Management and Production Engineering Review

Content

Management and Production Engineering Review | 2021 | vol. 12 | No 4

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Abstract

Simulations are becoming one of the most important techniques supporting production preparation, even in those industrial sectors with atypical technological processes, such as in metallurgy, where there is a multiphase material flow. This is due to the fact that in the conditions of a market economy, enterprises have to solve more and more complex problems in a shorter time. On the basis of the existing production process and the knowledge of the flow characteristics in a given process, a model is built, which, when subjected to simulation tests, provides experimental results in the scope of the defined problem. The use of computer techniques also creates new possibilities for the rational use of the reserves inherent in each technological process. Taking into account the existing demand and the state of modern technology, the computer model can be a source of information for further analysis and decision-making processes supporting company management. At work a model of the logistic system was made on the example of a hot-rolled steel strip mill, on which simulation experiments were carried out to improve the effectiveness and efficiency of the analysis production line. The presented article aims to disseminate the idea of ??Industry 4.0 in Polish companies from the manufacturing industry sector, taking into account simulation techniques.
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Authors and Affiliations

Mariusz Niekurzak
1
Ewa Kubińska-Jabcoń
1

  1. AGH University of Science and Technology, Faculty of Management, Poland
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Abstract

This study investigates (1) the effect of quality information on quality performance through process control and (2) the moderating role of shop floor leadership on the relationship between quality information and quality performance in the context of manufacturing plants on a global basis. The moderated mediation analysis with a bootstrapping approach was employed to analyse data for hypotheses testing. The data is from the fourth-round dataset of the High- Performance Manufacturing Project, collected from manufacturing plants worldwide. The results indicate that (1) quality information is positively associated with quality performance through process control, and (2) shop floor leadership (i.e., supervisory interaction facilitation) positively moderates the indirect effect of quality information on quality performance; that is, the shop floor leadership practice strengthens the effect of quality information on quality performance through process control. This study also has a practical implication for top managers who should consider the vital role of leadership practices adopted by shop floor supervisors in implementing total quality management practices and should raise awareness that leadership practices are not only for the ‘C-suite’ but also for shop floor supervisors.
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Authors and Affiliations

Ngoc Anh Nguyen
Chi Phan Anh
Thi Xuan Thoa Pham
Matsui Yoshiki
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Abstract

The present paper describes a methodological framework developed to select a multi-label dataset transformation method in the context of supervised machine learning techniques. We explore the rectangular 2D strip-packing problem (2D-SPP), widely applied in industrial processes to cut sheet metals and paper rolls, where high-quality solutions can be found for more than one improvement heuristic, generating instances with multi-label behavior. To obtain single-label datasets, a total of five multi-label transformation methods are explored. 1000 instances were generated to represent different 2D-SPP variations found in real-world applications, labels for each instance represented by improvement heuristics were calculated, along with 19 predictors provided by problem characteristics. Finally, classification models were fitted to verify the accuracy of each multi-label transformation method. For the 2D-SPP, the single-label obtained using the exclusion method fit more accurate classification models compared to the other four multi-label transformation methods adopted.
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Authors and Affiliations

Neuenfeldt Júnior Alvaro
Matheus Francescatto
Gabriel Stieler
David Disconzi
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Abstract

Traditionally the aggregate production plan helps in determining the inventory, production, and work-force, based on the demand forecasts without considering the productivity loss at a tactical level in supply chain planning. In this paper, we include the productivity loss into traditional aggregate production plan and the prescriptive analytics technique, linear programming, is used to solve this problem of practical interest in the domain of multifarious businesses and industries. In this study, we discussed two model variations of the aggregate production planning problem with and without productivity loss, i) fixed work-force, and ii) variable Work Force. The mathematical models were designated to be solved by using an open-source python pulp package in order to evaluate the impacts of the productivity loss on both the models. PuLP is an open-source modeling framework provided by the COIN-OR Foundation (Computational Infrastructure for Operations Research) for linear and integer Programing problems written in Python. The computational results indicate that the productivity loss has direct impact on the workforce hiring and firing.
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Authors and Affiliations

Hakeem Ur REHMAN
Ayyaz AHMAD
Zarak ALI
Sajjad Ahmad BAIG
Umair MANZOOR

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Abstract

The aim of this work is to present new reliability characteristics expressed as functions of some variable expressing the measure of effective operation of a machine or a device. These characteristics can be used for both renewable and non-renewable objects. Their mathematical idea reflects the essence of already known characteristics, i.e. it expresses the probability of failure but expressed as a function of a variable, not necessarily identified with time.
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Authors and Affiliations

Gabriela Kopania
Anna Kuczmaszewska
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Abstract

In mid-1992, Japanese consultant Yamada Hitoshi was tasked with modifying the production systems of Japanese companies as the existing configurations at manufacturing plants no longer satisfied unstable demands. He made improvements to the overall production system by dividing the long assembly lines into several short ones called cells or seru. Although of the advantages, it is still unclear about how to manage this new production system, and what variables really promoted the desired benefits. We identify in total 39 articles from 2004– 2020 about the progress of the seru production system, and we observe some possibilities to improve the effectiveness of this type of the production system. The first is the possibility of manufacturing the product in flexible sequence, in which the operations are independent among them. We show through the developed example that the makespan may be different. We noted when converting the in-line production system to one pure seru, the makespan tend to increase. Nevertheless, when analyzing the effectiveness of serus working concomitantly considering splitting the same lot, makespan and the cost may be reduced. And finally, when converting to one of pure serus, the performance may be similar to that obtained when serus working concomitantly.
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Authors and Affiliations

Yung Chin Shih
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Abstract

Lean Green is a concept which is implemented as a part of the sustainable development strategy, share allowing for reduction of the company’s costs related to, on the one hand, efficient use of energy factors and on the other optimum use of production factors aimed at minimisation of wastefulness, in particular in the area of post-production waste and pollution. The purpose of the article is to identify the determinants, internal stimuli and to specify the force with which they affect the implementation of the Lean Green concept in companies on various continents: America, Asia and Europe. For the purpose of better recognition of the examined problem, analysis of results of studies was made in consideration of the following criteria: country where a given company operates and share of persons outside the company in the process of implementation of this concept. In article uses the one-way ANOVA methodology, the Shapiro Wilk and Levene tests and the non-parametric Kruskal Wallis test. Hitherto studies have confirmed that the determinants are regional, which indicates the necessity of directional studies.
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Authors and Affiliations

Nicoletta Baskiewicz
Claudiu Barbu
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Abstract

Enterprise innovation is currently becoming a recognized factor of the competitiveness, survival, and development of companies in the market economy. Managers still need recommendations on ways of stimulating the growth of innovation in their companies. The objective of this paper is to identify the strategic factors of enterprise innovativeness in the area of technology, defined as the most important internal factors positively impacting the innovativeness of enterprises in a strategic perspective. Empirical studies were conducted using the Computer-Assisted Web Interview (CAWI) method on a purposive sample of N = 180 small and medium-sized innovative industrial processing enterprises in Poland. Data analysis was performed using Exploratory Factor Analysis within the Confirmatory Factor Analysis framework (E-CFA) and Structural Equation Modeling (SEM). Empirical research shows that the strategic factor of enterprise innovativeness in the area of technology is technological activity. A technologically active company should (1) possess a modern machinery stock, (2) conduct systematic technological audits, and (3) maintain close technical cooperation with the suppliers of raw materials, consumables, and intermediates. The implementation of the indicated recommendations by managers should lead to increased innovativeness of small and medium-sized industrial companies. The author recommends the use of the presented research procedure and data analysis methods in further studies.
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Authors and Affiliations

Danuta Rojek
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Abstract

Technological progress is the driving force behind industrial development. It is a multidimensional and multi-level phenomenon. In this article we focus on its three manifestations: information and communication technologies (ICT), Industry 4.0 and agile manufacturing. The aim of this article is to analyse the relationship between these constructs as they are undoubtedly interrelated. ICT plays a key role, but it is not a goal itself. They are a prerequisite for the implementation of Industry 4.0, but together with it they serve to achieve agility by the manufacturing system and, as a result, achieve a competitive advantage by companies operating in turbulent and unpredictable environment. The literature findings in this paper are part of a broader study conducted on the impact of ICT on agility of SMEs operating in India. Therefore, we include also subsections showing the level of this relationship in Indian SMEs.
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Authors and Affiliations

Ibrahim Khan Mohammed
Stefan Trzcielinski
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Abstract

The aim of our research is to gain understanding about material flow related information sharing in the circular economy value network in the form of industrial symbiosis. We need this understanding for facilitating new industrial symbiosis relationships and to support the optimization of operations. Circular economy has been promoted by politics and regulation by EU. In Finland, new circular economy strategy raises the facilitation of industrial symbiosis and data utilization as the key actions to improve sustainability and green growth. Companies stated that the practical problem is to get information on material availability. Digitalization is expected to boost material flows in circular economy by data, but what are the real challenges with circular material flows and what is the willingness of companies to develop co-operation? This paper seeks understanding on how Industry 4.0 is expected to improve the efficiency of waste or by-product flows and what are the expectations of companies. The research question is: How Industry 4.0 technologies and solutions can fix the gaps and discontinuities in the Industrial Symbiosis information flow? This research is conducted as a qualitative case study research with three cases, three types of material and eight companies. Interview data were collected in Finland between January and March 2021. Companies we interviewed mentioned use-cases for sensors and analytics to optimize the material flow but stated the investment cost compared to the value of information. To achieve sustainable circular material flows, the development needs to be done in the bigger picture, for the chain or network of actors, and the motivation and the added value must be found for each of them.
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Authors and Affiliations

Anne-Mari Järvenpää
Vesa Salminen
Jussi Kantola
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Abstract

The aim of the article is to present an exemplary system for recording and analyzing quality costs and to demonstrate that it is helpful in planning and assessing the effectiveness of continuous improvement processes at the operational and strategic level. Various approaches to defining quality costs are described, followed by indicators for assessing effectiveness and tools to collect data on the values of individual groups of quality costs and compare them with financial indicators. The practical part presents a case study on the quality cost accounting system in a medical company and the possibility of using quality cost accounting to plan and evaluate continuous improvement processes and make managerial decisions.
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Authors and Affiliations

Ilona Herzog
Marta Grabowska
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Abstract

In digital revolution, the appropriate IT infrastructure, technological knowledge are essential for the success of companies, where the success of the digital transformation depends on digital maturity. The aim of the study is to define the digital maturity, theoretical foundation of the digital maturity model and present a framework for small and medium-sized enterprises (SMEs) understanding where they are in digitalisation (how advanced their digital resource system and digital approach) to respond faster and efficiently to environmental changes. The model construction is based on theory of dynamic capabilities, graduation models, and SMEs management challenges. The model is a dynamic model to support management in strategic, digital and organizational developments, which is divided into IT and organizational dimensions, including 6 components and 28 subcomponents. The ultimate goal of the study is to determine the component weights to create a neurofuzzy model.
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Authors and Affiliations

Ágnes Sándor
Ákos Gubán

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The ethics statements for the journal Management and Production Engineering Review are based on the guidelines of Committee on publication ethics (COPE) and the ELSEVIER publishing ethics resource kit.
For Authors: All articles, published in the journal Management and Production Engineering Review have to comprise a list of references which correspond with the journal’s Instructions to authors for paper preparation. The authors should ensure that they have written entirely original works, and if the authors have used the work and/or words of others that this has been appropriately cited or quoted. All articles are tested using antyplagiarism programme. An author should not in general publish manuscripts describing essentially the same research in more than one journal or primary publication. Submitting the same manuscript to more than one journal concurrently constitutes unethical publishing behaviour and is unacceptable. Authorship should be limited to those who have made a significant contribution to the conception, design, execution, or interpretation of the reported study. The corresponding author should ensure that all co-authors have seen and approved the final version of the paper and have agreed to its submission for publication. All authors should disclose in their manuscript any financial or other substantive conflict of interest that might be construed to influence the results or interpretation of their manuscript. All sources of financial support for the project should be disclosed.
Authors are accountable for the originality, validity and integrity of the content of their submissions. In choosing to use AI tools, authors are expected to do so responsibly and in accordance with our editorial policies on authorship and principles of publishing ethics. Authorship requires taking accountability for content, consenting to publication via an author publishing agreement, giving contractual assurances about the integrity of the work, among other principles. These are uniquely human responsibilities that cannot be undertaken by AI tools. Therefore, AI tools must not be listed as an author. Authors must, however, acknowledge all sources and contributors included in their work. Where AI tools are used, such use must be acknowledged and documented appropriately.
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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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