Management and Production Engineering Review

Content

Management and Production Engineering Review | 2022 | vol. 13 | No. 3

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Abstract

The main purpose of the paper is to identify and analyse a state of exploratory motivating factors in terms of lean management as the instrument of a policy of human resource management in the face of COVID-19 pandemic implemented in service companies. The main question is: if the motivation system used in the companies works out up against the unpredictable situation such as COVID-19 pandemic? The secondary purpose of the paper is to recognise relations and dependencies between these factors, and the question is: what factors have the strongest or the weakest relations with Lean Staff Management (LSM) tools? This research designed based on interview was conducted due to the lack of existing studies on the current status of motivating factors in terms of lean management tools in two service companies (case studies) in the light of COVID-19. The results show that factors influencing work efficiency in a dominating manner were, primarily, financial incentives (almost 21%), communications (around 21%), and workplace atmosphere (almost 18%). The paper investigates also the benefits and concerns of implementing LSM in service companies during the pandemic. This research might help the service organization’s management to identify the employees‘ problems to implement more effective lean services.
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Authors and Affiliations

Patrycja Żegleń
1
Aldona Kluczek
2
Daniela Matusikova
3

  1. University of Rzeszów, Poland
  2. Warsaw University of Technology, Poland
  3. University of Presov, Slovakia
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Abstract

The automotive industry is characterized by a high degree of uncertainty. Companies are facing the challenge of producing different systems simultaneously. Additionally, the global quantity of electric vehicles is also expected to increase significantly. This results in the following capability to remain competitive: Effective and efficient adaptions of production systems to model variations and volume increases. While flexible production is identified as the most promising concept, defining the actual flexibility level of included production resources is essential for its proper realization. A literature review on existing flexibility assessment approaches revealed their emphasis on high-level enablers and limited practical applicability in the automotive industry. In contrast, focusing the assessment on single workstations supports the selection of appropriate production resources. Therefore, a simple and structured standard procedure for a production resource flexibility assessment was developed. This theoretical construct was subsequently complemented with practical insights through its application on two real-life case studies within one automotive engineering company. Summarizing and discussing the findings in combination with a conclusion completed this paper.
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Authors and Affiliations

Oliver Moerth-Teo
1
Gernot Schlögl
2
Muaaz Abdul-Hadi
3
Markus Brillinger
3
Martin Weinzerl
4
Christian Ramsauer
1

  1. Institue of Innovation and Industrial Management, Graz University of Technology, Austria
  2. Institue of Production Engineering, Graz University of Technology, Austria
  3. Pro2Future GmbH, Austria
  4. AVL List GmbH, Austria
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Abstract

The paper addresses a managerial problem related to ensuring cybersecurity of information and knowledge resources in production enterprises interested in the implementation of INDUSTRY 4.0 technologies. The material presented shows the results of experimental research of a qualitative nature, using two expert inventive methods: brain-netting and a fuzzy formula of inference. The experts' competences included the following three variants of the industrial application of the INDUSTRY 4.0 concept: (1) high production volumes achieved using a dedicated and fully robotic production line (2) the manufacture of short, personalized series of products through universal production cells, and (3) the manufacture of specialized unit products for individual customers. The Google Forms software was used to collect these expert opinions. The conclusions of the research carried out using the brain-netting method point to nine variants of the cybersecurity strategy of IT networks and knowledge base resources in manufacturing enterprises represented by the experts. The results of the research using the fuzzy formula of inference are numerically and situationally defined relations linking the above-mentioned nine strategies with five types of cyber-attacks. The summary record of these relations as the basis for managerial cybersecurity recommendations has a matrix form.
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Authors and Affiliations

Leszek Pacholski
1
ORCID: ORCID

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

In many companies, along with the economic development, the use of integrated management systems is becoming more and more common, which are subject to evolution in terms of, inter alia, offered functions and new user requirements. The main purpose of this paper is to compare selected ERP (Enterprise Resource Planning) systems in the field of production planning and control on the example of the automotive industry. The paper presents the contemporary functioning of the automotive industry against the background of issues related to the integrated management systems used in them. The research part presents the proprietary methodology for the assessment of IT systems used in the automotive industry, which included a user survey. The obtained score allowed to indicate the optimal ERP class system supporting production planning and control.
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Authors and Affiliations

Robert Sika
1
ORCID: ORCID
Oliwia Wojtala
2
Jakub Hajkowski
1
ORCID: ORCID

  1. Poznan University of Technology, Faculty of Mechanical Engineering, Poland
  2. Poznan, Poland
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Abstract

Industry 4.0 is expected to provide high quality and customized products at lower costs by increasing efficiency, and hence create a competitive advantage in the manufacturing industry. As the emergence of Industry 4.0 is deeply rooted in the past industrial revolutions, Advanced Manufacturing Technologies of Industry 3.0 are the precursors of the latest Industry 4.0 technologies. This study aims to contribute to the understanding of technological evolution of manufacturing industry based on the relationship between the usage levels of Advanced Manufacturing Technologies and Industry 4.0 technologies. To this end, a survey was conducted with Turkish manufacturers to assess and compare their manufacturing technology usage levels. The survey data collected from 424 companies was analyzed by machine learning approach. The results of the study reveal that the implementation level of each Industry 4.0 technology is positively associated with the implementation levels of a set of Advanced Manufacturing Technologies.
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Authors and Affiliations

Tuğba Sari
1

  1. Konya Food and Agriculture University, Department of Management Information Systems, Turkey
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Abstract

This paper proposes the application of the digital numerical control (DNC) technique to connect the smart meter to the inspection system and evaluate the total harmonic distortion (THD) value of power supply voltage in IEEE 519 standard by measuring the system. Experimental design by the Taguchi method is proposed to evaluate the compatibility factors to choose Urethane material as an alternative to SS400 material for roller fabrication at the machining center. Computer vision uses artificial intelligence (AI) technique to identify object iron color in distinguishing black for urethane material and white for SS400 material, color recognition results are evaluated by measuring system, system measurement is locked when the object of identification is white material SS400. Computer vision using AI technology is also used to recognize facial objects and control the layout of machining staff positions according to their respective skills. The results obtained after the study are that the surface scratches in the machining center are reduced from 100% to zero defects and the surface polishing process is eliminated, shortening production lead time, and reducing 2 employees. The total operating cost of the processing line decreased by 5785 USD per year. Minitab 18.0 software uses statistical model analysis, experimental design, and Taguchi technical analysis to evaluate the process and experimentally convert materials for roller production. MATLAB 2022a runs a computer vision model using artificial intelligence (AI) to recognize color objects to classify Urethane and SS400 materials and recognize the faces of people who control employee layout positions according to their respective skills.
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Authors and Affiliations

Minh Ly Duc
1 2
Petr Bilik
2

  1. Faculty of Commerce, Van Lang University, 700000, Vietnam
  2. VSB–Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science, Department ofCybernetics, and Biomedical Engineering, 708 00, Ostrava, Czech Republic
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Abstract

Value Stream Mapping has been a key Lean tool since its publication in 1988, offering a strategic view on the reconfiguration of an organization’s processes to reduce overall lead time. It has since been used in many different domains beyond (car) manufacturing. However, the potential offered by its concise representation of both material flow and its controlling information flow seems to have been largely underused. Most literature reports on VSM in the context of waste detection and local improvements. VSM also supports redesigning the material flow (even on a supply chain level) towards (pure) pull systems. However, it fails to adequately give guidance on how to gradually evolve towards this ultimate ideal state. This paper wants to offer a significant contribution to practitioners on how to use VSM to bridge this gap. Another key challenge that remains largely unpublished is how to adapt the planning systems accordingly at each reconfiguration of the material flow. This paper presents extensions to the basic VSM tool to meet these challenges. It includes a more comprehensive 5-level hierarchy that allows to position most lean flow-related techniques. It also extends the basic “door-to-door” VSM with new symbols to accommodate these techniques into the map. Finally, it introduces a new set of 13 questions to support redesigning not only the material flow, but also the information flow. The resulting richer future state maps better support the gradual evolution towards a leaner future shop floor, as illustrated with an example.
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Authors and Affiliations

Hendrik Van Landeghem
1 2
ORCID: ORCID
Johannes Cottyn
1 2

  1. Department of Industrial Systems Engineering and Product Design, Ghent University, Gent-Zwijnaarde, Belgium
  2. Industrial Systems Engineering (ISyE), Flanders Make vzw, Kortrijk, Belgium
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Abstract

Lean thinking and Industry 4.0 have been broadly investigated in recent years in intelligent manufacturing. Lean Production is still one of the most efficient industrial solutions in business and research, despite being implemented for a long time. On the other hand, Industry 4.0 has been introduced referring to the fourth industrial revolution. This study aims to analyze the combination of both Industry 4.0 and Lean production practices through a systematic literature review from a Lean Automation perspective. In this field, 189 articles are examined using VOSviewer for cluster analysis. Then, a more detailed analysis is provided to explore how Industry 4.0 and Lean techniques are integrated from a practical perspective. Results highlighted Big Data Analysis and Value Stream Mapping as the most common techniques, also emphasizing a growing trend toward new publications. Nevertheless, few practical applications are identified in the literature highlighting six gaps in the correlation of LA practices.
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Authors and Affiliations

Laura Lucantoni
1
Sara Antomarioni
1
Filippo Emanuele Ciarapica
1
Maurizio Bevilacqua
1

  1. Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica Delle Marche, Italy
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Abstract

Abstract Meeting quality characteristics of products and processes is an important issue for customer satisfaction and business competitiveness. It is necessary to integrate new techniques and tools that improve and complement traditional process variables analysis. This paper proposes a new methodological approach to analyze process quality control variables using Fuzzy Cognitive Maps. Application of the methodology in the production process of carbonated beverages allowed identifying process variables with the greatest influence on finished product quality. The process variables with the greatest impact on carbon dioxide content in the beverage were the beverage temperature in the filler, the carbo-cooler pressure, and the filler pressure.
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Authors and Affiliations

Juan Cogollo-Florez
1
ORCID: ORCID
Orfani Valencia-Mena
1
ORCID: ORCID

  1. Department of Quality and Production, Instituto Tecnológico Metropolitano – ITM, Colombia
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Abstract

The current market situation shows that enterprises are still struggling to digitize their business through the integration of the Internet of Things (IoT), artificial intelligence (AI), cloud technologies and other more advanced technologies, but the fifth industrial revolution is knocking on the door. This article deals with the analysis and evaluation of the impact of Industry 5.0 on entrepreneurs. Industry 4.0 analysis provides results based on interviews with practitioners as well as sales representatives. The main part of the article focuses on the business situation, where the goal was to identify existing gaps along with opportunities and threats. This analysis also describes the best way how to transform in times of the next industrial revolution. Study addresses the approach of integrating human workers in the supply chain in cooperation with automated processes. The purpose of this study is to confirm or refute whether companies are ready for another industrial revolution.
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Authors and Affiliations

Laura Lachvajderová
1
ORCID: ORCID
Jaroslava Kádárová
1
ORCID: ORCID

  1. Technical University of Košice, Department of Industrial and Digital Engineering, Slovakia
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Abstract

The optimal decision regarding the place of production is an essential, sometimes determining factor of its effectiveness. The main drawback in substantiating the optimal location of production is the lack of a system approach to accounting in the analysis of potential sales markets. Orientation, when justifying the optimal location of production, only to some particular sales market (and orientation to specific sales markets is necessary both in terms of taking into account the costs of moving the benefit from the place of production to the places of consumption, and in terms of production capacity, since it depends unit cost of production) is erroneous because it does not take into account many other competitive options. The article develops a system approach to rationale optimal locations and production capacity, based on a comparison of combinations of locally optimal places, the total production capacity of which is equal to the total (system) demand. The variant of combinations of locally optimal places with minimal total costs is systemically optimal. The result of solving the problem will be information about 4 parameters of the production of benefit: “where?” (in what places), “how much?” (in each of these places), “how?” (with what technology in each of these places), “for whom?” (sales markets for each of these places). The system approach proposed in the article to rationale the optimal location of the production of a single benefit can be adapted to a more complex situation, when the optimal location of the production of several benefits is justified at the same time. Further research is promising in the direction of a clearer determination of the boundaries of the space of possible location of production, as well as in the direction of studying the possibility of aggregating potential sales markets.
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Authors and Affiliations

Jerzy Stadnicki
1
Andrii Terebukh
2

  1. Faculty of Management and Computer Modelling, Kielce University of Technology, Poland
  2. Department of Tourism, Lviv Polytechnic National University, Ukraine
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Abstract

Sustainability manufacturing is crucial in many aspects in terms of environmental impact. It concerns the consumption of energy, raw materials and materials, as well as the emission of harmful substances and waste. The implementation of sustainability manufacturing requires many actions at various levels, including strategic, tactical and operational ones. In order to implement measures aimed at minimizing the negative impact of the company on the environment, employees’ competencies are needed. The article presents preliminary research on key green competencies for sustainability companies. The research was carried out in the form of individual interviews with medium and large production companies. The result of the research is the division of competencies (knowledge, skills and attitudes) into three stages of the organization’s development, indicating the key competencies for each stage of the development of sustainability management.
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Authors and Affiliations

Magdalena Graczyk-Kucharska
1

  1. Institute of Safety and Quality Engineering, Department of Marketing and Organization Development, PoznanUniversity of Technology, Poland

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 (office@mper.org). 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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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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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.
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 (office@mper.org). 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 (e-mail: office@mper.org) 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

Zahid Hussain Agha Sarhad University of Science and IT Peshawar Pakistan
Mehmet Ali Akinlar Yildiz Technical University Turkey
Zoran Anisic University of Novi Sad, Faculty of Technical Sciences Serbia
Katarzyna Antosz Rzeszow University of Technology Poland
Rajesh As Maharaja Institute of Technology Thandavapura India
Erfan Babaee Tirkolaee Mazandaran University of Science and Technology Iran
Zbigniew Banaszak Koszalin University of Technology Poland
Jolanta Baran Silesian University of Technology Poland
Mariusz Bednarek WSB Warszawa Poland
Srinivasa Murthy Boorla Grupo Antolin Spain
Oumaima Bounou FST-Fez Marocco
Robert Cep VSB-TU OSTRAVA Czech Republic
Fatih Çetin Niğde Ömer Halisdemir University Turkey
Claudiu Cicea Bucharest University of Economic Studies Romania
Pedro Cunha Instituto Politécnico de Setúbal Portugal
Szymon Cyfert Poznań University of Economics and Business Poland
Asta Daunorienė Assoc. prof., Kaunas University of Technology Lithuania
Ahmed Deif Associate Prof. California Polytechnic State University USA
Yuliia Denysenko Sumy State University Ukraine
Jacek Diakun Poznań University of Technology Poland
Ewa Dostatni Poznan University of Technology Poland
Joanna Duda AGH University of Science and Technology Poland
Milan Edl University of West Bohemia Czech Republic
Joanna Ejdys Bialystok University of Technology Poland
Nurprihatin Filscha Department of Industrial Engineering, Universitas Bunda Mulia Indonesia
Adi Fitra Magister Industrial Engineering ,Mercubuana University Indonesia
Mosè Gallo Department of Chemical, Materials and Industrial Production Engineering, University of Napoli Federico II Italy
Józef Gawlik Cracow Univesity of Technology Poland
Andrzej Gessner Poznan University of Technology Poland
Arkadiusz Gola Lublin University of Technology, Poland Poland
Alireza Goli Department of industrial engineering, Yazd university, Yazd, Iran Iran
Błażej Góralski Poznan University of Technology Chair of Production Engineering Poland
Pop Grigore Marian Technical university of Cluj-Napoca Romania
Łukasz Grudzień Poznan University of Technology Poland
Vitalii Ivanov Sumy State University Ukraine
Małgorzata Jasiulewicz-Kaczmarek Poznan University of Technology Poland
Jozef Jurko Technical University in Košice Poland
Oksana Karpenko RUDN University Russia
Anna Karwasz Poznan University of Technology Poland
Sławomir Klos University of Zielona Góra, Institute of Mechanical Engineering Poland
Remigiusz Kozlowski University of Lodz Poland
Stanisław Krzyżaniak Poznań School of Logistics Poland
Anna Lewandowska-Ciszek State University of Applied Sciences in Konin Poland
Jerzy Lewandowski Warsaw University of Technology Poland
Anna Lis Gdańsk University of Technology Poland
Reza Lotfi Department of industrial engineering Yazd University Iran
Sylwia Łęgowik-Świącik Czestochowa University of Technology Poland
Iulian Malcoci PhD, Associate Professor / Mechanical Engineering Moldova
Damjan Maletic University of Maribor, Faculty of Organizational Sciences Slovenia
Paweł Mielcarek Poznań University of Economics and Business Poland
Anna Nagyova Technical University of Kosice Slovakia
Andrei Stefan Nestian Alexandru Ioan Cuza University Iasi, Romania Romania
Filip Osiński Poznan University of Technology Poland
Ivan Pavlenko Sumy State University Ukraine
Dragan Peraković University of Zagreb, Faculty of transport and traffic sciences Croatia
Niles Perera University of Moratuwa Sri Lanka
Jan Pitel Technical University of Kosice, Faculty of Manufacturing Technologies, Slovakia Slovakia
Paulina Rewers Poznan University od Technology Poland
Piotr Rogala Uniwersytet Ekonomiczny we Wrocłąwiu Poland
Izabela Rojek Kazimierz WIelki University Poland
Łukasz Rymaniak Poznan University of Technology Poland
Krzysztof Santarek Politechnika Warszawska Poland
Michał Sąsiadek Uniwersytet Zielonogórski Poland
Shah Rukh Shakeel University of Vaasa Finland Finland
Parveen Sharma Lovely Professional University Phagwara India
Dorota Stadnicka Rzeszow University of Technology Poland
Binod Timilsina University of Vaasa Finland
Justyna Trojanowska Poznan University of Technology Poland
Stefan Trzcielinski Poznan University of Technology, Faculty of Engineering Management Poland
Mariusz Uchroński Wroclaw University of Science and Technology Poland
Nicolae Stelian Ungureanu Technical University of Cluj-Napoca , Romania Romania
Wiesław Urban Politechnika Białostocka Poland
Wiesław Urban Bialystok University of Technology Poland
Gerhard-Wilhelm Weber FEM, PUT Poland
Ewa Więcek-Janka PUT Poland
Marek Wirkus Politechnika Gdańska, Wydział Zarządzenia i Ekonomii Poland
Rika Yunitarini Trunojoyo University Indonesia Indonesia
Jozef Zajac TU Kosice Slovakia
Paweł Zmarzły Kielce University of Technology Poland
Krzysztof Żywicki Poznan University of Technology Poland


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