Management and Production Engineering Review

Content

Management and Production Engineering Review | 2019 | vol. 10 | No 2

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Abstract

The field of academic research on corporate sustainability management has gained significant

sophistication since the economic growth has been associated with innovation. In this paper,

we are to show our research project that aims to build an artificial intelligence-based neurofuzzy

inference system to be able to approximate company’s innovation performance, thus

the sustainability innovation potential. For this we used an empirical sample of Hungarian

processing industry’s large companies and built an adaptive neuro fuzzy inference system.

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Authors and Affiliations

Miklos Guban
Richard Kasa
David Takacs
Mihai Avornicului
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Abstract

Fault Tree is one of the traditional and conventional approaches used in fault diagnosis. By

identifying combinations of faults in a logical framework it’s possible to define the structure

of the fault tree. The same go with Bayesian networks, but the difference of these probabilistic

tools is in their ability to reasoning under uncertainty. Some typical constraints to the

fault diagnosis have been eliminated by the conversion to a Bayesian network. This paper

shows that information processing has become simple and easy through the use of Bayesian

networks. The study presented showed that updating knowledge and exploiting new knowledge

does not complicate calculations. The contribution is the structural approach of faults

diagnosis of turbo compressor qualitatively and quantitatively, the most likely faults are

defined in descending order. The approach presented in this paper has been successfully

applied to turbo compressor, which represent vital equipment in petrochemical plant.

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Authors and Affiliations

Abdelaziz Lakehal
Mourad Nahal
Riad Harouz
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Abstract

At present, the speed of production and its complexity increases with each passing year due

to the shorter product life cycle and competition in the global market. This trend is also

observed in the machine-building industry, therefore, in order to ensure the competitiveness

of enterprises and reduce the cost of production, it is necessary to intensify production.

This is especially true in the machining of complex parts that require a great number of

setups, and technological equipment. The problem-oriented analysis of complex parts was

carried out, the parts classification was structured and developed according to the design

and technological features. This made it possible to offer advanced manufacturing processes

for complex parts like levers, forks, and connecting rods. The flexible fixtures for specified

complex parts were developed. The effectiveness of the proposed manufacturing processes,

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Authors and Affiliations

Vitalii Ivanov
Ivan Dehtiarov
Ivan Pavlenko
Illia Kosov
Mykyta Kosov
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Abstract

The supply chain of spare parts is the intersection between the supply chain, the after-sales

and the maintenance services. Some authors have tried to define improvement paths in terms

of models to satisfy the performance criteria. In addition, other authors are directed towards

the integration of risk management in the demand forecasting and the stock management

(performance evaluation) through probabilistic models. Among these models, the probabilistic

graphical models are the most used, for example, Bayesian networks and petri nets.

Performance evaluation is done through performance indicators.

To measure the appreciation of the supply of the spare parts stock, this paper focuses on the

performance evaluation of the system by petri nets. This evaluation will be done through

an analytical study. The purpose of this study is to evaluate and analyze the performance of

the system by proposed indicators. First, we present a literature review on Petri nets which

is the essential tool in our modeling. Secondly, we present in the third section the analytical

study of the model based on bath deterministic and stochastic petri networks. Finally, we

present an analysis of the proposed model compared to the existing ones.

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Authors and Affiliations

Bounou Oumaima
Abdellah El Barkany
Ahmed El Biyaali
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Abstract

Industry 4.0 will affect the complexity of supply chain networks. It will be necessary to

adapt more and more to the customer and respond within a time interval that is willing

to accept the product waiting. From these considerations, there is a need for a different way

of managing the supply chain. The traditional concept of supply chain as a linear system,

which allows optimizing individual subsystems, thus obtaining an optimized supply chain, is

not enough. The article deals with the issue of supply chain management reflecting demand

behaviour using the methodology Demand Driven MRP system. The aim of the publication

is to extend the knowledge base in the area of demand-driven supply logistics in the

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Authors and Affiliations

Miriam Pekarcıkova
Peter Trebuna
Marek Kliment
Jozef Trojan
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Abstract

The relatively limited application of lean in the food process industries has been attributed to

the unique characteristics of the food sector i.e. short shelf-life, heterogeneous raw materials,

and seasonality. Moreover, barriers such as large and inflexible machinery, long setup time,

and resource complexity, has limited the implementation and impact of lean practices in

process industries in general. Contrary to the expectations in the literature, we bring in this

paper a successful experience of lean implementation in a company of the food-processing

sector. By focusing on two lean tools (VSM and SMED), the company reduced changeover

time by 34%, and increased the production capacity of the main production line by 11%.

This improvement enabled the company to avoid the use of temporary workers by extending

the worktime of its workforce during peak months. Moreover, the reduction of setup time

avoided the use of large lot size in production, which, in turn, reduced the total cycle time

of production and the incidence of quality problems.

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Authors and Affiliations

Miguel Malek Maalouf
Magdalena Zaduminska
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Abstract

One of the strategic decisions of any organization is decision making about manufacturing

strategy. Manufacturing strategy is a perspective distinguishing a company from other

present companies in that industry and creates a kind of stability in decisions and gives a special

direction to organizational activities. SIR (SUPERIORITY& INFERIORITY Ranking)

method and their applications have attracted much attention from academics and practitioners.

FSIR proves to be a very useful method for multiple criteria decision making in fuzzy

environments, which has found substantial applications in recent years. This paper proposes

a FSIR approach based methodology for TOPSIS, which using MILTENBURG Strategy

Worksheet in order to analyzing of the status of strategy of the Gas Company. Then formulates

the priorities of a fuzzy pair-wise comparison matrix as a linear programming and

derives crisp priorities from fuzzy pair-wise comparison matrices

Manufacturing levers (Alternatives) are examined and analyzed as the main elements of

manufacturing strategy. Also, manufacturing outputs (Criteria are identified that are competitive

priorities of production of any organization. Next, using a hybrid approach of FSIR

and TOPSIS, alternatives (manufacturing levers) are ranked. So dealing with the selected

manufacturing levers and promoting them, an organization makes customers satisfied with

the least cost and time.

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Authors and Affiliations

Mehdi Ajalli
Mohammad Mahdi Mozaffari
Ali Asgharisarem
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Abstract

This study presents a customized root cause analysis approach to investigate the reasons,

provide improvements measures for the cost overruns, and schedule slippage in papermachine-

building projects. The proposed approach is an analytical-survey approach that

uses both actual technical data and experts’ opinions. Various analysis tools are embedded

in the approach including: data collection and clustering, interviews with experts, 5-Whys,

Pareto charts, cause and effect diagram, and critical ratio control charts. The approach was

implemented on seven projects obtained from a leading international paper machine supplier.

As a result, it was found that the main causes behind cost and schedule deviations

are products’ related; including technical accidents in the Press section, damaged parts, design

issues, optimization of the machine and missing parts. Based on the results, prevention

measures were perceived.

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Authors and Affiliations

Maha AlKhatib
Safwan Altarazi
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Abstract

The main purpose of this article is to present an author’s methodology of production levelling

and to show the impact of levelling on the time during which the product passes

through the process and on staff performance. The article presents the analysis of literature

concerning the method of improving the production process, especially taking production

levelling into consideration. The authors focussed on the definition and methodologies of

production levelling. A diagram of interrelations showing determinants and efficiency measures

of production levelling as well as an author’s production levelling methodology have

been presented. An example of the implementation of production levelling in one of the departments

of a company manufacturing surgical instruments has also been shown. Analysis

of the current state, stages of implementation and end effects have been presented. Attention

was focussed on the time during which the product passes through the process and on staff

performance.

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Authors and Affiliations

Paulina Rewers
Mariusz Bożek
Wojciech Kulus
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Abstract

The article presents the issue related with a proper preparation of a data sheet for the

analysis, the way of verifying the correctness and reliability of input information, and proper

data encoding. Improper input or coding of data can significantly influence the correctness

of performed analyses or extend their time. This stage of an analysis is presented by an

authorship questionnaire for the study on occupational safety culture in a manufacturing

plant, using the Statistica software for analyses. There were used real data, obtained during

the research on the issue of occupational safety and factors having the greatest influence on

the state of occupational safety.

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Authors and Affiliations

Patryk Krupa
Izabela Gabryelewicz
Milan Edl
Peter Pantya
Justyna Patalas-Maliszewska

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.

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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/.

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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