Management and Production Engineering Review

Content

Management and Production Engineering Review | 2020 | vol. 11 | No 1

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Abstract

Labor absenteeism is a factor that affects the good performance of organizations in any

part of the world, from the instability that is generated in the functioning of the system.

This is evident in the effects on quality, productivity, reaction time, among other aspects.

The direct causes by which it occurs are generally known and with greater reinforcement

the diseases are located, without distinguishing possible classifications. However, behind

these or other causes can be found other possible factors of incidence, such as age or sex.

This research seeks to explore, through the application of neural networks, the possible

relationship between different variables and their incidence in the levels of absenteeism. To

this end, a neural networks model is constructed from the use of a population of more than

12,000 employees, representative of various classification categories. The study allowed the

characterization of the influence of the different variables studied, supported in addition to

the performance of an ANOVA analysis that allowed to corroborate and clarify the results

of the neural network analysis.

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Authors and Affiliations

Reyner Perez-Campdesuner
Margarita De Miguel-Guzan
Gelmar Garcıa-Vidal
Alexander Sanchez-Rodrıguez
Rodobaldo Martınez-Vivar
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Abstract

Up to date, workload and worker performance in Small Medium-sized Enterprise (SMEs)

was assessed manually. KESAN (Kansei Engineering-based Sensor for Agroindustry) was

developed as a tool to assess worker workload and performance. The latest prototype of

KESAN was established. As the final step prior to the full-scale mass production, an industrial

design was required and must be designed based on the validation to user needs. This

research proposed an industrial design for mass production of KESAN using Kano model

and Quality Function Deployment (QFD). The user needs was extracted from attributive

analysis of Kano model. The matrix of House of Quality (HOQ) was utilized to connect

the user needs and technical requirement. The research result validated Thirteen (13) user

need attributes. The most important attribute was desktop application as an integrated

decision support system. Fourteen (14) technical requirement attributes were identified to

fulfil the user needs. Finally, a prototype was developed based on product final specification

and prioritized technical requirements.

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Authors and Affiliations

Taufik Nugraha Agassi
Mirwan Ushada
Atris Suyantohadi
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Abstract

The operation of thermal devices and installations, in particular heat exchangers, is associated

with the formation of various deposits of sediments, forming the boiler scale. The

amount of precipitate depends on the quality of the flowing liquids treatment, as well as

the intensity of the use of devices. There are both mechanical and chemical treatment methods

to remove these deposits. The chemical methods of boiler scale treatment include the

cleaning method consisting in dissolving boiler scale inside heat devices. Worked out descaling

concentrate contains phosphoric acid (V) and the components that inhibit corrosion,

anti-foam substances, as well as anti-microbial substances as formalin, ammonium chloride,

copper sulphate and zinc sulfate. Dissolution of the boiler scale results in the formation of

wastewater which can be totally utilized as raw materials in phosphoric fertilizer produc

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Authors and Affiliations

Piotr Olczak
Zygmunt Kowalski
Joanna Kulczycka
Agnieszka Makara
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Abstract

Seasonality is a function of a time series in which the data experiences regular and predictable

changes that repeat each calendar year. Two-stage stochastic programming model

for real industrial systems at the case of a seasonal demand is presented. Sampling average

approximation (SAA) method was applied to solve a stochastic model which gave a productive

structure for distinguishing and statistically testing a different production plan. Lingo

tool is developed to obtain the optimal solution for the proposed model which is validated

by Math works Matlab. The actual data of the industrial system; from the General Manufacturing

Company, was applied to examine the proposed model. Seasonal future demand

is then estimated using the multiplicative seasonal method, the effect of seasonality was

presented and discussed. One might say that the proposed model is viewed as a moderately

accurate tool for industrial systems in case of seasonal demand. The current research may

be considered a significant tool in case of seasonal demand. To illustrate the applicability of

the proposed model a numerical example is solved using the proposed technique. ANOVA

analysis is applied using MINITAB 17 statistical software to validate the obtained results.

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Authors and Affiliations

Asmaa A. Mahmoud
Mohamed F. Aly
Ahmed M. Mohib
Islam H. Afefy
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Abstract

Low cost manufacturing of quality products remains an essential part of present economy

and technological advances made it possible. Advances and amalgamation of information

technology bring the production systems at newer level. Industry 4.0, factory for future,

smart factory, digital manufacturing, and industrial automation are the new buzz words of

industry stalwarts and academicians. These new technological revolutions bound to change

not only the complete manufacturing scenarios but many other sectors of the society. In this

paper an attempt has been made to capture the essence of Industry 4.0 by redefining it in

simple words, further its complex, disruptive nature and inevitability along with technologies

backing it has been discussed. Its enabling role in manufacturing philosophies like Lean

Manufacturing, and Flexible Manufacturing are also

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Authors and Affiliations

Shailendra Kumar
Mohd. Suhaib
Mohammad Asjad
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Abstract

Technological assurance and improvement of the economic efficiency of production are the

first-priority issues for the modern manufacturing engineering area. It is possible to achieve

a higher value of economic efficiency in multiproduct manufacturing by multicriteria optimization.

A set of optimality criteria based on technological and economic indicators was

defined with the aim of selecting the optimal manufacturing process. Competitive variants

and a system of optimization were developed and investigated. A comparative analysis of

the optimality criteria and their influence on the choice of optimal machining processes was

carried out. It was determine

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Authors and Affiliations

Alexey Kotliar
Yevheniia Basova
Vitalii Ivanov
Olena Murzabulatova
Svitlana Vasyltsova
Mariia Litvynenko
Olena Zinchenko
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Abstract

The paper proposes three multi-criteria decision-making (MCDM) methods for the selection

of an industrial robot for a universal, flexible assembly station, taking into consideration the

technical and performance parameters of the robot. Fuzzy versions of AHP and TOPSIS

methods as well as SMART were chosen from the variety of MCDM methods as they represent

different attitudes to analysis. In order to minimise the impact of the method applied on

the final decision, a list of results of the analyses has been developed and a final classification

has been made based on decision makers’ preferences concerning selected parameters of the

robot.

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Authors and Affiliations

Marcin Suszynski
Michał Rogalewicz
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Abstract

This paper presents a new welding quality evaluation approach depending on the analysis

by the fuzzy logic and controlling the process capability of the friction stir welding of

pipes (FSWoP). This technique has been applied in an experimental work developed by

alternating the FSW of pipes process major parameters: rotation speed, pipe wall thickness

and travel speed. variable samples were friction stir welded of pipes using from 485 to 1800

rpm, 4–10 mm/min and 2–4 mm for the rotation speed, the travel speed, and the pipe wall

thickness respectively. DMAIC methodology (Defining, Measuring, Analyzing, Improving,

Control) has been used as an approach to analyze the FSW of pipes, it depends on the

attachment potency and technical commonplace demand of the FSW of pipes process.

The analysis controlled the Al 6061 friction stir welded joints’ tensile strength. To obtain

the best tensile strength, the study determined the optimum values for the parameters from

the corresponding range.

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Authors and Affiliations

Ibrahim Sabry
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Abstract

This study demonstrates application of Lean techniques to improve working process in

a sewing machine factory, focusing on the raw material picking process. The value stream

mapping and flow process chart techniques were utilized to identify the value added activities,

non-value activities and necessary but non-value added activities in the current

process. The ECRS (Eliminate, Combine, Rearrange and Simplify) in waste reduction was

subsequently applied to improve the working process by (i) adjusting the raw material picking

procedures and pre-packing raw material as per demand, (ii) adding symbols onto the

containers to reduce time spent in picking material based on visual control principle, and

(iii) developing and zoning storage area, identifying level location for each row and also

applying algorithms generated from a solver program and linear programming to appropriately

define the location of raw material storage. Improvement in the raw material picking

process was realized, cutting down six out of 11 procedures in material picking or by 55%,

reducing material picking time from 24 to 4 min or by 83%. The distance to handle material

in the warehouse can be shortened by 120 m per time or 2,400 m per day, equal to 86%

reduction. Lean techniques

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Authors and Affiliations

Kotcharat Srisuk
Korrakot Y. Tippayawong
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Abstract

The presented method is constructed for optimum scheduling in production lines with parallel

machines and without intermediate buffers. The production system simultaneously

performs operations on various types of products. Multi-option products were taken into

account – products of a given type may differ in terms of details. This allows providing for

individual requirements of the customers. The one-level approach to scheduling for multioption

products is presented. The integer programming is used in the method – optimum

solutions are determined: the shortest schedules for multi-option products. Due to the lack

of the intermediate buffers, two possibilities are taken into account: no-wait scheduling,

possibility of the machines being blocked by products awaiting further operations. These two

types of organizing the flow through the production line were compared using computational

experiments, the results of which are presented in the paper.

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Authors and Affiliations

Marek Magiera

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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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