jacek Diakun Poznan University of Technology, Poland
12 Milan Edl University of West Bohemia, Czech Republic
13 João Furtado Santa Cruz do Sul University, Brazil
14 Bożena Gajdzik "Politechnika Śląska Wydział Inżynierii Materiałowej Katedra Informatyki Przemysłowej, Poland"
15 Mose Gallo Materials and Industrial Production Engineering, University of Napoli Federico, Italy
16 Remigiusz Gawlik Department of Public Management, Krakow University of Economics (KUE), Poland
17 Raja Reddy GNV University of Saskatchewan, Canada
18 Arkadiusz Gola Department of Production Informatisation and Robotisation, Lublin University of Technology,Poland
19 Alireza Goli Department of industrial engineering, Yazd university, Yazd, Iran Iran, Iran
20 Cristian Gómez Universidad Nacional de Colombia, Colombia
21 José-Armando HIDALGO CRESPO ENSAM, Spain
22 Magdalena HRYB Faculty of Mechanical Engineering, Poznan University of Technology, Poland
23 Katarzyna Hys Opole University of Technology, Poland
24 Izabela Jonek-Kowalska "Wydział Organizacji i Zarządzania Politechnika Śląska, Poland"
25 Amirhossein Karamoozian, University of Chinese Academy of Sciences, China
26 Anna Karwasz Poznan University of Technology, Poland
27 khaoula khlie Liwa college, Morocco
28 Jerzy Kisilowski
29 Peter Kostal, Slovenská Technická Univerzita V Bratislave, Faculty of Material Science and Technology, Slovak Republic
30 Herbert Kotzab Institute for Logistics and Supply Chain Management, University of Bremen, Germany
31 Martin Krajčovič University of Žilina, Faculty of Mechanical Engineering, Slovak Republic
32 Krzysztof Krystosiak Toronto Metropolitan University, Graphic Communications Management, Canada
33 Wiesław Kuczko Poznan University of Technology, Poland
34 Agnieszka Kujawińska Poznan University of Technology, Poland
35 Edyta Kulej-Dudek Politechnika Częstochowska, Poland
36 Anup Kumar Inst Management Technol NagpurInst Management Technol Nagpur, Nagpur, Maharashtra, India, India
37 Sławomir Kłos Institute of Mechanical Engineering, University of Zielona Góra, Poland
38 Quynh Le Song Thanh Ho Chi Minh Technology University, Viet Nam
39 Yu Lee National Tsing Hua University, Taiwan
40 Stanisław Legutko Faculty of Mechanical Engineering, Poznan University of Technology, Poznan, Poland, Poland
41 Anna Lewandowska-Ciszek Department of Logistics, Poznań University of Economics and Business, Poland
42 José Machado University of Minho · School of Engineering, Portugal
43 Damjan Maletič University of Maribor, Faculty of Organizational Sciences, Slovenia
44 Marcela Malindzakova Technical University, Slovak Republic
45 Tomasz Malkus Department of Management Process, Cracow University of Economics, Poland
46 Mengistu Manaye, Kombolcha Institute of Technology, Wollo University, Ethiopia, Ethiopia
47 Marcin Matuszny, Faculty of Mechanical Engineering and Computer Science, University of Bielsko-Biala, Poland
48 Tomasz Małkus, Uniwersytet Ekonomiczny w Krakowie, Katedra Procesu Zarządzania, Poland, Poland
49 Rami Mokao MIS - Management Information Systems, HIAST, Syria
50 Beata Mrugalska Poznan University of Technology, Poland
51 Ig. Jaka Mulyana Industrial Engineering, Widya Mandala Surabaya Catholic University, Indonesia
52 fernando Nino Polytechnic University of San Luis Potos, Mexico
53 Shimon Nof Purdue University, United States
54 Hana Pacaiová KLI, Faculty of Mechanical Engineering, Faculty of Aeronautics, Technical University of Košice, Slovak Republic
55 Arun Kiran Pal Printing Engineering Department, Jadavpur University, India
56 Michal Patak University of Pardubice, Czech Republic
57 Ivan Pavlenko Department of General Mechanics and Machine Dynamics, Sumy State University, Ukraine
58 Miriam Pekarcikova Department of industrial and digital engineering, Technical University of Košice, Faculty of Mechanical Engineering, Slovak Republic
59 Alin Pop University of Oradea, Romania
60 Praveen Prabhu School of Engineering and Technology, Shivaji University, Kolhapur., India
61 Humiras Purba Industrial Engineering, Associate Professor, Universitas Mercu Buana, Jakarta, Indonesia, Indonesia
62 Paulina Rewers Faculty of Mechanical Engineering, Poznań University of Technology, Poland
63 Michał Rogalewicz Division of Production Engineering, Institute of Materials Technology, Faculty of Mechanical Engineering, Poznan University of Technology, Poland
64 Izabela Rojek Institute of Computer Science, Kazimierz Wielki University, Poland
65 David Romero Tecnológico de Monterrey, Mexico
66 Adam Sadowski Katedra Strategii i Zarządzania Wartością Przedsiębiorstwa, Uniwersytet Łódzki, Poland
67 Abdu Salam Abdul Wali Khan Univ MardanAbdul Wali Khan Univ Mardan, Dept Comp Sci, Mardan 23200, Pakistan, Pakistan
68 fernando sampaio KMITL, Brazil
69 Sebastian Saniuk Uniwersytet Zielonogórski, Poland
70 Iman Sharaf "Higher Technological Institute - Egypt Higher Technol Inst, Dept Basic Sci, Cairo, Egypt, Egypt"
71 Robert Sika Faculty of Mechanical Engineering and Management, Institute of Materials Technology, Poland
72 Beata Starzyńska Poznan University of Technology
73 Robert Ulewicz Politechnika Częstochowska, Poland
74 Wiesław Urban Politechnika Białostocka, Poland
75 Cang Vo Binh Duong University, Viet Nam
76 Jaroslav Vrchota University of South Bohemia České Budějovice, Czech Republic
77 Ewa Więcek-Janka Wydział Inżynierii Zarządzania, Politechnika Poznańska, Poland
78 Sylwia Łęgowik-Świącik Czestochowa University of Technology Poland, Poland

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