Management and Production Engineering Review

Content

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

Download PDF Download RIS Download Bibtex

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.
Go to article

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
Download PDF Download RIS Download Bibtex

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.
Go to article

Authors and Affiliations

Manish Oraon
1
Vinay Sharma
1

  1. Birla Institute of Technology, Faculty of Production Engineering, India
Download PDF Download RIS Download Bibtex

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.
Go to article

Authors and Affiliations

Oumaima Bounou
1
Abdellah El Barkany
1
Ahmed El Biyaali
1

  1. Mechanical Engineering Laboratory, Faculty of Science and Techniques, Morocco
Download PDF Download RIS Download Bibtex

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.
Go to article

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
Download PDF Download RIS Download Bibtex

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.
Go to article

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
Download PDF Download RIS Download Bibtex

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.
Go to article

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
Download PDF Download RIS Download Bibtex

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.
Go to article

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
Download PDF Download RIS Download Bibtex

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.
Go to article

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
Download PDF Download RIS Download Bibtex

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
Go to article

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
Download PDF Download RIS Download Bibtex

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.
Go to article

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
Download PDF Download RIS Download Bibtex

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.
Go to article

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

Instructions for authors

REVIEW PROCESS

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

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


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

Guidelines for Authors

Template for Authors





Additional info

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

Publication Ethics Policy

The ethics statements for the journal Management and Production Engineering Review are based on the guidelines of Committee on publication ethics (COPE) and the ELSEVIER publishing ethics resource kit.
For Authors: All articles, published in the journal Management and Production Engineering Review have to comprise a list of references which correspond with the journal’s Instructions to authors for paper preparation. The authors should ensure that they have written entirely original works, and if the authors have used the work and/or words of others that this has been appropriately cited or quoted. All articles are tested using antyplagiarism programme. An author should not in general publish manuscripts describing essentially the same research in more than one journal or primary publication. Submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behaviour and is unacceptable. Authorship should be limited to those who have made a significant contribution to the conception, design, execution, or interpretation of the reported study. The corresponding author should ensure that all co-authors have seen and approved the final version of the paper and have agreed to its submission for publication. All authors should disclose in their manuscript any financial or other substantive conflict of interest that might be construed to influence the results or interpretation of their manuscript. All sources of financial support for the project should be disclosed.
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

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

This page uses 'cookies'. Learn more