Management and Production Engineering Review

Content

Management and Production Engineering Review | 2020 | vol. 11 | No 2

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Abstract

Production companies face the challenge of choosing a suitable process optimization method

from a variety of methods, even though their effect on operational processes is uncertain.

This study shows, using a statistical hypothesis test, the impact of the methods Kanban

and Standard Worksheet on an autonomous team in comparison to a team that applies

these methods. For this purpose, 44 companies – of different size and operating in various

industries – across Germany completed a business game and generated data regarding the

KPIs adherence to delivery date, number of reworks and inventory costs. Based on these

data, the team’s performance could be ascertained and compared with each other.

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Authors and Affiliations

Patrick Poetters
Robert Schmitt
Bert Leyendecker
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Abstract

Lean management has become a much-researched topic in operations management. Beyond

its technical aspects, nowadays the analysis of soft factors (corporate culture, organization,

management, human resource management, knowledge transfer practices) have come to the

fore. However, there are few sources available to the lean organization to find out what organizational

changes are taking place alongside the lean application, and what organizational

structures are being developed. In our study first we deal with the literature-based concepts

of lean organizational structure and with the international examples, and then through five

Hungarian corporate solutions and with help of the literature of organizational theories we

synthesize the lean organizational forms.

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Authors and Affiliations

Zsuzsanna Bathory
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Abstract

This study builds on an existing structural model developed to examine the influence of

leadership and organizational culture on innovation and satisfaction of engineers in Australian

public sectors (APS). The objective of this study is to increase the understanding of

innovation process with a focus on causal relationships among critical factors. To achieve this

objective, the study develops an assessment approach to help predict creativity and work

meaningfulness of engineers in the APS. Three quantitative analysis methods were sequentially

conducted in this study including correlation analysis, path analysis, and Bayesian

networks. A correlation analysis was conducted to pinpoint the strong association between

key factors studied. Subsequently, path analysis was employed to identify critical pathways

which were accordingly used as a structure to develop Bayesian networks. The findings of

the study revealed practical strategies for promoting (1) transformational leadership and (2)

innovative culture in public sector organizations since these two factors were found to be key

drivers for individual creativity and work meaningfulness of their engineers. This integrated

approach may be used as a decision support tool for managing the innovation process for

engineers in the public sectors.

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Authors and Affiliations

Warit Wipulanusat
Kriengsak Panuwatwanich
Rodney A. Stewart
Piya Parnphumeesup
Jirapon Sunkpho
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Abstract

In the article, the significance and essence of management of intelligent manufacturing in

the era of the fourth industrial revolution has been presented. The current revolution has

a large impact on the operation of the company. Through the changes resulting from the

application of modern technologies, production processes are also undergoing revolutions,

which results in changes in such indicators of business development. Management of intelligent

manufacturing is also a challenge for socially responsible activities; due to solutions of

Industry 4.0, enterprises directly and indirectly influence environmental protection, which

results in benefits for all mankind. In the article, the analysis and assessment of management

of intelligent manufacturing, using modern technologies during the production process,

has been carried out, with particular emphasis on the components of management such as:

monitoring, control, autonomy, optimization. Moreover, the impact of the above components

of management on changes in the following indicators (KPI – Key Performance Indictors)

has been evaluated, i.e. (1) quality, (2) rapidity of the production process implementation,

(3) performance and (4) productivity, (5) decrease in waste generated during the technological

process and (6) amount of consumed electricity. For the purposes of conducting the

research, a case study has been used, developed due to the information shared by the company

manufacturing machinery and equipment for the polymer processing industry, in which

intelligent solutions of Industry 4.0 are being applied. The presented article is a significant

contribution to the current development of knowledge in the field of implementing Industry

4.0 solutions for polymer processing. The article is a combination of theoretical and practical

knowledge in the field of management and practical industrial applications. It refers to the

most current research trends.

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Authors and Affiliations

Katarzyna Łukasik
Tomasz Stachowiak
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Abstract

The main aim of this research is to compare the results of the study of demand’s plan and

standardized time based on three heuristic scheduling methods such as Campbell Dudek

Smith (CDS), Palmer, and Dannenbring. This paper minimizes the makespan under certain

and uncertain demand for domestic boxes at the leading glass company industry in Indonesia.

The investigation is run in a department called Preparation Box (later simply called PRP)

which experiences tardiness while meeting the requirement of domestic demand. The effect

of tardiness leads to unfulfilled domestic demand and hampers the production department

delivers goods to the customer on time. PRP needs to consider demand planning for the

next period under the certain and uncertain demand plot using the forecasting and Monte

Carlo simulation technique. This research also utilizes a work sampling method to calculate

the standardized time, which is calculated by considering the performance rating and

allowance factor. This paper contributes to showing a comparison between three heuristic

scheduling methods performances regarding a real-life problem. This paper concludes that

the Dannenbring method is suitable for large domestic boxes under certain demand while

Palmer and Dannenbring methods are suitable for large domestic boxes under uncertain

demand. The CDS method is suitable to prepare small domestic boxes for both certain and

uncertain demand.

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Authors and Affiliations

Filscha Nurprihatin
Ester Lisnati Jayadi
Hendy Tannady
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Abstract

Today, the changes in market requirements and the technological advancements are influencing

the product development process. Customers demand a product of high quality and fast

delivery at a low price, while simultaneously expecting that the product meet their individual

needs and requirements. For companies characterized by a highly customized production, it

is essential to reduce the trial-and-errors cycles to design new products and process. In such

situation most of the company’s knowledge relies on the lessons learnt by operators in years

of work experience, and their ability to reuse this knowledge to face new problems. In order

to develop unique product and complex processes in short time, it is mandatory to reuse

the acquired information in the most efficient way. Several commercial software applications

are already available for product lifecycle management (PLM) and manufacturing execution

system (MES). However, these two applications are scarcely integrated, thus preventing an

efficient and pervasive collection of data and the consequent creation of useful information.

The aim of this paper is to develop a framework able to structure and relate information

from design and execution of processes, especially the ones related to anomalies and critical

situations occurring at the shop floor, in order to reduce the time for finalizing a new product.

The framework has been developed by exploiting open source systems, such as ARAS

PLM and PostgreSQL. A case study has been developed for a car prototyping company to

illustrate the potentiality of the proposed solution.

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Authors and Affiliations

Giulia Bruno
Alberto Faveto
Emiliano Traini
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Abstract

Digitalization and sustainability are important topics for manufacturing industries as they

are affecting all parts of the production chain. Various initiatives and approaches are set

up to help companies adopt the principles of the fourth industrial revolution with respect

sustainability. Within these actions the use of modern maintenance approaches such as

Maintenance 4.0 is highlighted as one of the prevailing smart & sustainable manufacturing

topics. The goal of this paper is to describe the latest trends within the area of maintenance

management from the perspective of the challenges of the fourth industrial revolution and

the economic, environmental and social challenges of sustainable development. In this work,

intelligent and sustainable maintenance was considered in three perspectives. The first perspective

is the historical perspective, in relation to which evolution has been presented in the

approach to maintenance in accordance with the development of production engineering. The

next perspective is the development perspective, which presents historical perspectives on

maintenance data and data-driven maintenance technology. The third perspective, presents

maintenance in the context of the dimensions of sustainable development and potential opportunities

for including data-driven maintenance technology in the implementation of the

economic, environmental and social challenges of sustainable production.

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Authors and Affiliations

Małgorzata Jasiulewicz-Kaczmarek
Stanisław Legutko
Piotr Kluk
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Abstract

A project scheduling problem investigates a set of activities that have to be scheduled

due to precedence priority and resource constraints in order to optimize project-related

objective functions. This paper focuses on the multi-mode project scheduling problem concerning

resource constraints (MRCPSP). Resource allocation and leveling, renewable and

non-renewable resources, and time-cost trade-off are some essential characteristics which are

considered in the proposed multi-objective scheduling problem. In this paper, a novel hybrid

algorithm is proposed based on non-dominated sorting ant colony optimization and genetic

algorithm (NSACO-GA). It uses the genetic algorithm as a local search strategy in order to

improve the efficiency of the ant colony algorithm. The test problems are generated based on

the project scheduling problem library (PSPLIB) to compare the efficiency of the proposed

algorithm with the non-dominated sorting genetic algorithm (NSGA-II). The numerical result

verifies the efficiency of the proposed hybrid algorithm in comparison to the NSGA-II

algorithm.

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Authors and Affiliations

Jafar Bagherinejad
Fariborz Jolai
Raheleh Abdollahneja
Mahnaz Shoeib
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Abstract

The current industrial constraints on production systems, especially availability problems

are complicating maintenance managers’ mission and making longer and further performance

improvement process. Dealing with these problems in a wiser managerial vision respecting

sustainability dimensions would be more efficient to optimize all resources. In this paper, and

after addressing the lean/sustainability challenge in a the literature to define main research

orientations and critical points in manufacturing and then maintenance specific context, two

case studies have been conducted in two production systems in Morocco and Canada, within

the objective to set a clearer scene of the lean philosophy implementation in maintenance

and within the sustainability scope from an empirical perspective. To activate the social dimension

being often non-integrated in the lean/sustainability initiatives, the article authors

reveal an original research direction assigning maintenance logistics as the leading part of our

approach to cover all sustainability dimensions. Furthermore, its management is discussed

for the first time in a sustainable framework, where the authors propose a new model considering

the lean/sustainable perspective and inspired by the rich Human-Machine interaction

memory to solve daily maintenance problems exploiting the operators’ experience feedback.

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Authors and Affiliations

Salima Hammadi
Brahim Herrou
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Abstract

Scheduling of multiobjective problems has gained the interest of the researchers. Past many

decades, various classical techniques have been developed to address the multiobjective problems,

but evolutionary optimizations such as genetic algorithm, particle swarm, tabu search

method and many more are being successfully used. Researchers have reported that hybrid

of these algorithms has increased the efficiency and effectiveness of the solution. Genetic

algorithms in conjunction with Pareto optimization are used to find the best solution for

bi-criteria objectives. Numbers of applications involve many objective functions, and application

of the Pareto front method may have a large number of potential solutions. Selecting

a feasible solution from such a large set is difficult to arrive the right solution for the decision

maker. In this paper Pareto front ranking method is proposed to select the best parents for

producing offspring’s necessary to generate the new populations sets in genetic algorithms.

The bi-criteria objectives minimizing the machine idleness and penalty cost for scheduling

process is solved using genetic algorithm based Pareto front ranking method. The algorithm

is coded in Matlab, and simulations were carried out for the crossover probability of 0.6,

0.7, 0.8, and 0.9. The results obtained from the simulations are encouraging and consistent

for a crossover probability of 0.6.

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Authors and Affiliations

B.V. Raghavendra

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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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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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