Management and Production Engineering Review

Content

Management and Production Engineering Review | 2019 | vol. 10 | No 3

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Abstract

With the increasing demand of customisation and high-quality products, it is necessary for

the industries to digitize the processes. Introduction of computers and Internet of things

(IoT) devices, the processes are getting evolved and real time monitoring is got easier.

With better monitoring of the processes, accurate results are being produced and accurate

losses are being identified which in turn helps increasing the productivity. This introduction

of computers and interaction as machines and computers is the latest industrial revolution

known as Industry 4.0, where the organisation has the total control over the entire value chain

of the life cycle of products. But it still remains a mere idea but an achievable one where IoT,

big data, smart manufacturing and cloud-based manufacturing plays an important role. The

difference between 3rd industrial revolution and 4th industrial revolution is that, Industry

4.0 also integrates human in the manufacturing process. The paper discusses about the

different ways to implement the concept and the tools to be used to do the same.

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Authors and Affiliations

Devansh Sanghavi
Sahil Parikh
S. Aravind Raj
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Abstract

The article presents tools, methods and systems used in mechanical engineering that in

combination with information technologies create the grounds of Industry 4.0. The authors

emphasize that mechanical engineering has always been the foundation of industrial activity,

while information technology, the essential part of Industry 4.0, is its main source of innovation.

The article discusses issues concerning product design, machining tools, machine tools

and measurement systems.

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Authors and Affiliations

Adam Hamrol
Józef Gawlik
Jerzy Sładek
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Abstract

Rescheduling is a frequently used reactive strategy in order to limit the effects of disruptions

on throughput times in multi-stage production processes. However, organizational deficits

often cause delays in the information on disruptions, so rescheduling cannot limit disruption

effects on throughput times optimally. Our approach strives for an investigation of

possible performance improvements in multi-stage production processes enabled by realtime

rescheduling in the event of disruptions. We developed a methodology whereby we

could measure these possible performance improvements. For this purpose, we created and

implemented a simulation model of a multi-stage production process. We defined system

parameters and varied factors according to our experiment design, such as information delay,

lot sizes and disruption durations. The simulation results were plotted and evaluated

using DoE methodology. Dependent on the factor settings, we were able to prove large improvements

by real-time rescheduling regarding the absorption of disruption effects in our

experiments.

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Authors and Affiliations

Peter Burggraf
Johannes Wagne
Oliver Bischoff
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Abstract

The objective of the milk-run design problem considered in this paper is to minimize transportation

and inventory costs by manipulating fleet size and the capacity of vehicles and

storage areas. Just as in the case of an inventory routing problem, the goal is to find a periodic

distribution policy with a plan on whom to serve, and how much to deliver by what

fleet of tugger trains travelling regularly on which routes. This problem boils down to determining

the trade-off between fleet size and storage capacity, i.e. the size of replenishment

batches that can minimize fleet size and storage capacity. A solution obtained in the declarative

model of the milk-run system under discussion allows to determine the routes for each

tugger train and the associated delivery times. In this context, the main contribution of

the present study is the identification of the relationship between takt time and the size

of replenishment batches, which allows to determine the delivery time windows for milkrun

delivery and, ultimately, the positioning of trade-off points. The results show that this

relationship is non-linear.

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Authors and Affiliations

Grzegorz Bocewicz
Wojciech Bożejko
Robert Wójcik
Zbigniew Banaszak
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Abstract

This paper explores selected heuristics methods, namely CDS, Palmer’s slope index, Gupta’s

algorithm, and concurrent heuristic algorithm for minimizing the makespan in permutation

flow shop scheduling problem. Its main scope is to explore how different instances sizes

impact on performance variability. The computational experiment includes 12 of available

benchmark data sets of 10 problems proposed by Taillard. The results are computed and

presented in the form of relative percentage deviation, while outputs of the NEH algorithm

were used as reference solutions for comparison purposes. Finally, pertinent findings are

commented.

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Authors and Affiliations

Zuzana Soltysova
Pavol Semanco
Jan Modrak
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Abstract

The objectives of this study were to develop a framework of the collaboration network, operational

performance, and reverse logistics determinants on the performance outcomes of the

auto parts industry, and to study the direct, indirect, and overall effects of the factors that

influence the performance outcomes of the auto parts industry. This quantitative research

utilized a questionnaire as the tool for data collection, which was completed by the managers

in the auto parts industry from 320 companies. According to the analysis with the Structural

Equation Modeling (SEM), it was found that the collaboration networks, operational

performance, and reverse logistics positively affect the performance outcomes; whereas, the

collaboration networks mainly affect the development of organizations by causing performance

outcomes to continue growing unceasingly, including the enhancement of sustainable

competitive capacity and the operational results of the auto parts industry.

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Authors and Affiliations

Phasit Phoosawad
Wanno Fongsuwan
Wawmayura Chamsuk
Josu Takala
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Abstract

Redundancy based methods are proactive scheduling methods for solving the Project

Scheduling Problem (PSP) with non-deterministic activities duration. The fundamental

strategy of these methods is to estimate the activities duration by adding extra time to the

original duration. The extra time allows to consider the risks that may affect the activities

durations and to reduce the number of adjustments to the baseline generated for the project.

In this article, four methods based on redundancies were proposed and compared from two

robustness indicators. These indicators were calculated after running a simulation process.

On the other hand, linear programming was applied as the solution technique to generate

the baselines of 480 projects analyzed. Finally, the results obtained allowed to identify the

most adequate method to solve the PSP with probabilistic activity duration and generate

robust baselines.

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Authors and Affiliations

Nestor Raul Ortiz-Pimiento
Francisco Javier Diaz-Serna
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Abstract

The focus of this paper is to propose a method for prioritizing knowledge and technology

factor in companies’ business strategy. The data has been gathered and analyzed from

Malaysian-owned company of medium size type industry, employing around 250 employees

and listed in the Malaysian Bourse Stock of Exchange, since 2000. Sense and respond model

is used to determine competitive priorities of the firms. Then knowledge and technology

part of sense and respond questionnaire is used to calculate the variability coefficient i.e. the

uncertainty caused by technology and knowledge factor. The results show that the company

is not leading in term of technology (spear head technology share is around 33%). Therefore,

the enhancement of technology and knowledge to SCA values is not significantly seen in

this study. The usage of the core technologies is around 41% and it might seem relatively

enough. In terms of basic technology, while its share is the lowest (around 25%), it has the

highest source of uncertainties among technology types. In this case, the proposed model

helped to have a clear and precise improvement plan towards prioritizing technology and

knowledge focus.

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Authors and Affiliations

Sara Tilabi
Rosmaini Tasmin
Josu Takala
M.H. Muazu
A.H. Nor Aziati
A.R. Shafiee
Noraini Kaprawi
M.S. Che Rusuli
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Abstract

Industrial engineers gather knowledge during their bachelor studies through lectures and

practical classes. The goal of practical class might be an extension of knowledge and/or a

consolidation and application of already gathered knowledge. It is observed that there exists

a gap between theory learnt during lectures and practical classes. If practical classes require

holistic approach and solving complex tasks (problems), students strive with understanding

relations and connections between parts of knowledge. The aim of this article is to show an

example of a simple practical assignment that can serve as a bridge between lectures and

practical classes through discussion of interactions and relations between parts of theoretical

knowledge. It is an example of in-class simulating of a line and cellular layout considering

discussion of elements impacting and impacted by the type of layout (e.g. learning curve,

changeovers, etc.). In-class verification of the presented approach confirmed its usability for

teaching industrial engineers and bridging the gap between theory delivered through lectures

and more advanced practical classes.

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Authors and Affiliations

Bartlomiej Gladysz
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Abstract

The objective of this research is to investigate the perception of owner – managers and

their employees regarding entrepreneurial leadership. To develop the research, two questions

are raised related to the similarities or differences of the perceptions of both groups

with what is established in the literature and between the self – evaluation of the owner –

managers and their employees on whether the former perform as an entrepreneurial leader.

As a research method, both groups are asked to perform, first individual evaluations and

then to match certain behaviours and the levels at which they should appear at certain levels

of entrepreneurial leadership capacity. The data gathered during the investigation were

processed using the Categorical Principal Components Analysis and revealed the similarities

and differences between the perceptions of the owner-managers and their employees on

entrepreneurial leadership. In spite of not finding significant differences between what is established

in the literature and among the perceptions of the groups under study, interesting

nuances stand out that, if not identified and understood, could have a negative effect on

the performance of SMEs. The results of the research demonstrated the importance of the

approach of behaviour and perception in the study of entrepreneurial leadership.

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Authors and Affiliations

Gelmar Garcıa-Vidal
Alexander Sanchez-Rodrıguez
Reyner Perez-Campdesuner
Rodobaldo Martınez-Vivar
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Abstract

The application of artificial intelligence (AI) in modeling of various machining processes has

been the topic of immense interest among the researchers since several years. In this direction,

the principle of fuzzy logic, a paradigm of AI technique, is effectively being utilized

to predict various performance measures (responses) and control the parametric settings of

those machining processes. This paper presents the application of fuzzy logic to model two

non-traditional machining (NTM) processes, i.e. electrical discharge machining (EDM) and

electrochemical machining (ECM) processes, while identifying the relationships present between

the process parameters and the measured responses. Moreover, the interaction plots

which are developed based on the past experimental observations depict the effects of changing

values of different process parameters on the measured responses. The predicted response

values derived from the developed models are observed to be in close agreement with those

as investigated during the past experimental runs. The interaction plots also play significant

roles in identifying the optimal parametric combinations so as to achieve the desired

responses for the considered NTM processes.

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Authors and Affiliations

Shankar Chakraborty
Partha Protim Das
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Abstract

This paper is a case study conducted to present an approach to the process of designing

new products using virtual prototyping. During the first stage of research a digital geometric

model of the vehicle was created. Secondly it underwent a series of tests utilising the

multibody system method in order to determine the forces and displacements in selected

construction nodes of the vehicle during its movement on an uneven surface. In consequence

the most dangerous case of loads was identified. The obtained results were used to conduct

detailed strength testing of the bicycle frame and changes its geometry. For the purposes

of this case study two FEA software environments (Inventor and SolidWorks) were used. It

has been confirmed that using method allows to implement the process of creating a new

product more effectively as well as to assess the influence of the conditions of its usage more

efficiently. It was stated that using of different software environments increases the complexity

of the technical process of production preparation but at the same time increases the

certainty of prototype testing. The presented example of simulation calculations made for

the bicycle can be considered as a useful method for calculating other prototypes with high

complexity of construction due to its systematized character of chosen conditions and testing

procedure. It allows to verify the correctness of construction, functionality and perform

many analyses, which can contribute to the elimination of possible errors as early as at the

construction stage.

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Authors and Affiliations

Krzysztof Łukaszewicz

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.


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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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