In this article we present an industrial application of our mathematical model that integrates
planning and scheduling. Our main objective is to concretize our model and compare the
reel results with the theoretical ones. Our application is realized on a conditioning line of
pharmaceutical products at the ECAM EPMI production laboratory. For this reason and to
save time, we used Witness simulation tool. It gives an overall idea of how the line works,
the Makespan of each simulation and it highlights areas for improvement. We looked for
the best resulting sequence which corresponds to the minest Makespan and total production
cost. Then this sequence is applied on the conditioning line of pharmaceutical products for
simulation. On the other hand, we program our mathematical model with the parameters of
the conditioning line under python in version 3.6 and we adopt a simulation/optimization
coupling approach to verify our model.
Studies linking the use of lean practices to company performance have been increasing as
markets are becoming more competitive and companies are eager for reducing waste and
therefore implementing the Lean Management (LM) philosophy to improve performance.
However, results from these studies have found various and different impacts and some light
is needed. Extant literature was reviewed and, to achieve the research objective, a metaanalysis
of correlations was carried out. The obtained results suggest a positive relationship
between some lean practices and performance measures. Furthermore, the presence of moderators
influencing the relationship between lean practices and performance outcomes is
highlighted in our results. To our best knowledge, this is the first research that proposes
a comparison of results from primary studies on Lean implementation, by analysing the
linear relationship between lean practices and enterprise performance. It fills this gap and
therefore represents an important contribution.
Maintenance of process plants requires application of good maintenance practice due to
a great level of complexity. From a plant maintenance point of view, the most significant activity
is turnaround, an activity carried out through project task with long planning process
period and very short execution period, which makes it one of the most complex projects
of maintenance in general. It is exactly this kind of maintenance that is based on multidisciplinarity
which has to be implemented through the system of quality management on all
levels of maintenance management. This paper defines the most significant factors determining
the process of turnaround projects quality management and its efficiency. Such relation
is observed through moderating influence of complexity on process management efficiency
in the turnaround project. The empirical research was conducted based on the survey of
turnaround project participants in five refineries in Croatia, Italy, Slovakia and Hungary.
For exploring the influence of research variables testing of the target relation is carried out
by applying logistical regression. Research results confirm the significance of complexity as
variable that significantly contributes to the project performance through the moderating
influence on success of the project, as well as the influence of an efficient management on
a plant turnaround project key results. Beside theoretical indications, practical implications
that arise from this research study mainly refers to management process of the industrial
plant maintenance project.
Today’s manufacturing environment is highly uncertain, and it is continuously changing. It
is characterized by shorter life cycles of products and technologies, shorter delivery times, an
increased level of customization at the price of a standard product, increased product variety,
quality as well as demand variability and intense global competition. Academicians, as well as
practitioners, agree that uncertainty will continue to grow in the twenty-first century. To deal
with the uncertainties in demand variation and production capacity a manufacturing system
is required which can be easily reconfigured when there is a need at low cost. A reconfigurable
manufacturing system is such a type of system.
In the present work, the concept of the reconfigurable manufacturing system has been discussed
and reviewed. It has been compared with dedicated systems and flexible manufacturing
systems. Part family formation and barriers of reconfiguration also have been discussed.
This work is an attempt to contribute to the conceptual systematization of the reconfigurable
manufacturing system and reconfigurability by synthesizing the vast literature available after
a systematic review.
The Industry 4.0 Concept assumes that the majority of industry’s resources will be able
to self-diagnose; this will, therefore, enable predictive maintenance. Numerically controlled
machines and devices involved in technological processes should, especially, have the facility
to predict breakdown. In the paper, the concept of a predictive maintenance system for
a vacuum furnace is presented. The predictive maintenance system is based on analysis of the
operating parameters of the system and on the algorithms for identifying emergency states in
the furnace. The algorithms will be implemented in the monitoring sub-system of the furnace.
Analysis of the operating parameters of vacuum furnaces, recorded in the Cloud will lead to
increased reliability and reduced service costs. In the paper, the research methodology for
identification of the critical parameters of the predictive maintenance system is proposed.
Illustrated examples of the thermographic investigation of a vacuum furnace are given.
The article deals with the subject of recruitment of a candidate for a creative team in manufacturing
company. For this purpose, a recruitment model has been developed. It consists
of three main stages: preliminary selection of candidates, assessment of the predispositions
of the selected candidates to work in a team and creative team building. The authors developed
recruitment model of a candidate for a creative team includes a set of tools supporting
the assessment at each stage. In the first stage concerning the preliminary selection, a competence
Questionnaire for working in a creative team, was developed. The second stage
includes the assessment of a candidate’s predispositions with the use of original tools for
assessing creativity, a tool supporting the monitoring of employees’ activity in proposing
innovative solutions and assessment center methodology. The principles of AC remained the
same. The competences that a creative team should possess were adjusted to the tool. Tasks
were proposed in order to assess these competences. The tool itself is ready for application.
In the subsequent stage of research, the tool in question will be tested in selected companies
and evaluated. The last stage concerns the team building. The tool used at this stage is
the Questionnaire for assessing the role in the team. While creating a recruitment model of
a candidate for a creative team, of the selected companies team leaders were consulted.
In the assembly industry, almost all components are outsourced or transferred to other
parties, in order to meet the need for supply. This is referred as outsourcing of production.
The outsourcing of assembly product components is based on a relationship model
between the contractor and the industry. However, there is no relationship or communication
pattern between the contractor or supplier and the assembler. Hence, in order to
accelerate line production and overcome problems with assembly components, the communication
path is shortened by providing a direct communication channel between the
assembler and the supplier or contractor, in order to communicate any problems that arise
during the assembly process by internal communication within the industry. The purpose
of this study is the design and development of a web-based software application electronic
data interchange (EDI) that can be used as a tool for communication between the assembler
and supplier. The EDI application provides formal communication between the assembly
industry and the contractor providing the components or parts needed in the assembly process.
The main purpose of using EDI technology is to help the assembler to communicate
the relevant documents to suppliers quickly, accurately and efficiently. The documents to
be communicated are in the form of reports or claims, and are related to non-conformities,
errors and component difficulties arising during the assembly process. This research novelty
is providing direct communication between assembly and supplier by using EDI application
that can give contribution in manufacturing area so it can accelerate the line production in
In the two-sided mixed-model assembly line, there is a process of installing two single stations
in each position left and right of the assembly line with the combining of the product model.
The main aim of this paper is to develop a new mathematical model for the mixed model
two-sided assembly line balancing (MTALB) generally occurs in plants producing large-sized
high-volume products such as buses or trucks.
According to the literature review, authors focus on research gap that indicate in MTALB
problem, minimize the length of the line play crucial role in industry space optimization.In
this paper, the proposed mathematical model is applied to solve benchmark problems of
two-sided mixed-model assembly line balancing problem to maximize the workload on each
workstation which tends to increase the compactness in the beginning workstations which
also helps to minimize the length of the line.
Since the problem is well known as np-hard problem benchmark problem is solved using
a branch and bound algorithm on lingo 17.0 solver and based on the computational results,
station line effectiveness and efficiency that is obtained by reducing the length of the line in
mated stations of the assembly line is increased.
In the existent world of continuous production systems, strong attention has been waged
to anonymous risk that probably generates significant apprehension. The forecast for net
present value is extremely important for any production plant. The objective of this paper
is to implement Monte Carlo simulation technique for perceiving the impact of risk and uncertainty
in prediction and forecasting company’s profitability. The production unit under
study is interested to make the initial investment by installing an additional spray dryer
plant. The expressive values acquied from the Monte Carlo technique established a range of
certain results. The expected net present value of the cash flow is $14,605, hence the frequency
chart outcomes confirmed that there is the highest level of certainty that the company
will achieve its target. To forecast the net present value for the next period, the results
confirmed that there are 50.73% chances of achieving the outcomes. Considering the minimum
and maximum values at 80% certainty level, it was observed that 80% chances exist
that expected outcomes will be between $5,830 and $22,587. The model’s sensitivity results
validated that cash inflows had a greater sensitivity level of 21.1% and the cash inflows for
the next year as 19.7%. Cumulative frequency distribution confirmed that the probability
to achieve a maximum value of $23,520 is 90 % and for the value of $6,244 it is about 10 %.
These validations suggested that controlling the expenditures, the company’s outflows can
also be controlled definitely.
This article intends to justify the gap in the research of similarity coefficient driven approaches
and cell formation problems (CFP) based on ratio data in cellular manufacturing systems
(CMS). The actual implication of ratio data was vaguely addressed in past literature, which
has been corrected recently. This research considered that newly projected CFP based on
ration data. This study further revealed the lack of interest of researchers in investigation for
an appropriate and improved similarity coefficient primarily for CFP based on ratio data.
For that matter a novel similarity coefficient named as Generalized Utilization-based Similarity
Coefficient (GUSC) is introduced, which scientifically handles ratio data. Thereafter
a two-stage cell formation technique is adopted. First, the proposed GUSC based method
is employed to obtained efficient machine cells. Second, a novel part allocating heuristic is
proposed to obtain effective part families. This proposed approach is successfully verified on
the test problems and compared with algorithms based on another similarity coefficient and
a recent metaheuristic. The proposed method is shown to obtain 66.67% improved solutions.
The paper presents an example of Instance-Based Learning using a supervised classification
method of predicting selected ductile cast iron castings defects. The test used the algorithm
of k-nearest neighbours, which was implemented in the authors’ computer application. To
ensure its proper work it is necessary to have historical data of casting parameter values
registered during casting processes in a foundry (mould sand, pouring process, chemical
composition) as well as the percentage share of defective castings (unrepairable casting defects).
The result of an algorithm is a report with five most possible scenarios in terms of
occurrence of a cast iron casting defects and their quantity and occurrence percentage in
the casts series. During the algorithm testing, weights were adjusted for independent variables
involved in the dependent variables learning process. The algorithms used to process
numerous data sets should be characterized by high efficiency, which should be a priority
when designing applications to be implemented in industry. As it turns out in the presented
mathematical instance-based learning, the best quality of fit occurs for specific values of
accepted weights (set #5) for number k = 5 nearest neighbours and taking into account the
search criterion according to “product index”.
Current fast development requires continuous improvement of employees’ skills and knowledge.
Therefore, companies are looking for the best way for improving the employees’ qualifications
and understanding of new concepts and tools which have to be implemented in
manufacturing areas. One method employs gamification for this purpose. The aim of this
paper is to present how gamification can increase the acquisition of knowledge concerning
lean manufacturing concept implementation. Gamification is an active learning approach for
people who will understand the subject easier by ‘feeling’ and ‘touching’ personally the analysed
problems. The research utilized a questionnaire which assessed the game participants’
engagement level. The assessment focused specifically on the participants’ motivation, cognitive
processing and social aspects. The participants were also examined before and after the
game in order to assess the increase of their understanding of different lean manufacturing
topics and tools. Five different games with different groups of participants were played. The
results confirmed the hypothesis that gamification has a positive impact on the knowledge
acquisition as well as on motivation, cognitive processing and social aspects. Finally, various
insights on how to better design, conduct and utilize gamification in the similar technical
context are presented.
Time-of-use (TOU) electricity pricing has been applied in many countries around the world
to encourage manufacturers to reduce their electricity consumption from peak periods to
off-peak periods. This paper investigates a new model of Optimizing Electricity costs during
Integrated Scheduling of Jobs and Stochastic Preventive Maintenance under time of-use
(TOU) electricity pricing scheme in unrelated parallel machine, in which the electricity price
varies throughout a day. The problem lies in assigning a group of jobs, the flexible intervals
of preventive maintenance to a set of unrelated parallel machines and then scheduling of jobs
and flexible preventive maintenance on each separate machine so as to minimize the total
electricity cost. We build an improved continuous-time mixed-integer linear programming
(MILP) model for the problem. To the best of our knowledge, no papers considering both
production scheduling and Stochastic Preventive Maintenance under time of-use (TOU) electricity
pricing scheme with minimization total Electricity costs in unrelated parallel machine.
To evaluate the performance of this model, computational experiments are presented, and
numerical results are given using the software CPLEX and MATLAB with then discussed.
Results of scientific researches show the trend of active using nitrides and borides of transition
metals and their combination in developing protective materials. While single elements
nitrides have been well studied, their multilayer modifications and combinations require
more detailed study. Physical-mechanical properties and structural-phase state of multilayer
coating according to the deposition conditions is an important task for the study.
It will be the analysis of physical-mechanical and electrical properties of coatings based on
refractory metals nitrides, their structure and phase composition and surface morphology
depending on the parameters of condensation. It was established the structure and behavior
of nano scale coatings based on refractory metals nitrides (Ti, Zr) depending on the size
of nano grains, texture, stress occurring in coatings.
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