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.
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.
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.
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,
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.
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
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.
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.
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.
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.
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.
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