Management and Production Engineering Review

Content

Management and Production Engineering Review | 2024 | No 1

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Abstract

The fourth industrial revolution has broadly transformed the manufacturing system. However, this transformation is somewhat lacking in traditional or manual production systems due to the absence of IT infrastructure. Such traditional industries need to have the advantage of real-time control and monitoring. This study has developed economic assembly planning, scheduling, and control for a traditional assembly system. We used the concept of the configurable virtual workstation as the digitalization framework. Then, we employed the decentralized scheduling concept to reduce the computational effort in scheduling the complex product. The implementation result showed that scheduling and planning have transformed the traditional assembly process into intelligent scheduling and control with low digitalization effort
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Authors and Affiliations

Sri RAHARNO
Vina Sari YOSEPHINE
Rachmad HARTONO
Ari SETIAWAN
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Abstract

his study explores the impact of augmented reality (AR) on worker performance in manufacturing contexts through an analysis of case studies extant in the literature. Two specific analyses were conducted to assess the impacts of AR technologies on worker performance in terms of objective and subjective metrics, and in terms of their age, experience with the task and experience with the AR device. Regarding objective metrics, the results showed that the task completion time was reduced for some AR devices (projectors, monitors, tablets, smartphones), whereas the use of the head-mounted display (HMD) increased task-completion time; moreover, the error rate was reduced with any AR device compared with traditional methods. Regarding subjective metrics, the analysis underlined that operator perceived a lower workload with the HMD or the monitor compared with traditional methods. The age of operators did not influence performance, while the operators’ experience allowed for the improvement of human performance.
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Authors and Affiliations

Chiara BELSITO
Chiara FRANCIOSI
Valentina DI PASQUALE
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Abstract

This paper presents a model for evaluating production strategies, policies and methods based on fuzzy set theory. To illustrate the application of a model, the longitudinal case study was carried out in the sector of automotive components and parts production in Serbia. Within the automotive supplier industry, analysis is concentrated on the Cooper Standard company, one of the world’s most prominent component suppliers. The study was conducted with the management team of the Cooper Standard branch in Serbia. Triangular fuzzy numbers are employed to effectively evaluate the critical areas of production management and overall competitiveness over time. The findings of the empirical survey confirmed the usability and usefulness of the proposed approach. Also, the longitudinal character of this case study provided an opportunity to follow the patterns of change over a period of 5 years (2019–2024).
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Authors and Affiliations

Aleksandar PESIC
Duska PESIC
Slavko IVKOVIC
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Abstract

Nowaday, many manufacturing companies are integrating Industry 4.0 technology into their operational processes, particularly those aiming to enhance production operations. However, business decision-makers must remain vigilant about potential risks associated with adopting this technology. These risks include initial financial investments for testing and system installation, managing human resources to operate the new system, and concerns regarding data security. This study proposes designing an Industry 4.0 technology system to augment machining machine operations, leveraging Internet of Things (IoT) devices to facilitate connectivity and data transmission. Additionally, it aims to improve production process monitoring through visual management techniques. The machines under study are semi-automatic and lack operational digitization or expansion capacity. Through research on integrating low-cost Industry 4.0 technology into the production process, this study has achieved an annual reduction in production costs by $9593. Moreover, the defect rate for product length dimensions has plummeted from 54.90% per month to zero defects. The study employs the DMAIC method (Define-Measure-Analysis-Improve-Control) cycle within the Six Sigma methodology to investigate and apply low-cost Industry 4.0 technology to production process enhancement. This combined approach can be customized and applied to various business process improvement models, further enhancing the operation of machining machines originally equipped with Industry 3.0 technology.
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Authors and Affiliations

Do Ngoc Hien
Minh Ly DUC
Tran Duc Tuan
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Abstract

Business Process mapping (BP mapping) is important for a company to identify their activities. Previous research suggests several approaches for process identification and BP mapping, which would be easier if the company had already implemented a computer-based information system. The research presented in this paper has the purpose of providing an alternative method for BP mapping especially for the company that does not implement the computer-based information system. A proposed method is using job description documents that the company had to identify elements needed to perform BP mapping which are actor, process, document, and flow of documents. A Natural Language Process (NLP) which is text mining method is used for mining job documents to identify those elements that exist in each job position. To illustrate the applicability of the proposed method, samples of job descriptions of 15 companies are taken. It shows that the proposed method can be applied.
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Authors and Affiliations

Ririn Diar ASTANTI
Adelia Veneska SWITASARRA
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Abstract

Small and Medium Enterprises SME play a crucial role in the global economy through their contribution in countries economy and creation of employment opportunities, and their success heavily relies on the implementation of efficient manufacturing systems like Lean Production(LP). LP is a continuous improvement philosophy based on various lean activities for improving enterprise lean performance. A fuzzy model that integration Fuzzy Consistency Algorithm (FCA) and Fuzzy Analytical Hierarchy Process (FAHP) was proposed as a comprehensive framework to assess the levels of importance and priority of nineteen SME lean activities that categorized into the related five related lean dimensions. FCA was used to construct the fuzzy pairwise comparison matrix to ensure obtaining consistent experts judgment, whereas FAHP was applied to identify the level of importance and priority of lean activities. Identifying the level of importance of lean activities will be contributed in focuses SME efforts in the improvement process on the most important lean activities to ensure effective resource allocation and foster continuous improvement process and offer a practical tool for enhancing their competitiveness and sustainability. The proposed model was applied in Iraqi SME. The result showed that FCA is an efficient approach to construct a consistent judgment matrix. Efficient manger, Kaizen team, supplier relationship, execution customer suggestions and customer satisfaction job rotation are the most important lean activities with level of importance 58.90%, 21.30%, 49.80%, 38.50%, 41.20% respectively. The proposed model can be used for small or medium size enterprise for various production industries.
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Authors and Affiliations

Zainab Al-BALDAWI
AllaEldin H. KASSAM
Sawsan Sabeeh A. Al-ZUBAIDI
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Abstract

Indonesia is widely known as a country with rich biodiversity. Medicinal plants that thrive in Indonesia are utilized as traditional medicine locally known as “jamu”. One of the islands famous for jamu production is Madura Island. As a well-known jamu producer, Madura Island are facing problems related to jamu production. Procurement of medicinal plants is not well controlled. There are no reports of spices procurement and production. When there is an increase in demand or sale of certain jamu, the stock of jamu is commonly inadequate/insufficient This may result in order cancellation. The solution to this problem is to create a production forecasting information system by using single exponential smoothing. The data used is a weekly report on the number of sales of 3 types of jamu from August to October 2024. Mean Absolute Percentage Error (MAPE) testing using an alpha value of 0.1 to 0.9 resulted in “high” accuracy and the forecasted values were close to the actual data values.
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Authors and Affiliations

Rika YUNITARINI
Muhamad Afif EFFINDI
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Abstract

This study employed two primary approaches to determine the optimum structure: the lightweight and sustainable models. The lightweight model considered various factors such as materials, geometry, and dimensions of the brake disc rotor and brake pads. On the other hand, the sustainable model considers the manufacturing process and aims to reduce the carbon footprint. To calculate the optimal lightweight structure, finite element analysis was conducted using two different materials to compare the resulting stresses and determine the most appropriate material. Subsequently, four different models were utilized in finite element analysis to evaluate the displacement and stress and establish the optimum structure. Regarding sustainability, two distinct processes were employed to assess the environmental impact and energy consumption to adopt an eco-friendly approach. This paper investigates the transition from the initial brake disc rotor to a lightweight model, employing finite element analysis, topology optimization, and sustainability considerations. The work is achieved by comparing the cost between conventional and 3D printing processes.
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Authors and Affiliations

Hicham Fihri FASSI
Reda OURIHI
Fatima Zohra EL HILALI
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Abstract

In response to the urgent need for sustainable energy, this study addresses a critical challenge in wind turbine optimization. It focuses on developing a nuanced preventive maintenance strategy to minimize costs and mitigate energy losses. Within this framework, our paper introduces a novel approach employing a Monte Carlo simulation to identify the optimal preventive maintenance frequency, striking a balance between cost efficiency and energy loss mitigation. The results show, that grouped maintenance approach, pinpointing an optimal frequency of 93 months. This strategic configuration minimizes costs to $9997 while concurrently maintaining an average energy loss of 32.014 MWh, resulting in a notable 4.29% increase in total energy production. Variability analysis reveals that increasing maintenance frequency reduces cost fluctuations, while energy loss remains relatively stable. These findings elucidate the interplay among preventive maintenance strategies, cost, and reliability in the realm of wind turbine performance optimization
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Authors and Affiliations

Yassine EDDOUH
Abdelmajid DAYA
Rabie EL OTMANI
Abdelhamid TOUACHE
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Abstract

The purpose of the research process was to assess the state of knowledge on the use of Industry 4.0 postulates in the context of Engineer 4.0 and Manager 4.0 competencies in family firms, identify research gaps and outline future research directions. We conducted a systematic literature review of 21 articles from the Scopus database that relate to the topic of Industry 4.0 and Engineer 4.0 and Manager 4.0 in family firms. To identify the state of the art, keyword co-occurrence analysis using VosViewer software was used as an analytical tool. We identified the most influential journals and subject areas. The study allowed us to identify consistent clusters that show a wide variety of topics in the discussion of the mentioned topic. The results showed a wide dispersion of research interests and the lack of a single, in-depth or dominant research area dealing with the phenomenon worldwide. We recommend further research on family businesses and Industry 4.0. In addition, the lack of comparative research on family and non-family businesses should be addressed. Contribution and added value: Our systematic literature review systematizes the existing literature on Industry 4.0 in family firms, isolates key research interests, identifies future research directions and provides important insights for researchers.
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Authors and Affiliations

Ewa Więcek-Janka
ORCID: ORCID
Natalia CHOCHOŁOWSKA
Weronika ZARÓWNA
Patrycja GRALIŃSKA
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Abstract

In the logistics center (warehouse or distribution center), customer orders need to be picked up by the pickers. In this research, we examine the order-picking problem with sequencedependent constraints with two decision variables (container start time and product quantity) in a distribution center with a one-directional conveyor. The decision-making is based on the developed two variations of two-step matheuristics. At first, the main order-picking problem is divided into two subproblems. Next, each step of each variant of the subproblem is solved using a mathematical programming-based technique. Both matheuristics were better in 85 of 120 test instances compared to the initial model solved by mathematical programming. Pickers matheuristics were better on average at 46.56%, while Buffers matheuristics were better on average at 46.87%. The proposed matheuristics approach allows distributors to schedule orders in the logistics center fast enough and with fewer resources.
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Authors and Affiliations

Kateryna Czerniachowska
ORCID: ORCID
Radosław Wichniarek
ORCID: ORCID
Krzysztof Żywicki
ORCID: ORCID
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Abstract

Engineering plays a significant role in the advancement of medicine. One example of this is endoprostheses, which are prostheses implanted inside the body. Hip joint endoprostheses are commonly implanted nowadays, greatly improving physical fitness and the associated quality of life. However, a potential risk in using such endoprostheses is the possibility of dislocation. In this presented work, systems of forces acting on the limb were subjected to analysis, identifying unstable states that increase the risk of dislocation. Most of the analyses are qualitative, presenting rather than solving the problem. Nevertheless, a quantitative approach was presented for the case of dynamic forces generated during kicking a soccer ball. For this purpose, computer simulation was employed, based on an appropriate mathematical model.
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Authors and Affiliations

Bozena Kaczmarska
Wacław Gierulski
ORCID: ORCID
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Abstract

The purpose of the work presented here is a comparative analysis of two methods of solving the problem of optimizing the working time and path length of operators for manual harvesting of raspberries over an area of one hectare. An analytical solution is a method of solving mathematical problems based on finding an exact formula that describes a phenomenon or process. A simulation solution is the opposite of a numerical solution, which is based on calculating an approximation using statistical methods. An analytical and simulation approach will be presented to show how to calculate the number of workers needed, the minimum working time and the length of the path taken by raspberry fruit pickers. The results obtained for the two methods are compared.
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Authors and Affiliations

Ireneusz KACZMAR
Tamás BANYAI
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Abstract

In the era of Industry 4.0, digital human modeling (DHM) may be the key to improving ergonomics related to manual operations in the workplace. Poor workplace ergonomics may lead to reduced work productivity and an increased risk of health problems among employees, resulting in actual losses for enterprises, e.g., sickness absence, employee turnover, and training. DHM technology can help speed up ergonomic analysis and improvement. This paper proposes a methodological framework based on DHM to improve ergonomics in the workplace. Its purpose is to provide practitioners with an easy and detailed approach to ergonomics assessment and improvement procedures. The framework developed two main stages: the workplace Research Stage and the DHM and Simulation Stage, which cover the eight detailed steps of an effective DHM-based ergonomic assessment together. A case study was used to verify and demonstrate the effectiveness of the proposed methodological framework.
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Authors and Affiliations

Andrzej Marek LASOTA
Krzysztof HANKIEWICZ

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

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