Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, forecasting, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.
The main purpose of Management and Production Engineering Review is to publish the results of cutting-edge research advancing the concepts, theories and implementation of novel solutions in modern manufacturing. Papers presenting original research results related to production engineering and management education are also welcomed.
We welcome original papers written in English. The Journal also publishes technical briefs, discussions of previously published papers, book reviews, and editorials.
Letters to the Editor-in-Chief are highly encouraged.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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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