Management and Production Engineering Review

Content

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

Download PDF Download RIS Download Bibtex

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.

Go to article

Authors and Affiliations

Miklos Guban
Richard Kasa
David Takacs
Mihai Avornicului
Download PDF Download RIS Download Bibtex

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.

Go to article

Authors and Affiliations

Abdelaziz Lakehal
Mourad Nahal
Riad Harouz
Download PDF Download RIS Download Bibtex

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,

Go to article

Authors and Affiliations

Vitalii Ivanov
Ivan Dehtiarov
Ivan Pavlenko
Illia Kosov
Mykyta Kosov
Download PDF Download RIS Download Bibtex

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.

Go to article

Authors and Affiliations

Bounou Oumaima
Abdellah El Barkany
Ahmed El Biyaali
Download PDF Download RIS Download Bibtex

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

Go to article

Authors and Affiliations

Miriam Pekarcıkova
Peter Trebuna
Marek Kliment
Jozef Trojan
Download PDF Download RIS Download Bibtex

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.

Go to article

Authors and Affiliations

Miguel Malek Maalouf
Magdalena Zaduminska
Download PDF Download RIS Download Bibtex

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.

Go to article

Authors and Affiliations

Mehdi Ajalli
Mohammad Mahdi Mozaffari
Ali Asgharisarem
Download PDF Download RIS Download Bibtex

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.

Go to article

Authors and Affiliations

Maha AlKhatib
Safwan Altarazi
Download PDF Download RIS Download Bibtex

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.

Go to article

Authors and Affiliations

Paulina Rewers
Mariusz Bożek
Wojciech Kulus
Download PDF Download RIS Download Bibtex

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.

Go to article

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.

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.
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

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

This page uses 'cookies'. Learn more