The article includes presentation of fuzzy numbers application in projects prioritizing at
manufacturing and service providing enterprises. The following criteria have been applied
as a basis for projects prioritizing analysis in enterprise: NPV index, linked with the enterprise strategic aims, project execution cost, project time, project scope and risk. As the
criteria selected were of measurable and non-measurable character in projects prioritizing
evaluation, the fuzzy decision making system has been developed, in which a linguistic value
has been defined for each criterion of projects prioritizing. Knowledge base has been developed afterwards, presenting cause-effect dependencies in projects prioritizing. Knowledge
base consisted of conditional rules. Fuzzy system of decision making in project prioritizing
has been developed in MATLAB application.
The decision making fuzzy system established, constitutes an efficient tool for projects prioritizing, on the basis of criteria given and concluding system developed. The obtained analysis
results provide basis for the decision making parties to set the projects execution sequences.
Make-To-Stock (MTS) and Make-To-Order (MTO) are the two traditional strategies in
production management. In the case of the MTS there is a growing demand for a new
approach, which is called Make-To-Availability (MTA) strategy. The paper characterizes and
compares the MTS and MTA strategies. The comparative analysis based, among others, on
computational experiments carried out in a computer program developed in Microsoft Visual
Studio 2017 Environment was presented. The models have been prepared for both strategies
with the same assumptions: external conditions (market demand) and internal conditions
(structure of the production process). The investigation of how the strategies respond to
various scenarios of demand intensity was done. The simulation models were prepared and
validated for the case of the production line in one of the industrial automation company.
The research shows that the use of the MTA strategy in the majority of cases gives much
better results than the use of the MTS strategy due to the minimization of storage costs and
the costs of non-fulfillment of the customers’ demand. The directions for further research
were also presented.
This paper focuses on the analysis of selected risks as part of investments in the power
engineering at the initial (tender) stage of the life cycle in the context of the method of
project management by the Contractor. The study was carried out on the basis of an
analysis of over 500 tenders in the power engineering, from the last 5 years, taking into
account future forecast data. The analysis carried out in this article was aimed at achieving
specific and unique goals and results aimed at creating a useful product, which is the
Contractor’s offer in the power engineering, taking into account the most significant risks.
The result of this article is to support the project team in implementing risk management
in the project at the tender stage. For this purpose, the risks with their basic parameters
were defined, which allowed for the development of a risk matrix taking into account the
data obtained in the tender procedures of leading electric power distributors. Based on
the proposed risk quantification criteria, a list of remedial actions was prepared for all risk
types listed in this article. In addition, the aspects of possible elimination/reduction of the
impact of the most significant risks that occur at the analyzed stage of the investment life
cycle were developed.
The industry transformation to the digital model 4.0 will be a significant change from
the perspective of the organisation and processes. In the context of the above, the research
was undertaken, the principal aim of which constituted the attempt to answer the question
concerning the technological advancement level of manufacturing companies operating in
the agricultural machinery sector. It is about identifying what adaptation projects in the
context of the fourth generation industry era should be undertaken by the Polish manufacturers operating in the agricultural machinery sector. The achievement of the main
objective required formulation and implementation of partial objectives, which, according
to the authors, include: C(1) – defining the Industry 4.0 axiom merit; C(2) – using the
subject literature reconstruction and interpretation methods – nomination of areas, on the
one hand essential from the perspective of the model 4.0, and on the other hand those that
may demonstrate the maturity in the domain of the adopted desiderata; C(3) – compilation
of the research model, in the form of an assessment sheet, being a resultant of literature
studies and research conducted among deliberately selected domain experts; C(4) – based
on the selected indicators, the technological advancement level recognition of the studied
companies; specification of a technological gap (questioning among experts).
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 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.
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.
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 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.
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 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.
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.
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 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.
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,
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.
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 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.
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.
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.
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.
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.
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.
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.