Реферат по дисциплине «Иностранный язык» на тему «AUTOMATION OF DATA PROCESSING IN COMPUTER-CONTROLLED MACHINE TOOL PRODUCTION OF PRODUCTS »

Министерство образования Республики Беларусь
Учреждение образования
«Гродненский государственный университет
имени Янки Купалы»
РЕФЕРАТ
по дисциплине «Иностранный язык»
на тему
«AUTOMATION OF DATA PROCESSING IN COMPUTER-CONTROLLED
MACHINE TOOL PRODUCTION OF PRODUCTS »
ВЫПОЛНИЛ:
Магистрант
кафедры математического и
информационного обеспечения
экономических систем,
специальность «Прикладная
математика и информатика»
Гоманчук Владислав Олегович
Допущен к сдаче кандидатского
экзамена:____________________
(ФИО преподавателя, дата, подпись)
Гродно 2024
АННОТАЦИЯ
В современной промышленности автоматизация производства с помощью
станков с ЧПУ (числовым программным управлением) играет ключевую роль.
Это
позволяет
повысить
эффективность,
точность
и
безопасность
производственных процессов. Станки с ЧПУ управляются компьютерами, что
минимизирует человеческое вмешательство.
В эпоху данных автоматизированный сбор и анализ информации
становятся все более важными. Технологии датчиков, обеспечивающие прямое
измерение, являются одним из ведущих трендов. Одновременно анализ данных
на основе физических моделей имеет свои ограничения из-за сложности
описания производственных процессов.
Глубокое
обучение
имеет
большой
потенциал
для
принятия
автоматизированных решений на основе обширных данных. При этом подходы,
основанные на данных, позволяют достичь схожих или даже лучших
результатов, используя ограниченные объемы информации.
АНАТАЦЫЯ
У сучаснай прамысловасці аўтаматызацыя вытворчасці з дапамогай
станкоў з ЧПУ (лікавым праграмным кіраваннем) іграе ключавую ролю. Гэта
дае магчымасць павысіць эфектыўнасць, дакладнасць і бяспеку вытворчых
працэсаў. Станкі з ЧПУ кіруюцца камп’ютарамі, што мінімізуе чалавечае
ўмяшанне.
У эпоху дадзеных аўтаматызаваны збор і аналіз інфармацыі становяцца
ўсё важнейшымі. Тэхналогіі датчыкаў, якія забяспечваюць прамое вымярэнне,
з'яўляюцца адным з кіроўных трэндаў. Адначасова аналіз дадзеных на аснове
фізічных мадэляў мае свае абмежаванні з-за складанасці апісання вытворчых
працэсаў.
Глыбокае навучанне мае вялікі патэнцыял для прыняцця аўтаматызаваных
рашэнняў на аснове шырокіх даных. Пры гэтым падыходы, заснаваныя на
дадзеных, дазваляюць дасягнуць падобных ці нават лепшых вынікаў,
2
выкарыстоўваючы абмежаваныя аб'ёмы інфармацыі.У заключэнне варта
адзначыць, што дадзеная праца прапануе каштоўныя звесткі аб бягучым стане
прагназавання спажывання газу і вызначае курс на будучыню развіццё гэтай
галіне.
ABSTRACT
In modern industry, the automation of production with CNC (numerical
control) machines plays a key role. It makes it possible to increase the efficiency,
accuracy and safety of production processes. CNC machines are controlled by
computers, which minimises human intervention.
In the data age, automated collection and analysis of information is becoming
increasingly important. Sensor technologies that provide direct measurement are one
of the leading trends. At the same time, analysing data based on physical models has
its limitations due to the complexity of describing production processes.
Deep learning has great potential for automated decision making based on
extensive data. At the same time, data-driven approaches can achieve similar or even
better results using limited amounts of information.
3
CONTENTS
GLOSSARY .................................................................................................................. 5
INTRODUCTION ......................................................................................................... 7
CHAPTER 1 ADVANTAGES OF USING CNC MACHINES FOR PRODUCTION
AUTOMATION ............................................................................................................ 8
CHAPTER 2 PREPARING VECTOR FORMATS WITH CORELDRAW IMAGE
TRACING TOOLS .................................................................................................... 18
CHAPTER 3 CONVERSION OF VECTOR GRAPHICS INTO A MACHINE
CONTROL PROGRAMME ....................................................................................... 23
CONCLUSION ........................................................................................................... 25
REFERENCES ............................................................................................................ 26
4
GLOSSARY
1.
Smart Manufacturing: The integration of intelligent technologies and
manufacturing processes to automate production using advanced information
technologies, including IoT, cyber-physical systems, cloud computing, and big data
analytics.
2.
Automated Production System: A system that involves automatic
machine tools, industrial robots, material handling systems, assembly lines,
inspection systems, and computer-based planning and control for efficient and errorfree production.
3.
Data-Driven Manufacturing: A paradigm where manufacturing
decisions are based on data analysis rather than simplified physical models or human
expertise. It leverages abundant data for better automation.
4.
Machine Learning: An approach that enables computers to learn from
data and improve decision-making without being explicitly programmed. Deep
learning, a subset of machine learning, is particularly powerful for automation.
5.
Data Collection: The process of gathering manufacturing-related
information at various stages, including explicit values (e.g., material properties,
temperature) and implicit data (e.g., supply chain resources, customer preferences).
6.
Data Analysis: The examination of collected data to extract meaningful
insights. Physical model-based analysis may have limitations due to the complexity
of manufacturing processes.
7.
Sensor Technology: Groundbreaking technology that facilitates direct
measurement, especially important for complex and uncertain manufacturing
processes.
8.
Indirect Measurement: Measurement methods that do not directly
observe the desired parameter but infer it from related measurements or models.
9.
Physical Model-Based Analysis: Analyzing data using simplified
physical models, which may lead to ill-posed solutions due to the complexity of
manufacturing processes.
5
10.
Computer Numerical Control (CNC): A technology that automates
machine tools using pre-programmed sequences of commands. CNC machines follow
precise instructions for manufacturing tasks.
11.
Automation: Using technology and machines to perform specific tasks
without human intervention, aiming to increase efficiency, productivity, and accuracy
in production.
12.
Digital Twin: A virtual representation of a physical product or process,
allowing real-time monitoring, simulation, and optimization.
13.
Cloud Manufacturing: A model where manufacturing resources and
services are provided via cloud computing, enabling flexibility, scalability, and
collaboration.
14.
IoT-Enabled Manufacturing: Integrating Internet of Things devices
into manufacturing processes for real-time data exchange, monitoring, and control.
15.
Computer-Aided Design and Computer-Aided Manufacturing
(CAD/CAM): Software tools that assist in designing products and generating
machine instructions for manufacturing.
6
INTRODUCTION
The advent of automation in various industrial sectors has marked a significant
revolution in the way productions and operations are conducted. In the realm of
manufacturing, particularly within the sphere of computer-controlled machine tool
production, automation has introduced unparalleled efficiency, precision, and
productivity.
The incorporation of data processing automation in this area not only
streamlines the fabrication process but also enhances the quality and consistency of
the products manufactured. This paper aims to explore the multifaceted role of
automation in data processing, specifically focusing on its implementation in the
production of products through computer-controlled machine tools. By delving into
the technological advancements that have made this automation possible, examining
the implications for productivity and quality, and assessing the future directions of
this trend, this study endeavors to highlight the transformative impact of automation
on the manufacturing industry.
Through a comprehensive analysis, we will uncover the benefits and
challenges of automating data processing in the realm of computer-controlled
machine tool production, thereby offering insights into the optimization of
manufacturing processes in the contemporary industrial landscape.
7
CHAPTER 1
ADVANTAGES OF USING CNC MACHINES FOR PRODUCTION
AUTOMATION
Modern machine tools vary in size and design, depending on their purpose:
from a compact benchtop unit to a heavy gantry construction. However, there are
some common functional components.
The basing mechanism is used for positioning the workpiece relative to the
machine coordinate system and for clamping. It consists of one or more tables and
must be rigid and vibration-resistant to absorb vibrations arising during operation.
Positioning mechanism – rail guides and travelling screws, which ensure the
movement of the workpiece and/or the slide with the tool along the coordinate axes.
They must have high rigidity as well as precise and smooth running. These properties
are ensured by the design of the guideways themselves, as well as by the bearings and
stepper or servo motors used.
Spindle – a shaft with integrated devices for automatic tool setting and
clamping. It must be rigid, precise, backlash-free, with wear-resistant seating
surfaces. The accuracy of tool rotation and spindle housing rotation is determined by
the accuracy of the corresponding drive.
The tool magazine for storing replacement cutting tools and machine heads is
usually moved together with the slide. At the command of the CNC control
programme, the tool is changed.
A feedback system is required for monitoring and correcting workpiece
parameters and drive speeds. It constantly compares the readings of the feedback
sensors with the programme values and outputs voltages to the drives until deviations
reach the target values.
The control system consists of a controller, memory, display, keyboard and data
input device. It is used for program input from the media, keyboard or computer with
CAD/CAM system; formation of control actions on the drives and implementation of
8
auxiliary technological operations (supply of cooling lubricant); reading and
interpretation of feedback signals; formation of messages for the operator.
The CNC equipment operation is defined by a programme of G- and M-codes sequential commands for tool drives and moving parts of the machine holding the
workpiece – platform, spindle.
When the programme is executed, the processor issues the corresponding
control actions to the machine's actuators. Depending on the command, the machine
moves the workpiece or tool, starts the main technological operation, supplies
coolant, turns the tool magazine to the required position, changes the tool.
When the programme is completed, the resulting workpiece is moved to the
next machining step and the machine moves on to machining a new workpiece.
NC programmes can be:
•
write them manually in the form of G- and M-codes;
•
can be entered using the touch screen, keyboard and joystick on the
control stand;
•
automatically generated by a postprocessor on the basis of a 3D model
of the workpiece. The 3D model is first created in a CAD system, and the CAM
system converts the 3D model into toolpaths [5].
The CNC programme is stored in the machine's memory and can be accessed
when needed to start production of the product or to make changes to the code.
CNC machines are more expensive than manual machines. However, they
quickly pay for themselves by reducing the number of manual operations, eliminating
human error, lowering operating costs and saving time on changeovers. The use of
CNC equipment is justified in the following cases.
The machine automatically processes surfaces, including complex ones,
according to a predetermined programme, without the operator's participation. Due to
relatively low production costs, the machine pays off quickly.
CNC machines provide higher machining accuracy. And the possibility to
create a 3D model in advance and "rehearse" on inexpensive materials excludes the
spoilage of valuable raw materials.
9
CNC equipment provides precise machining with a tolerance within the first
six qualifications. The amount of deviation is determined by the drive pitch (up to 3
µm).
CNC machines quickly process parts with complex surfaces, including those
imitating artistic elements: wood or stone carvings, bas-reliefs. Modern multi-axis
machines with automatic tool change can process three-dimensional shapes of any
complexity.
Necessity of product customisation. In order to modify the product according
to the customer's wishes, it is necessary to make changes in the CAD-model of the
object or directly in the CNC programme. This is easier and faster than reconfiguring
a manually operated machine.
CNC machines are used in mechanical engineering, instrument making,
furniture, jewellery and souvenir production, stone grinding and engraving. Such
machines are used to produce decorative elements and finishing materials,
components of telecommunications equipment, critical parts of high-tech equipment
for the energy, pharmaceutical and aerospace industries.
Classification of CNC machines
CNC machines are divided into groups according to various characteristics.
This classification is reflected in the standard labelling of domestic machine tools.
•
By technological operations:
Turning, milling, drilling, cutting, tapping, thread-cutting, multifunctional.
There are also machines for laser, plasma, oxygen, water jet cutting, for electronbeam, photochemical, ultrasonic processing.
•
According to the location of the spindle axis:
Horizontal, vertical.
•
By number of controlled coordinates:
2-, 3-axis machines move the tool and workpiece along 2 or 3 mutually
perpendicular axes. 3-axis machines can machine relatively complex surfaces.
4-, 5-axis machines have 1 or 2 additional controlled coordinates and can
machine complex surfaces in a single workpiece setup, thus reducing machining time.
10
•
In terms of machining accuracy:
Normal, increased, high, extra high precision, extra high precision master
machines.
•
By type of control system:
In the CNC machine marking there is a letter F with a numerical index, which
denotes the type of control system (Table 1).
•
By type of control system:
The marking of the CNC machine includes the letter F with a numerical index
that
indicates
Index
the
type
of
Control system
control
system
(Table
1).
Deciphering
Coordinates are set using the keypad;
F1
Digital display and the current position of the machine drive is
coordinate preselection. indicated by luminous digits on the light
display.
F2
The implement is moved to the set
Positional
point and then the machining starts.
The
F3
Contouring
implement
moves
along
a
predetermined trajectory, while carrying out
processing.
F4
Combined
Position and contour control, including
4-5 coordinates, with automatic tool change.
Table 1 - Types of NC control system
•
Feedback:
Machines with open loop control system execute the program without checking
the current parameters of the process operation. This type of control is usually used in
positioning machines where there are no high requirements for positioning accuracy
and tool speed.
11
Machines with closed-loop control are equipped with feedback sensors that
monitor the position of the workpiece and the working tool, spindle angular speed,
ambient temperature and other important parameters. Such machines adjust the
parameters of technological operations in real time depending on the sensor readings.
Production automation
Modern lines integrated into the automatic production control loop based on
MES/MOM and ERP systems are equipped with closed-loop machines. The first step
towards flexible automated production can be the integration of one or more closedloop CNC machines and a production monitoring and control system such as DPA.
This will allow:
•
control the parameters and duration of operations,
•
comply with machining technologies
•
plan production and meet deadlines for order fulfilment,
•
control product quality.
As production scales, you can grow your machine fleet and implement a
MES/MOM system that will take over resource accounting and real-time scheduling
of equipment.
One of the major challenges that manufacturing faces is the task of ensuring
the required dimensional and shape accuracy parameters of machined surfaces. In the
process of machining there are quite a large number of factors, both deterministic and
stochastic in nature, which lead to the fact that the actual values of dimensions differ
from the nominal ones. In industrial practice, a number of methods are used to
improve the accuracy of machining parts on CNC machines. Among such methods of
ensuring accuracy are the reduction of machining parameters [1], such as feed,
cutting speed. In addition, active control and accounting of the relationship between
cutting modes [3] and output process parameters [5] are used. Each of these methods
has both advantages and disadvantages. The main disadvantages include a decrease in
machining productivity, changes in machine design and increased costs, as well as
violation of modern principles of automation of production processes. The way out of
this situation can be the use of modelling apparatus, which allows to take into account
12
the deformations from cutting forces in the preparation of control programs, making
appropriate corrections to the tool trajectory to compensate for emerging errors. Since
the process of part surface formation is a complex process and it is practically
impossible to describe it completely, the solution of the problem was aimed at the
study of elastic force deformations, their influence on the quality of metalworking
and the possibility of compensation.
Investigation of possibilities of application of the approach of preparation
of control program by transformed CAD-model of the part
It is reasonable to evaluate the capabilities of each of the above methods of
accuracy improvement on the basis of the method of hierarchy analysis [7].
The calculation was performed in the SPPR software environment Choice (free
version). The hierarchy has three levels, the comparison was carried out for four
alternatives.
The level of criteria included such production indicators as productivity, the
need to change or modernize the machine or equip it with additional means of
automation, as well as the cost of implementing the existing technology or accepting
the implementation of improving the accuracy of machining on numerically
controlled machines.
The assessment was made in points from 1 (the same value) to 9 (significantly
superior). This approach makes it possible to introduce gradation of importance of
comparison criteria.
The set of methods and progressive technology of application of the approach
of preparation of control programs on the transformed CAD-model of a part are
intended for improvement of operability and simulation of functioning of production
objects or models of behavior of processes. These models (digital twins) realise such
a goal as to anticipate the behavior of the object under consideration for making a
rational management decision, in this case in the field of precision control of
workpiece machining on CNC machines. The application of the proposed approach
allows to reduce non-compliance with the established requirements, to reduce
material and other resources for possible defects [9].
13
Terminology in the field of digital twins and their application is currently one
of the possible directions of progressive technologies of industrial production [10].
Digital twins are a complex software product representing a virtual model, which is
described by mathematical apparatus and dependencies and linked to a database of
parametric characteristics of the virtual object under consideration [11].
In accordance with the scheme of control program preparation based on the
proposed approach, the first stage consists in obtaining a CAD model of the part
specified by the requirements of the design documentation at the stage of design
preparation of production. CAD-model of the part can be obtained using various
means of computer-aided design systems (CAD) at the enterprise, such software
products as SolidWorks Simulation and Autodesk Inventor are widely used, which
were applied in the implementation of the study.
Next, the determination of loads that act on the workpiece when cutting metal
is made. Calculation of the components of cutting forces can also be made using
modern CAD of technological processes, which have databases depending on the
selected cutting modes, or the calculation is made using the reference books of a
machine-building technologist.
The third stage is the determination of specific values of deformation
deviations under the influence of factors that were considered in the study, namely
elastic force deformations. The above stage was implemented using finite element
modelling in SolidWorks Simulation and Autodesk Inventor environments. The
calculation model with the specified load was built and the values of deviations were
identified.
Based on the results of finite element modelling, the trajectory of the cutting
tool relative to the workpiece, in this case a transformed CAD model of the
workpiece, is determined. Trajectory modelling is implemented as follows.
In the CAD model Siemens NX, a parametric model of the workpiece is
developed, which contains a certain number of sections with different parameters
equal to the radius of the ideal model.
14
Then in the subsystem "Modelling" the input data for the development of the
control program for the ideal model of the part is formed (definition of the geometry
of the part and workpiece, its material, machining areas, basing, cutting tool
parameters, machining strategy and input of data on cutting modes).
Based on the adopted machining strategy, automatic calculation of tool
trajectories relative to the ideal part model and their verification is performed.
Then postprocessing is performed. The standard code of the ISO 7bit
programming language for CNC lathes with turret tool changer is used as a
postprocessor. The result is a control program for the machining process of an ideal
part model.
Siemens NX CAD uses the "expressions" tool built into the Siemens NX CAD
system to import data from the finite element engineering analysis. The data are
imported into the CAD model from *.xlsx (Excel) and *.exp (export files) files,
according to the cross sections.
Since the data changes only the values of the specified parameters, the
Simulation subsystem does not need to redefine the input data to develop a control
program for the transformed part model. To obtain the control program, the only
thing left to do is to regenerate the cutting tool trajectories and perform the
verification and postprocessing process. The result is a control program generated
during postprocessing for machining the transformed part model on a CNC lathe.
The experiment was carried out. Two batches of workpieces were processed on
a CNC lathe: the first batch - by the proposed method, the second - by the traditional
method. The results of experimental data processing are presented in the table 2.
In the course of experimental verification it was found that the proposed
method allows to achieve a reduction in the variation of the actual size by a factor of
2.38 and a reduction in the mean square deviation by a factor of 2.19.
One of the directions for further research is the development of a model that
takes into account the uncertainty of initial data (e.g. cutting forces, the influence of
tool wear, machine elements, etc.). This problem can be solved by using neuro-fuzzy
models.
15
Mean
Arithmetic mean
square
deviation
No. of experience
, mm
, mm
sd1,
mm
sd2,
mm
1
43,78
43,83
0,078
0,193
2
43,84
43,93
0,071
0,152
3
43,81
43,77
0,066
0,133
4
43,81
43,85
0,076
0,162
43,81
43,85
0,073
0,16
Average
value
from the experiment
Table 2 - Statistical characteristics of the estimated parameter
In the course of experimental verification it was found that the proposed
method allows to achieve a reduction in the variation of the actual size by a factor of
2.38 and a reduction in the mean square deviation by a factor of 2.19.
One of the directions for further research is the development of a model that
takes into account the uncertainty of initial data (e.g. cutting forces, the influence of
tool wear, machine elements, etc.). This problem can be solved by using neuro-fuzzy
models.
The presence of a knowledge base with the ability to self-learning and flexible
logic blocks will allow to take into account the uncertainties of the initial data more
correctly.
Conclusions:
•
The results of the complex analysis of methods of accuracy
improvement have shown that the best combination of criteria possesses the method
based on the use of the proposed approach of preparation of control programmes for
CNC machines.
16
•
Application of the approach of preparation of control programmes for
CNC machine tools by the transformed CAD-model of the part, taking into account
the revealed errors, allows to increase significantly the accuracy of machining:
reduction of the actual size variation by 2.38 times and reduction of the mean square
deviation by 2.19 times.
•
One of the directions for further research is the development of a model
that takes into account the uncertainty of the initial data (e.g., cutting forces, the
influence of tool wear, machine elements, etc.).
•
This problem can be solved by using neuro-fuzzy models [6].
17
CHAPTER 2
PREPARING VECTOR FORMATS WITH CORELDRAW IMAGE
TRACING TOOLS
To automate manufacturing processes using CNC machines, you can resort to
converting raster drawing formats to vector format to create a control programme.
We use a conversion method such as image tracing.
Quick Trace
The Quick Trace tool allows you to create vector images based on raster
images literally with a single click. Vector images offer two advantages: they can be
scaled loss, and they usually require much less storage space.
The Quick Trace tool becomes available the moment you import and select a
bitmap image (photo or digital image). To do this in CorelDRAW, choose File >
Import. To access the Quick Trace tool, choose Bitmaps > Quick Trace. Quick Trace
allows you to convert a photo into a drawing without any additional steps. Typically,
this tool allows you to create drawings using just a few colours and elements. Using
the default settings for simple bitmap images gives very impressive results. However,
for complex bitmaps with many individual elements for which a significant reduction
in the level of detail is unacceptable, the settings need to be changed.
To trace this firefly, the Quick Trace tool was used with default settings.
To change the settings, choose Tools > Options > Workspace > PowerTRACE.
You can use the slider bar to adjust the accuracy. Drag it to the right to improve the
quality of the trace results. The list also contains ten preset styles.
In the Workspace category list, you can select a preset quick trace style.
The higher the quality of the original raster image, the better the result will be
after tracing is applied. When using some tools such as Dithering, Anti-Aliasing,
Resharpening with an Unsharp mask and Lossy Compression with compression
defects (e.g. JPEG method), the quality of the tracing results decreases: all these
functions create noise and interference in the image.
18
Line art
The outline tracing method offers a preset Line Art style that is particularly
useful for processing scanned sketches and tracing black-and-white sketches and
images. Strokes made with a biro or pencil are relatively uneven. Using ink or felt-tip
pen will usually give much better results than any attempt to trace drawings created
with biros or pencil.
Instead of processing scanned sketches, you can use the LiveSketch tool, which
allows you to draw and colour drawings on a tablet to get more a natural-looking
image.
Use the following tips and guidelines and you will get the best possible images
when processing stroke graphics. These recommendations also apply to the contour
tracing methods described below:
•
It is recommended that you keep the original size of the images as small
as possible to preserve detail.
•
The background colour for the entire image should be removed.
•
When preparing the image, it is necessary to zoom in and check
individual details to ensure that sufficiently accurate settings are selected.
•
It is recommended to reduce the number of colours used (however, at
least two colours should be retained).
•
It is recommended to use a thin felt-tip pen to create drawings that need
to be traced. - For drawings that require particularly careful processing, such as pencil
drawings with low contrast, it is necessary to increase contrast using Image
Adjustment Lab in Corel PHOTO-PAINT. To access the Image Adjustment Lab,
choose Adjust > Image Adjustment Lab.
Thin strokes:
•
drawings created with fine-tip capillary pens produce much better results
than pencil sketches.
•
In the Image Adjustment Lab section, select Create Snapshot to create a
snapshot that you can return to later if necessary.
19
•
You can also use Bitmaps > Contour > Edge Detect.... or Bitmaps >
Contour > Trace Contour... or Bitmaps > Contour > Trace Contour.
•
If the image has too low a resolution, you can increase the resolution
with a special tool. To export the image to Corel PHOTO-PAINT, choose File >
Export for.... > PhotoZoom Pro 4 and zoom in on the image. In most cases, the image
quality will be quite high. (See Section 6 for more tips and tricks. Low Quality
Image.)
The Logo outline trace style is ideal for tracing simple logos with little detail
and colour. Select Bitmaps > Outline Trace > Logo to open the dialogue box.
PowerTRACE does not support tracing large or highly detailed graphics.
Instead, the software prompts users to select Reduce bitmap to automatically reduce
the image size. PowerTRACE displays a Before/After preview window.
Before performing tracing, you must remove unnecessary areas by cropping
the image. This will leave only the most necessary areas, saving time.
Trimmed: by reducing the number of colours, you can simplify vector graphics.
In this window, select Remove Background and Specify Color. Hold down the
Shift key and click on the areas you want to remove [7].
Alternatively, to reduce the number of nodes, you can reduce the number of
colours. You can do this on the Colours tab. You can use the Smooth tool to smooth
the outlines and reduce the number of nodes.
Detailed Logo tool
The Detailed Logo tool is ideal for tracing logos with a lot of detail and colour.
To use this tool, choose Bitmaps > Outline Trace > Detailed Logo.
On the Colours tab, you can reduce the number of colours if necessary. To do
this, select Merge and then Sort colours by: Similarity. It is recommended that you
create outlines and colour styles. It is also important to choose a suitable colour
palette at this stage.
When using the Detailed Logo tool, you will have to experiment to find the
ideal values for the Detail, Smoothing and Corner Smoothness settings. In the
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Colours tab, you should limit the number of colours you use, leaving only the most
essential ones.
You can reduce the number of colours and nodes by converting to a grayscale
image
By converting a colour photo to a grayscale image, you can significantly
reduce the number of nodes. You can also reduce the number of colours used.
This allows you to quickly change the colour model - for example, using the
CMYK colour scheme instead of RGB.
Clipart
Select Bitmaps > Outline Trace > Clipart to run the Outline Trace feature for a
final graphic image with different colours. As with the Detailed Logo feature, you'll
have to experiment a bit to get the values perfectly accurate.
Use the following tips and tricks:
•
Zoom in to check the detail of the image.
•
Use the Smart Fill tool to create objects between the strokes.
Low Quality Image
If the image is of low quality due to insufficient pixels, you can start by trying
to zoom in on the image using the PhotoZoom Pro tool. Right-click the image and
select Edit Bitmap. The image opens in Corel PHOTO-PAINT. Select File > Export
for > BenVista PhotoZoom Pro 4. (If this plug-in is not installed, the utility assistant
will display step-by-step instructions for this procedure. You will need to restart
PHOTO-PAINT, as the plug-in is loaded during PHOTO-PAINT). PhotoZoom offers
other ways to zoom in photos, including the pre-installed Spline XL and Lanczos
tools. It is recommended to experiment with different options. Click the drop-down
menu to the right of the Presets section to open the Fine-tuning section. In the Finetuning section, increase the Edge Boost and Detail Boost values.
Final detail correction: in PhotoZoom Pro 4, you can maximise the fine-tuning
of the magnification of your photos.
Open the PowerTRACE dialogue box by selecting Bitmaps > Outline Trace >
Low Quality Image.
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High Quality Image
Select Bitmaps > Outline Trace > High Quality Image to open the
PowerTRACE dialogue box for tracing high quality images. The same procedure is
then used as for low quality images, but without zooming in PhotoZoom.
If the source image is high resolution, this does not guarantee the best result.
If you compare source images with two clearly different resolutions, it
becomes obvious that it is possible to get high quality drawings even with lower
resolution photos [8].
Tracing manually
You can quickly create vector graphics manually based on photos. Create a
copy of the photo and lock the bottom image. Trace the copy and create a border.
Create a bounding box using the drawing tool. Use the Smart Fill tool to fill the areas.
A combination of the drawing tools and the Smart Fill tool was used to create
these drawings.
After tracing, the original image is edited with the Boundary and Smooth tool
and converted to a new vector object [9].
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CHAPTER 3
CONVERSION OF VECTOR GRAPHICS INTO A MACHINE
CONTROL PROGRAMME
The transformation of vector graphics is closely related to the development of
control programmes for modern industrial CNC machines. Numerical Computer
Control (or NC) is a field of technology that involves the use of digital computing
devices to control manufacturing processes.
The control system processes instructions in a specialised programming
language (e.g. G-code) of programs, after which they are converted by the CNC
interpreter from the input language into commands for regulating the drive heads,
feed drives and controllers of machine components (e.g. switching on/off the supply
of cooling emulsion).
Nowadays, CNC programmes are developed using special computer-aided
design (CAD) modules or separate computer-aided programming (CAM) systems
that create a machining programme based on an electronic model.
An interpolator is used to determine the preferred tool/workpiece path
according to the control programme, which calculates the positions of intermediate
points in the tool/workpiece path according to the programme.
In addition to the programme itself, the control system includes data in other
formats and for various purposes. At a minimum, this includes machine data and user
data specific to a certain control device or a certain series (series) of control device
models of the same type.
The program for a CNC machine (or machines) can be loaded from external
storage media such as magnetic tape, perforated paper tape (punch tape), floppy disk
or flash memory, either temporarily in RAM until power is turned off or permanently
in ROM, to a memory card or other storage medium: hard disk or solid state drive. In
addition, modern machine tools are connected to centralised control systems via
factory (shop floor) communication networks [12].
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G-code programming language
The most common programming language for CNC machines is described in
ISO 6983 of the International Standards Committee and is called "G-code". In some
cases - for example in control systems for engraving machines - the control language
is fundamentally different from the standard language. For simple tasks, such as
cutting metal plates, the TNC can use a text file in a data exchange format such as
DXF or HPGL as input data.
G-code is a coding language for numerically controlled machine tools (NC).
The term "G-code" is derived from "geometric code." G-code instructions define the
machine tool's direction of travel, speed, and trajectory.
When machine tools such as lathes or milling machines are used, the cutting
tool is placed in motion using G commands to follow a specific tool path, machining
the material to the desired shape.
Similar to additive manufacturing or 3D printing, G code directs the machine
to apply material layer by layer, creating a precise geometric image (Figure 1).
Figure 1 - Example of program operation on G-code
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CONCLUSION
Automation of production with CNC machines is an important step in modern
industry. It makes it possible to increase the efficiency, accuracy and safety of
production processes. CNC (Computer Numerical Control) machines are controlled
by computers, which provides a high degree of automation and minimises human
intervention.
The benefits of automation with CNC machines include:
Precision: CNC machines are capable of performing complex operations with
high precision. This is especially important for manufacturing parts that require
micrometre dimensions.
Efficiency: Automated processes run much faster than manual processes. This
reduces production time and increases output.
Safety: Human error can be a source of errors and accidents. Automation
reduces the risk of injury and increases the safety of the working environment.
Flexibility: CNC machines can quickly switch between different jobs. This
allows companies to respond quickly to changes in demand and produce new
products.
The research conducted in this area provides valuable guidance to companies
looking to optimise their production processes and increase their competitiveness in
the market.
25
REFERENCES
1. IEA [Electronic resource]: International Energy Agency. – Mode of access:
https://www.iea.org/. – Date of access: 01.03.2024.
2. Kovács, G., Xirouchakis, P. CNC machine tools automation based on
advanced computing techniques / G. Kovács, P. Xirouchakis // International Journal
of Advanced Manufacturing Technology. – 2003. – Vol. 22. – P. 840–850.
3. Altintas, Y., Verl, A. Machine tool feed drives / Y. Altintas, A. Verl // CIRP
Annals - Manufacturing Technology. – 2011. – Vol. 60. – № 2. – P. 779–796.
4. Brown, R.G. Smoothing forecasting and prediction of discrete time series /
R. G. Brown. – N.Y. : Prentice–Hall, 1963. – P. 174–199.
5. Brown, R. G., Meyer, R. F. The fundamental theorem of exponential
smoothing / R. G. Brown, R. F. Meyer. – N.Y. : Prentice–Hall, 1961. – Vol. 9. –№ 5.
– P. 52–79.
6. Koren, Y. The Global Manufacturing Revolution: Product-Process-Business
Integration and Reconfigurable Systems / Y. Koren. – Wiley, 2010.
7. Li, X., Gao, L., Li, W. Development of a hybrid manufacturing process for
sculptured surface machining / X. Li, L. Gao, W. Li // Journal of Manufacturing
Systems. – 2017. – Vol. 44. – P. 216–227.
8. Monostori, L. AI and machine learning techniques for managing complexity,
changes, and uncertainties in manufacturing / L. Monostori // Engineering
Applications of Artificial Intelligence. – 2003. – Vol. 16. – P. 277–291.
9. Teti, R., Jemielniak, K., O’Donnell, G., Dornfeld, D. Advanced monitoring
of machining operations / R. Teti, K. Jemielniak, G. O’Donnell, D. Dornfeld // CIRP
Annals - Manufacturing Technology. – 2010. – Vol. 59. – № 2. – P. 717–739.
10. Zhang, G. Forecasting with artificial neural networks: The state of the art /
G. Zhang // International Journal of Forecasting. – 1998. – Vol. 14. – P. 35–62.
11. Bohez, E. L. J. Five-axis milling machine tool kinematic chain design and
analysis / E. L. J. Bohez // International Journal of Machine Tools and Manufacture. –
2002. – Vol. 42. – P. 505–520.
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12. Susto, G. A. Machine learning for predictive maintenance: A multiple
classifier approach / G. A. Susto, A. Schirru, S. Pampuri, S. McLoone, A. Beghi //
IEEE Transactions on Industrial Informatics. – 2014. – Vol. 11(3). – P. 812–820.
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