Method for analysing bottlenecks and improvements using simulation

ILIJA KAROV
METHOD FOR ANALYSING BOTTLENECKS AND
IMPROVEMENTS USING SIMULATION
ABSTRACT: In this graduation thesis the method of simulation is
described as one of the methodologies for bottlenecks
analysis and process improvement. Further in the
content are presented the bottleneck types, the
reasons for their occurrence as well as the methods for
identifying the bottleneck in the process. The
emphasis, with the aim of this paper, is the
improvement and analysis of the bottlenecks using the
simulation method. With the help of simulation
software - Technomatix Plant Simulation, a
production process for wooden chairs has been
programmed for analysis. With the Bottelenck
Analyzer tool the process is analyzed and the
bottlenecks are identified. The data obtained from the
analyzes were used to improve the model, by
experimenting with the basic model. In order to get an
improved model, more experiments were made. From
the experiment, more improved models have been
obtained with increased productivity.
KEY WORDS: Bottleneck, simulation, process, analysis, Plant
Simulation.

1. Introduction
The aim in this graduate thesis is the improvement of processes through bottleneck analysis. There
are several methods for identifying and analyzing bottlenecks. This paper presents the simulation method
using the tools of simulation software Tecnomatix Plant Simulation, part of Siemens PLM, software for
modeling, simulation, analysis, visualization and optimization of production systems and processes, the
flow of materials and logistics operations.
Business processes are of great importance to a company, because with well-designed processes it
increases their efficiency and effectiveness. With the help of the software and the tools it contains, we
will analyze in detail the processes in the production of wooden chairs. By creating the model and
analyzing it, we will identify bottlenecks that reduce productivity in production. Process analysis and
bottlenecks identification is important, as there is almost no production process in which an operation is
working with full capacity and still slows down the whole production. In order to present the way of
dealing with such situations, in this paper will be presented the ways of optimizing and reducing
bottlenecks through the production processes, with a simulation model.

2. Bottlenecks
Improving the efficiency in production and other work processes is an important part of
improving the overall performance and productivity of the company, as well as meeting customer
requirements. While there are many different things that can cause slowing and disrupting of
work processes, bottlenecks are among the most serious.
"An activity that delays the operation of the system and reduces the overall efficiency
of the process is known as bottleneck".
The term "bottleneck" is used to describe the point of congestion in any system, from a
production assembly line to a computer system. In such a system, there is always a process, a task,
a machine, etc. which is a limiting factor that prevents greater flow and thus determines the
capacity of the entire system. For example, a production company has different production lines,
each of which is related to each other, i.e. work produced by one unit is the input to the other unit.
Figure 1 represents the idea of what a bottleneck means in a process, where it is clearly
shown that the input rate is higher than the output rate. In such a case, if a process is interrupted
or stopped for some reason, it directly affects other production processes, causing a lower output
level due to the bottleneck.
Figure 1. Example of bottleneck
Bottleneck
Flow of the material

 Bottleneck Detection Methods
Some of the bottleneck detection methods with their characteristics and measurements are shown
in Table 1.1.
Table 1
METHOD CHARACTERISTIC MEASUREMENT
1.
Queue Size before
the machine
The bottleneck is the machine which has the
longest queue before the machine, waiting to be
processed.
Quantity of
products
2. Utilization Factor
The percentage of time that the machine is working
with regards to the system’s overall time is
measured. The machine with highest utilization is
the bottleneck.
Percentage
3.
Waiting Time before
the machine
It is measured on how long a product will wait in
queue to be processed.
Time
4.
Shifting Bottleneck
Method
Sum of duration of the active state without
interruption in a period of time for a production
station. Even though instantly some machines can
be the bottleneck, the one with the highest value is
the bottleneck.
Time
5.
Computer
simulation
Virtual process model is created by setting realistic
parameters and working conditions. Computer
analysis of processes is performed and more
statistics are obtained. In this way, the bottleneck
in the production process is visually easy to see.
Various
statistics:
(time of work,
waiting time,
pause, pause)

3. Мethod for analysing bottlenecks and improvements using
simulation
3.1. Method of simulation
Simulation is a virtual display or imitation of the functioning of a real process or system.
The simulation process first requires the development of a model that represents the key features,
behaviors, and functions of the selected physical or abstract system or process. The model
represents the system itself, while the simulation represents the work of the system over time.
Hence, the simulation can be used in many contexts, such as simulation for performance
optimization of the technology, in the design phase of a project, testing, training, education. Often,
computer experiments are used to study simulation models.
The simulation model is a process of creating and analyzing a prototype of a real
model to see its performance in the real world. Performing experiments and setting
up different situations gives information about the behavior of the system in terms of
changes and ways to improve it.

Figure 2. Seven-step approach to conducting a successful simulation study
Formulate the problem
Collect information/Data and
construct a Conceptual Model
Program the model
( simulation)
Design, conduct and analyze
simulation experiments
Document and present the simulation
results
Is it the simulation
model valid?
Is it the Conceptual
Model valid?
yes
no
no
yes

3.2. Task: Manufacture for producing chairs
One businessman wants to open a chairs manufacturing plant. Simple, school chairs. You are
asked to do a project on how to organize the production. The technology is bought from Germany and
wants to use it here. The times for each of the operations are given in minutes.
The bars I would buy are 2 meters in size. They should be cut to a size of 1.80 cm [2:30], then
grind [3:00] and twisted [4:00]. The bars are released for cutting every 15 minutes. In painting are going
10 bars at once and it lasts 10 minutes. 12% of the painted are not of the proper quality and are again
hand-painted in 1 minute.
The seats and the back are made of wood. The first operation for the two pieces is cutting 2
[12:30], then pressing [30:00].
• At the first assembly place, two metal-shaped bars, a seat and 4 bolts are connected in 13:00
minutes.
• The second assembly satiation merges the previous sub-assemble with the backrest and 2
screws, during a normal distribution of 3 minutes and μ = 1: 00.
• At the third assembly station, are put 4 rubber feet on the metal legs in 2 minutes.
• The stool goes to the control [00:15], and on the pack [6:00] in boxes of 5 pieces in one. They
are stored in the warehouse.
People are needed at all assembly stations, control and packaging.
The system should be tested in 30 days, without work on Saturdays and Sundays, with working
hours from 7:00 - 15:30, with 30 minutes of breaks.
The availability of all stations is 90%, with MTTR = 2 minutes.

 List of components
The list of components contains information about the resources we need to implement
the process successfully. It also contains comments that explain the participation of resources in
the process, why are they needed and what their role is. In the following table 2, is displayed a list
of components for the production process.
Таble 2. List of components
Components Details
Active/
Inactive
Comment
Material
Steel bars Inactive
The material is not
important for this
simulation/not related
for making of the chair
Wood Inactive
Bolts Inactive
Rubber Inactive
Container
Inactive
Machine
Cutting machine for
bars
Active
Processes are
important in this
simulation/the
machines that are
needed for making the
chair
Grinding machine Active
Bending machine Active
Painting machine Active
Hand painting
machine
Active
Cutting machine for
seat
Active
Cutting machine for
backrest
Active
Pressing machine for
seat
Active

Pressing machine for
backrest
Active
Assemble
Assemble 1 Active
Processes that add
value to the product
Assemble 2 Active
Assemble 3 Active
Control
Active
Packaging
Active
 Flow diagram
The flow diagram presents visually the flow of the processes, starting from the beginning
to the end of the model. Figure 3 shows the flowchart for making a chair.

Cutting seat Cutting Cutting backrest
Grinding
Bending
Painting
Is it painted well?
Pressing seat
Pressing
backrest
Assembly station
1
Hand painting
Assembly station
2
Assembly station
3
Control
Packaging
no
yes
Figure 3. Flow chart

 Sequence of events
The sequence of events represents the sequence of events in production, followed by an
explanation of what kind of event it is. Data such as quantity, mass, position, number of executors
and times per minute are also used. In table 3, you can see the sequence of events for the given
process.
Sequence of events Mark:
Condition: What is recording: No. of records:
present suggested material workers resources
PRODUCT: Chairs Department: /
Recording starts with: Cutting
Recording ends with: Packaging
No. Events
Operation
Control
Transport
Downtime
Storage
Length
[m]
Quantity
Weight
[kg]
Position
No.
of
executors
Times (min)
t
pz
t
t
t
p
1. Cutting bars     02:30
2. Grinding bars     03:00
3. Bending bars     04:00
4. Mechanical painting     10:00
5. Control    
6. Hand painting     01:00
7. Cutting backrest     12:30
8. Pressing backrest     30:00
9. Cutting seat     12:30
10.Pressing seat     30:00
11.Assembly station 1     13:00
12.Assembly station 2     03:00
13.Assembly station 3   02:00
14.Control   0:15
15.Packaging   06:00
Remarks: Sum before
Sum after
Difference
Date: Record: Approved:

Table 3. Sequence of events
 Creation of model
This is the phase in which the simulation model is actually created. For the creation of
the simulation model as already mentioned, the Plant Simulation software will be used. At this
stage, ideas from the concept model, data and distributions in the software selected for
programming the virtual virtual model are transmitted. In Figure 4, the basic simulation model
is shown in standby, and in Figure 5 the basic model is presented after the simulation.
Figure 4. Basic simulation model

 Verification
Verification as a process of evaluating the system whether it meets the required conditions
can best be confirmed experimentally. By creating a process model, we can test it and see if the
system works properly. The results obtained from the simulated model demonstrate its reliability
and the verification process is carried out. Figure 6 shows the comparison of input and output in
the basic model after the simulation.
Figure 5. Comparation of input and output in the basic model
By comparing these data, it can be noticed that the output from the station "Pivoting seat" (324
pieces) coincides with the final output (64 · 5 = 320), since the difference of 4 pieces is due to the
completion of the duration of the simulation .
After the verification is made, experimenting and finding the appropriate combination can be
continued in order to meet the expectations of the investor.
 Validation
Validation is deciding whether the simulation model is an accurate representation of the
real system. In order to perform the validation, it is necessary to compare the output information
of the simulation with the observed information about the real system. Predicting the model
should be compared to the actual performance of the system. In this case, we can observe that
validation is not possible to implement, because we are creating a completely new model, for
which there is no real system with which we could compare the obtained data.

3.3. Methodology for analyzing bottlenecks
In each production system, there are one or more processes that cause downtime in
production. Such operations or processes are known as bottlenecks. There are many ways to
analyze and identify them. In this production process, the use of BottelneckAnalyzer as part of the
Plant Simulation program will be described as a tool for analysis.
The methodology for analysis of bottlenecks consists of the four phases shown in Figure 7:
 Analyze the model;
 Identification of the bottleneck;
 Improving the model;
 Analyze the improvement.

Figure 6. Methodology for analyzing bottlenecks
Analyzing the simulation model
Identification of the bottlenecks
Analyze the improvement
Are we satisfied with
the improvement?
yes
Start
Improvement of the model
Finish
no

 Аnalyze the model
In the first phase, as the name itself says, an analysis of the simulated model is carried out.
The analysis in the software is done using the BottleneckAnalyzer tool. All the elements in the
model are analyzed and a report is provided containing data on the way each machine works,
where it has the most waiting, which machine is the most comprehensive, which is blocked or
stopped. Before we start analyzing the simulation, the following steps need to be performed:
1. Drag the tool to the desktop
First, we need to download the BottelneckAnalyzer tool located in the Toolbox menu in the Tools
section and transfer it to the desktop (Figure 8).
Figure 7. Set the tool “BottelneckAnalyzer” on the working frame
2. Playing a simulation
Once the tool is set on the working frame, next step is release the simulation and wait for it to
end (Figure 9).
3. Activate the BottelneckAnalyzer tool After the simulation finishes, the Bottelnec kAnalyzer
tool opens and the Analyse field is selected. After the activation of the tool, diagrams for each
station describing the operation automatically appear (Figure 9 and Figure 10).
Figure 8. Basic model with finished simulation and diagram for each operation

Figure 9. Legend for the data in the diagram from BottelneckAnalyzer
 Identification of the bottleneck
In the second phase, based on the simulation model and the data obtained from the simulation,
we detect the problem, that is the bottleneck. The first and the second phase are closely connected,
that is, according to the data obtained from the analysis of the simulation model, detection of the
bottleneck processes is performed.
To identify the bottleneck in the given process, we will first analyze in detail the operations with
their results shown by the program itself through the Statistic Report function (Figure 11).
Figure 10. Report from function “Statistic Report”

The next thing to do is to present a schematic simulation model, as shown in Figure 11,
and using the data obtained from the statistical report created by the program itself, enables easier
and more accurate detection of the bottlenecks.
Backrest
Seat
Cutting
backrest
Cutting
seat
Pressing
backrest
Pressing seat
Bars
Cutting
Grinding
Bending
Painting Assembly
3
Hand painting
Buffer
Assembly
1
Assembly
2
Control
Packing
Warehouse
blocked
blocked
blocked
blocked
blocked
blocked
waitng
waiting
waiting waiting
waiting
work
work
Work/blocked
Work/blocked
!
!
!
Figure 11. Schematic view of the simulation model
From the data obtained from the statistical report, it can be seen that there are more bottlenecks
in the considered process:
• The machine for pressing backrest
• The machine for pressing the seat
• Assembly station 1
Pressure stations represent bottlenecks because they operate at full capacity while the cutting
stations that precede them are blocked by them.
The assembly station 1 is a bottleneck because it blocks the stations that precede it while it waits
for the material from the station for pressing the seat.
After determining the bottlenecks in the simulation model, we approach the third phase of the
methodology, that is to create improvements to the basic model.

 Improving the model and analyzing the improvement
The third and fourth stages of the analysis methodology are closely related to each other. Since
three bottlenecks are detected in the given process, the improvements for each of them will be
presented in parallel along with the analyzes of each improvement. These are in fact the most
important stages in resolving the problem and eliminating the bottleneck in the process. The
number of improvements created depends on how satisfied we are with the improved model. If
the improved model meets our expectations, the next step is implementing the improvement.
After we have implemented the improvement, we are re-analyzing the new model with
improvement, comparing the data from the new model with the initial model, and if we are
satisfied with the achieved result, we finish with the analysis and implement the improvement. If
we are not satisfied, we repeat the steps again. That is, we create new improvements until we
achieve the desired results.
Improvement 1: Adding another assembly station 1
The first improvement will be achieved by eliminating one of the bottlenecks, that is, the mounting
station 1. The improvement is done by placing another mounting station in the simulation model
(Figure 12), which would be expected to reduce the blockage at the stations that preceded them.
Figure 12. Improvement 1: Adding another assembly station 1
In order to see the result of the improvement made, it is necessary to re-analyze with the
Bottleneck Analyzer and review the data obtained from the new statistical report (Figure 13).

Figure 13. Statistic Report from improved model 1
A comparison of the data obtained from the basic model is made, as shown in Table 2, whereby
the results of the improved improvement are easily seen.

Table 2. Comparison of statistics reports between the basic model and the improved model 1
Working Waiting Blocked
Station basic model 1 basic model 1 basic model 1
Bending 6.61% 7.80% 1.14% 1.28% 14.94% 13.61%
Cutting 4.14% 4.89% 0.71% 0.73% 17.69% 16.92%
Grinding 4.96% 5.86% 0.95% 1.05% 16.75% 15.76%
Bars 0.00% 0.00% 1.01% 1.04% 98.99% 98.96%
Painting 1.63% 1.92% 1.53% 6.19% 19.50% 82.02%
Hand painting 0.67% 0.73% 3.74% 2.62% 85.75% 19.24%
Preparation for paiting 0.16% 0.19% 30.19% 35.96% 69.64% 63.85%
Dismantle Station 0.16% 0.19% 4.02% 7.14% 95.82% 92.67%
Source1 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Buffer 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Backrest 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Seat 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Cutting backrest 9.28% 13.32% 0.00% 0.00% 13.39% 9.35%
Pressing backrest 22.20% 1.06% 0.13% 5.45% 0.44% 18.64%
Assembly station 1 9.64% 5.42% 11.21% 17.03% 1.60% 0.00%
Bolts 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Buffer1 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Source41 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Packaging 0.88% 0.99% 21.65% 21.54% 0.00% 0.00%
Control 0.18% 0.21% 22.30% 22.22% 0.09% 0.15%
Source5 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Warehouse 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Flow Control 0.00% 0.00% 1.60% 0.00% 21.13% 0.00%
Cutting seat 9.33% 10.45% 0.00% 0.14% 13.37% 12.25%
Pressing seat 22.29% 25.02% 0.11% 0.14% 0.33% 0.00%
Buffer2 0.00% 0.00% 4.11% 7.13% 95.89% 92.87%
WorkerPool 0.00% 0.00% 14.55% 18.07% 10.60% 7.09%
Assembly station 11 / 5.39% / 17.19% / 0.00%

From the comparison we can observe that the stations in the improved model 1 have a higher
percentage of working and a smaller percentage of blockage compared to the basic model, and
that the waiting at some stations is reduced. It can also be seen that the number of output boxes
increased in relation to the basic model. Regarding the operation and blockage of the assembly
station 1, we can notice that there are no improvements, but the work has been splited between
the two assembly stations in the improved model 1. (assembly station 1, assembly station 11).
The reason for this is the bottleneck that is located at the station pressing the seat. Therefore the
next step is to make a new improvement.
 Improvement 2: Add another station for pressing the seat.
With the second improvement of the already improved model 1, we add another station for
pressing the seat (Figure 14). This improvement is expected to reduce blockage at stations,
increase work and reduce waiting at assembly stations.
Figure 14. Improvement 2: Add another station for pressing the seat.
The procedure for checking the results of the improvement made is the same as described above
in the improved model 1. First, the analysis with the Bottleneck Analyzer tool is performed, and
then the statistical report is generated. Table 3 will show the comparison of the improved model
1 with the improved model 2.

Табела 3. Comparison of statistics reports between the improved model 1 and the improved
model 2
Station model 1 model 2 model 1 model 2 model 1 model 2
Bending 7.80% 9.72% 1.28% 1.54% 13.61% 11.43%
Cutting 4.89% 6.09% 0.73% 0.91% 16.92% 15.54%
Grinding 5.86% 7.30% 1.05% 1.33% 15.76% 14.04%
Bars 0.00% 0.00% 1.04% 1.36% 98.96% 98.64%
Painting 1.92% 2.41% 6.19% 19.85% 82.02% 67.88%
Hand painting 0.73% 0.74% 2.62% 4.91% 19.24% 16.94%
Preparation for painting 0.19% 0.24% 35.96% 40.38% 63.85% 59.38%
Source1 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Buffer 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Backrest 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Seat 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Bolts 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Buffer1 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Source41 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Packaging 0.99% 0.99% 21.54% 21.54% 0.00% 0.00%
Control 0.21% 0.21% 22.22% 22.25% 0.15% 0.12%
Source5 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Warehouse 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Cutting seat 10.45% 16.29% 0.00% 0.00% 12.25% 6.40%
Buffer2 0.00% 0.00% 7.13% 20.69% 92.87% 79.31%
Worker Pool 0.00% 0.00% 18.07% 16.96% 7.09% 8.19%
Buffer3 0.00% 0.00% 100.00% 56.47% 0.00% 43.53%
Buffer4 0.00% 0.00% 23.29% 100.00% 76.71% 0.00%
Buffer6 0.00% 0.00% 100.00% 27.28% 0.00% 72.72%
Pressing seat 25.02% 24.99% 0.14% 0.16% 0.00% 0.00%

Figure 16. Statistic report from the improved model 3
From the comparison it can be noted that the working percentage at assembly station 1 and
assembly station 11 is increased. Blocking at stations is also reduced, which contributes to the
reduction of blockages and to the processes that precede them. However, it is noticed that there
were no improvements in relation to the output, i.e the number of final boxes remained
unchanged. Given that an investment has been made, without increasing the productivity of the
process, it is necessary to make another improvement.
 Improvement 3: Add another station for pressing the backrest
Since the desired results are not obtained, a new improvement is started and thus the elimination
of the last bottleneck detected on the begining, and is located at the station for pressing the
backrest. Figure 15 shows the improved model 3, followed by the statistical report in Figure 16.
Figure 15. Improvement 3: Add another station for pressing the backrest
Comparison between the reports is shown in Table 4.

Table 4. Comparison of statistics reports between the improved model 2 and the improved
model 3
Bending 9.72% 15.59% 1.54% 2.00% 11.43% 5.09%
Cutting 6.09% 9.76% 0.91% 0.91% 15.54% 11.87%
Grinding 7.30% 11.70% 1.33% 1.65% 14.04% 9.31%
Bars 0.00% 0.00% 1.36% 1.36% 98.64% 98.64%
Painting 2.41% 3.88% 19.85% 22.67% 67.88% 63.59%
Hand painting 0.74% 1.32% 4.91% 6.02% 16.94% 15.24%
Source1 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Buffer 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Backrest 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Seat 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Bolts 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Buffer1 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Source41 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Packaging 0.99% 1.94% 21.54% 20.59% 0.00% 0.00%
Control 0.21% 0.41% 22.25% 21.88% 0.12% 0.29%
Source5 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Warehouse 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Cutting seat 16.29% 22.70% 0.00% 0.00% 6.40% 0.00%
Buffer2 0.00% 0.00% 20.69% 24.06% 79.31% 75.94%
Worker Pool 0.00% 0.00% 16.96% 23.97% 8.19% 1.19%
Buffer3 0.00% 0.00% 56.47% 100.00% 43.53% 0.00%
Buffer4 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Buffer6 0.00% 0.00% 27.28% 100.00% 72.72% 0.00%
Pressing seat 24.99% 25.12% 0.16% 0.03% 0.00% 0.00%

From the comparison, it can be seen that the percentage of operation of the stations has increased
significantly, and that the percentage of blocking in the stations has dropped significantly.
We can also notice that the output of the improved simulation model 3 grew by almost 50% as a
result of the elimination of the last bottleneck that was detected in the second phase.
After eliminating the bottlenecks that were identified at the beginning, a schematic overview of
the improved simulation model 3 is again being made in order to obtain a picture of the final
result achieved with the improvements implemented (Figure 17).
Backrest
Seat
Cutting
backrest
Cutting
seat
Pressing
backrest
Pressing seat
Bars
Cutting
Grinding
Bending
Painting
Assembly
3
Hand painting
Buffer Assembly
1
Assembly
2
Control
Packaging
Warehouse
Work/blocked
Work/blocked
Work/blocked
Work/blocked
Work/blocked
Work/waiting
Work/waiting
Work/waiting waiting
waiting
work
work
work
work
!
!
Assembly1
_1
Work/waiting
Buffer
!
Work/blocked
Figure 17. Schematic view of the improved model 3
Although the bottlenecks that were identified at the beginning were eliminated from the new
analysis, it can be noticed that the assembling stations are waiting, i.e they do not receive the
material in time, and therefore there is a delay in the production and blocking of the stations that
precede them.
As the capacity of the stations for pressing the seat and backrest has already been increased, we
can conclude that the stations for cutting the seat and backrest do not meet their needs i.e they
represent the bottleneck.
Therefore, the next step is implementing a new improvement, that is, an increase in the number
of stations for cutting back and seat, which entails and again increases the number of pressing
stations.

 Improvement 4: Adding stations for cutting and pressing the seat and backrest
6 additional stations (2 for cutting and 4 for pressing) are added in the improved model 4 as shown
in Figure 18.
Figure 18. Improvement 4: Adding stations for cutting and pressing the seat and backrest
The steps of analyzing the simulation model are repeated using Bottleneck Analyzer and Statistic
Report, which generates a data report (Figure 19) in order to compare the data from the improved
model 3 and the newly created report.
.

Figure 19. Statistic report for the improved model 4

Table 5. Comparison of statistics reports between the improved model 3 and the improved
model 4
Bending 15.59% 21.91% 2.00% 73.78% 5.09% 4.32%
Cutting 9.76% 13.70% 0.91% 1.22% 11.87% 7.61%
Grinding 11.70% 16.44% 1.65% 2.26% 9.31% 3.97%
Bars 0.00% 0.00% 1.36% 1.75% 98.64% 98.25%
Painting 3.88% 5.45% 22.67% 17.21% 63.59% 0.00%
Hand painting 1.32% 0.47% 6.02% 22.11% 15.24% 0.00%
Source1 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Buffer 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Backrest 0.00% 0.00% 0.00% 0.01% 100.00% 99.99%
Seat 0.00% 0.00% 0.00% 0.01% 100.00% 99.99%
Bolts 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Buffer1 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Source41 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Packaging 1.94% 3.26% 20.59% 19.27% 0.00% 0.00%
Control 0.41% 0.68% 21.88% 21.48% 0.29% 0.42%
Source5 0.00% 0.00% 0.00% 0.00% 100.00% 100.00%
Warehouse 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Cutting seat 22.70% 22.19% 0.00% 0.00% 0.00% 2.96%
Buffer2 0.00% 0.00% 24.06% 100.00% 75.94% 0.00%
Worker Pool 0.00% 0.00% 23.97% 22.69% 1.19% 2.46%
Buffer3 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Buffer4 0.00% 0.00% 100.00% 2.02% 0.00% 97.98%
Buffer6 0.00% 0.00% 100.00% 100.00% 0.00% 0.00%
Pressing seat 25.12% 24.24% 0.03% 0.03% 0.00% 0.89%

From the comparison, it can be noted that the number of outputs on the final boxes has
increased, the blocking of the stations has been drastically reduced, and as a result, the
percentage of work at the stations has increased.
This improvement eliminated the bottlenecks that were detected. The results of the improved
model 4 are satisfactory, which means that it completes the analysis and approaches the next
step, implementing it.
It is important to note that when analyzing the bottlenecks we always start
from the end to the beginning of the process !!! (Figure 20).
Figure 20. Bottleneck analyze from end to the beginning of the process
Bottlenck
Flow of material
Bottleneck analyze
1
2
3
4
5

4. Conclusion
The problem of bottlenecks is a key issue in optimizing and increasing the efficiency of
production processes. Discovery and analysis of bottlenecks is one of the fundamental constraints
of modern manufacturing companies. That is why companies should not ignore this problem that
significantly impacts the efficiency of the processes. One of the ways to solve the "bottleneck"
problem is using the simulation method that was presented in detail through this paper.
Analysis of bottlenecks is a detailed process in which a company collects information about
the production flow of a particular product or process. In particular, data are collected on the step
or steps in the process where work is closely related. This type of analysis can be done specifically
to identify the cause of the bottleneck causing problems or to anticipate processes where a
bottleneck may occur in the future. Regardless of the reason for conducting this type of analysis,
important information is provided on how things are done and how they can be improved.
When performing analysis of bottlenecks, it is important not only to look at the specific
step in which a bottleneck occurs, but rather the entire production process. This will provide
essential information about processes leading to a bottleneck, the very bottleneck itself, and what
happens right after the bottleneck. This is important for various reasons, including the fact that if
the bottleneck in the production process is eliminated, it may result in the formation of a new
bottleneck in the future. Properly analyzed will not only help to find solutions to the existing
bottleneck but also help prevent the formation of new ones.
Companies should find ways to improve and improve their operations. The use of the
simulation method is proving to be an effective tool for finding ways to improve productivity of
the processes. The possibility of presenting various scenarios and their analysis, without the need
for them to be tested in reality, leads to a reduction in time and costs for finding optimal solutions
to the problems. The purpose of this graduation thesis is to develop a simulation model of the
production process and with the help of the analysis method to analyze the model and to find and
eliminate the bottleneck in the production process. The study confirms the possibility of using the
simulation software Plant Simulation in the analysis of both simpler and more complex
production processes

5. References
. Јовановски, Бојан. Интерни скрипта - Моделирање на деловни системи
2. Mateusz Kikolski. Identification of production bottlenecks with the use of Plant
Simulation software
3.Binod Timilsina. REMOVING BOTTLENECK FROM A MANUFACTURING UNIT:
A case studies to BET-KER OY, Ylivieska-84100, Finland
4. Arul Pragash Karthikeyan. DETECTION OF BOTTLENECKS FOR MULTIPLE
PRODUCTS AND MITIGATION USING ALTERNATIVE PROCESS PLANS
5. Благој Делипетрев, Наташа Стојковиќ, Зоран Утковски. Моделирање и
симулации – скрипта, Штип, 2015
6. Plant Simulation. www.plm.automation.siemens.com
7. https://www.creativesafetysupply.com/articles/bottleneck-analysis/

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