Management and Production Engineering Review

Content

Management and Production Engineering Review | 2021 | vol. 12 | No 1

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Abstract

To increase their competitive advantage in turbulent marketplaces, contemporary manufacturers must show determination in seeking ways to: fulfill buyer orders with quality merchandise; meet deadlines; handle unexpected production disruptions; and lower the total relevant expense. To tackle the abovementioned challenges, this study explores an economic manufacturing quantity (EMQ) model with machine failure, overtime, and rework/disposal of nonconforming items; the goal is to find the best fabrication uptime that minimizes total relevant expenses. Specifically, we consider a production unit with overtime capacity as an operational feature that is linked to higher unit and setup costs. Further, its EMQ-based process is subject to random nonconforming items and failure rates. Extra screening separates the reworkable nonconforming items from scrap, and the rework is executed at the end of each cycle of regular fabrication. The failures follow a Poisson distribution, and a machine repair task starts as soon as a failure occurs; the fabrication of the lot that was interrupted resumes after the repair has been carried out. A decision model is built to capture the characteristics of the problem. Mathematical and optimization processes help in determining the optimal fabrication uptime. A numerical example not only illustrates the applicability of the research outcomes, but also reveals a diverse set of information about the individual or joint influences of deviations in mean-time-to-failure, overtime factors, and rework/disposal ratios linked to nonconforming rates related to the optimal replenishment uptime, total operating expenses, and various cost contributors; this facilitates better decision making.
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Authors and Affiliations

Singa Wang Chiu
1
Tiffany Chiu
2
Yuan-Shyi Peter Chiu
3
Hong-Dar Lin
3

  1. Faculty of Business Administration, Chaoyang University of Technology, Taichung City 413, Taiwan
  2. Faculty of Anisfield School of Business, Ramapo College of New Jersey, Mahwah, NJ 07430, USA
  3. Faculty of Industrial Engineering & Management, Chaoyang University of Technology, Taichung City 413, Taiwan
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Abstract

Artificial neural network (ANN), a Computational tool that is frequently applied in the modeling and simulation of manufacturing processes. The emerging forming technique of sheet metal which is typically called single point incremental forming (SPIF) comes into the map and the research interest towards its technological parameters. The surface quality of the end product is a major issue in SPIF, which is more critical with the hard metals. The part of the brass metal is demanded in many industrial uses because of its high load-carrying capacity and its wear resistance property. Considering the industrial interest and demand of the brass metal products, the present study is done with the SPIF experiment on calamine brass Cu67Zn33 followed by an ANN analysis for predicting the absolute surface roughness. The modeling result shows a close agreement with the measured data. The minimum and maximum errors are found in experiment 3 and experiment 7 respectively. The error of predicted roughness is found in the range of –30.87 to 20.23 and the overall coefficient of performance of ANN modeling is 0.947 which is quite acceptable.
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Authors and Affiliations

Manish Oraon
1
Vinay Sharma
1

  1. Birla Institute of Technology, Faculty of Production Engineering, India
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Abstract

The presence of the spare parts stock is a necessity to ensure the continuity of services. The supply of spare parts is a special case of the global supply chain. The main objective of our research is to propose a global spare parts management approach which allows decision makers to determine the essential points in stock management. Thus, it is important for the stock manager to evaluate the system considered from time to time based on performance indicators. Some of these indicators are presented in the form of a dashboard. The presentation of this chapter chronologically traces the progress of our research work. In the first part, we present the work related to the forecast of spare parts needs through parametric and statistical methods as well as a Bayesian modelling of demand forecasting. To measure the appreciation of the supply of spare parts inventory, the second part focuses on work related to the evaluation of the performance of the spare parts system. Thus, we concretize the link between the management of spare parts and maintenance in the third part, more precisely, in the performance evaluation of the joint -management of spare parts and maintenance, in order to visualize the influence of parameters on the system. In the last section of this chapter, we will present the metaheuristic methods and their use in the management of spare parts and maintenance and make an analysis on work done in the literature.
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Authors and Affiliations

Oumaima Bounou
1
Abdellah El Barkany
1
Ahmed El Biyaali
1

  1. Mechanical Engineering Laboratory, Faculty of Science and Techniques, Morocco
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Abstract

Industry 4.0 (I4) as a concept offers powerful opportunities for many businesses. The set of Industry 4.0 technologies is still discussed, and boundaries are not perfectly clear. However, implementation of Industry 4.0 concept becomes strategic principle, and necessary condition for succeeding on turbulent markets. Radio Frequency Identification (RFID) was used before I4 emerged. However, it should be treated as its important part and even enabler. The question arises how adoption of RFID was impacted by I4 paradigm. Therefore, to answer this question a set of technology management tools was selected and applied to forecast RFID potential development in forthcoming years. Moreover, case studies were conducted for technology management tools and their applications for RFID for qualitative discussion of its relevance. It aimed to prove that existing toolset should be applied for modern technologies related to I4. Tools were proven to be necessary and successful. However, some specific challenges were observed and discussed.
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Authors and Affiliations

Bartlomiej Gladysz
1
Donatella Corti
2
Elias Montini
2

  1. Warsaw University of Technology, Institute of Production Systems Organization, Warsaw, Poland
  2. University of Applied Science and Arts of Southern Switzerland, Department of Innovative Technologies
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Abstract

As the corporate culture and re/setting of employer – employee relations is crucial due to changes in workplace due to impact of COVID-19, this article aims to identify types of organizational culture, and to find impact on the implementation of HR activities and employer branding, including classification of organizations by their defined strategies. A model of organizational culture, including its systematic relationships, is proposed and tested using a sample of 402 organizations across sectors operating in the Czech Republic as a characteristic economy in Central Eastern European region. This model includes different dimensions of internal brand management and manifestations of organizational culture. Data are analyzed using bivariate and multivariate statistics. Identification of a suitable type of organizational culture leads towards successful employer branding and work engagement; brand identification and communication directly raise positive perception of organizational culture. Three major areas of use of organizational culture and branding have been identified: re-setting of personnel processes depending on the change of organization’s size, on the decline in labor productivity and on organizational mergers, changes in scope of business and in market position. The results suggest that orientation on employee engagement is a better predictor of (positive) organizational culture than increase in productivity. Furthermore, the results explain supportive roles of organizational culture towards customers and employees. The results extend theory by empirical analysis of organizational culture and internal brand management from the employers’ perspective.
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Authors and Affiliations

Hana Urbancová
1
Lucie Depoo
2

  1. University of Economics and Management, Department of Human Resources
  2. University of Economics and Management, Department of Management
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Abstract

The industrial revolution taking place since the 18th century has brought the global economies to the stage of mass production, mass industrialization and spreading ideas connected with its efficiency. The most famous of its kind is Fordism and its modern variations called PostFordism or Neo-Fordism. We can still see traditional way of producing things in some parts of the world, and the leading economies are using Ford’s ideas or the modifications of the Ford’s concepts. But there is a question about the place of these models in the modern economy, especially because mass-production causes mass-waste and modern societies has woken up to the reality of the global pollution, climate change or just the simple fact that the amount of the raw materials is limited. The social mood is slowly changing so there should be a change to the way we produce and consume things as well. There is a question: can we proceed within existing models or should we think outside the box so we can invent more suitable way of looking at efficiency and effectiveness. The objective of this paper is to contribute to the discussion about the future of how are we going to produce things. It is based on the literature review considering Fordism and its variations, Product Life Cycle facing issues like pollution, massive waste and changes in modern economy, as well as on the case study of implementing waste reduction activities in the product’ design phase in the industrial plant based in one of the EU countries – Poland.
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Authors and Affiliations

Mariusz Bednarek
1 2
Aneta Parkes
3

  1. Wyższa Szkoła Bankowa, Warszawa, Poland
  2. Universidad Autonoma de Chile, Temuco, Chile
  3. Społeczna Akademia Nauk, Łódź, Poland
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Abstract

The market of consumer goods requires nowadays quick response to customer needs. As a consequence, this is transferred to the time restrictions that the semi-finished product manufacturer must meet. Therefore the cost of manufacturing cannot determine how production processes are designed, and the main evaluation function of manufacturing processes is the response time to customers’ orders. One of the ideas for implementing this idea is the QRM (Quick Response Manufacturing) production organization system. The purpose of the research undertaken by the authors was to develop an innovative solution in the field of production structure, allowing for the implementation of the QRM concept in a Contract Manufacturer, which realizes its tasks according to engineering-to-order (ETO) system in conditions defined as High Mix, Low Volume, High Complexity. The object of the research was to select appropriate methods for grouping products assuming that certain operations will be carried out in traditional but well-organized technological and/or linear cells. The research was carried out in one of the largest producers of sheet metal components in Europe. Pre-completed groupings for data obtained from the company had indicated that – among the classical methods – the best results had been given by the following methods: King’s Algorithm (otherwise called: Binary Ordering, Rank Order Clustering), k-means, and Kohonen’s neural networks. The results of the tests and preliminary simulations based on the data from the company proved that the implementation of the QRM concept does not have to be associated with the absolute formation of multi-purpose cells. It turned out that the effect of reducing the response time to customer needs can be obtained by using hybrid structures that combine solutions characteristic of cellular systems with traditional systems such as a technological, linear, or mixed structure. However, this requires the application of technological solutions with the highest level of organization.
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Authors and Affiliations

Jerzy Duda
1
Andrzej Macioł
2
Stanisław Jedrusik
2
Bogdan Rebiasz
2
A. Stawowy
ORCID: ORCID
Monika Sopinska-Lenart
3
Adam Stawowy
2

  1. AGH University of Science and Technology, Faculty of Management, Kraków, Poland
  2. AGH University of Science and Technology, Faculty of Management, Kraków, Poland
  3. Addit Sp. z o.o., Wegrow, Poland
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Abstract

Commercialization processes are modeled and analyzed from the point of view of the implementation of activities under particular stages. These issues are the subject of many studies and analyzes, which is why the extensive literature is available on this subject. Technology valuation at various stages of the commercialization process is a separate issue. Such valuation is prepared in most cases by consulting companies for determining the price in the buying and selling processes. These valuations use known methods also used in other cases, e.g., real estate valuation. The work carried out presents the author’s concept of the commercialization process model, taking into account the costs and value of the technology at various stages of the product life cycle. The model uses a stochastic approach to determine future revenues and costs, which allows estimating the value of the technology by or in determining the probability of assessment validity. The proposed stochastic approach greatly increases the chances of using the presented solutions in practical activities related to technology valuation for the purposes of purchase and sale transactions.
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Authors and Affiliations

Bozena Kaczmarska
1
Wacław Gierulski
1
ORCID: ORCID
Josef Zajac
2
Anton Bittner
2
Wacław Gierulski
1

  1. Kielce University of Technology, Poland
  2. Technical University of Kosice, Slovakia
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Abstract

Industry 4.0 promises to make manufacturing processes more efficient using modern technologies like cyber-physical systems, internet of things, cloud computing and big data analytics. Lean Management (LM) is one of the most widely applied business strategies in recent decades. Thus, implementing Industry 4.0 mostly means integrating technologies in companies that already operate according to LM. However, due to the novelty of the topic, research on how LM and Industry 4.0 can be integrated is still under development. This paper explores the synergic relationship between these two domains by identifying six examples of real cases that address LM-Industry 4.0 integration in the extant literature. The goal is to make explicit the best practices that are being implemented by six distinct industrial sectors
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Authors and Affiliations

Beatrice Paiva Santos
1
Daisy Valle Enrique
1 2
Vinicius B.P. Maciel
1
Tânia Miranda Lima
1
Fernando Charrua-Santos
1
Renata Walczak
3

  1. Electromechanical Department, C-MAST, University of Beira Interior, Covilhã, Portugal
  2. Industrial Engineering Department, Federal University of Rio Grande do Sul, Brazil
  3. University of Technology, Warsaw, Poland
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Abstract

So far, numerous studies have been published on the selection of appropriate maintenance tactics based on some factors affecting them such as time, cost, and risk. This paper aims to develop the TRIZ contradiction matrix by explaining the dimensions and components of each of the following Reactive maintenance tactics. The related findings of previous studies were analyzed by adopting “Rousseau and Sandoski” seven-step method to identify and extract the relationships between TRIZ principles and Reactive maintenance tactics. Thereafter, 5 Reactive maintenance tactics were replaced TRIZ’s 40 principles in the TRIZ contradiction matrix. Finally, the ANP method were used to extract and prioritize the appropriate Reactive maintenance tactics. The proposed matrix in this research was used in the desalination section of one of the oil companies to select on the appropriate Reactive maintenance tactics. The results of this research is useful for managers and maintenance specialists of units in making decisions to provide appropriate Reactive maintenance tactics for the desired equipment.
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Authors and Affiliations

Mohammad Amin Mortazavi
1
Atefeh Amindoust
1
Arash Shahin
2
Mehdi Karbasian
3

  1. Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
  2. Department of Management, University of Isfahan, Isfahan, Iran
  3. Department of Industrial Engineering, Malek-Ashtar University of Technology, Isfahan, Iran
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Abstract

Major manufactures are moving towards a sustainability goal. This paper introduces the results of collaboration with the leading company in the packaging and advertising industry in Germany and Poland. The problem addresses the manufacturing planning problem in terms of minimizing the total cost of production. The challenge was to bring a new production planning method into cardboard manufacturing and paper processing which minimizes waste, improves the return of expenses, and automates daily processes heavily dependent on the production planners’ experience. The authors developed a module that minimizes the total cost, which reduces the overproduction and is used by the company’s manufacturing planning team. The proposed approach incorporates planning allowances rules to compromise the manufacturing requirements and production cost minimization.
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Authors and Affiliations

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

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

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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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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.
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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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