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DEVELOPMENT OF SMART PAINTING MACHINE USING IMAGE
PROCESSING
Atif Saeed
Faculty, Department of Mechatronics Engineering, SZABIST, (Pakistan).
E-mail: m.atif@szabist.edu.pk ORCID: https://orcid.org/0000-0003-4369-2388
Hussain Muslim Mithaiwala
Student, Department of Mechatronics Engineering, SZABIST, (Pakistan).
E-mail: hussain.muslim53@gmail.com ORCID: https://orcid.org/0000-0001-6284-6237
Ammar Iqbal Hussain
Student, Department of Mechatronics Engineering, SZABIST, (Pakistan).
E-mail: ammararsi48@gmail.com ORCID: https://orcid.org/0000-0003-2031-8393
Tulsi Kumar
Student, Department of Mechatronics Engineering, SZABIST, (Pakistan).
E-mail: tulsikumar199600@gmail.com ORCID: https://orcid.org/0000-0002-8848-0533
Recepción:
04/09/2020
Aceptación:
02/10/2020
Publicación:
14/12/2020
Citación sugerida:
Saeed, A., Mithaiwala, H.M., Hussain, A.I., y Kumar, T. (2020). Development of smart painting machine using image
processing. 3C Tecnología. Glosas de innovación aplicadas a la pyme, 9(4), 95-119. https://doi.org/10.17993/3ctecno/2020.
v9n4e36.95-119
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ABSTRACT
Painting is a process in automotive industry that takes about 10% of the total time consumed per vehicle.
Currently, the painting lines in several automotive industries like Toyota motors or General motors
is largely being automated after implementation of robotic arms. However, according to the study
done, this automation is restricted to paint main body or chassis only, the coating and painting on small
vehicle parts is still done manually. This paper represents the study conducted on local Toyota motor
plant located in Karachi where the need of automating the small parts painting line evolved to increase
production. The designed system is based on 3axis gantry mechanism which locates the position of parts
to be painted on moving conveyor through computer vision, reach the coordinates, paints autonomously
and forwards it to buer station for drying. The computer vision is introduced to minimize the human
interference and make the line semi-autonomous. The system was tested for correct image processing
and at the end algorithms was correctly identifying and locating 90% of the parts. Moreover, the system
was tested for one week in a laboratory environment and it was observed that production rate was
increased to 2% as compare to their previously available data.
KEYWORDS
Computer Vision, Autonomous Painting, CNC, Automobile, Mechatronic System, Python.
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1. INTRODUCTION
Today, the modern industrial revolution is on its way towards advancements. The industrial revolution
is taking over the entire world briey. One of the major goals of today’s industrial revolution is to
adopt automation. Almost in every sector such as military, agriculture, automobile, manufacturing
and design and development etc. Presently, automation is widely being implemented and used in the
industrial sector all over the world, this is done in order to increase the eciency and productivity of
the manufactured goods. The automobile sector is also using automation to perform various task in the
cars body manufacturing, assembly and paint shops in order to increase their per day productivity and
eciency of the cars. But however, the industrial automation is not implemented and used in Pakistan
at its maximum pace. Thus, a lot of task are done manually, this aects the eciency and productivity
of the produced parts. In Pakistan, especially in the automobile sector, painting procedures are not
fully carried out by robots, instead paid labors (humans) are also employed in painting small parts such
as mirror covers, mud aps, door handles, spoiler and fog lamps etc. And also, automatic painting is
adopted only by factories and industries which produce large lot sizes of same type/variant of parts
(Saeed et al., 2019).
Thus this paper discusses about the possible feasible solution which will help shift the small scale industries
and the automobile industries to implement modern industrial automation by placing robots in their
production line in order to increase their productivity and eciency of produced goods.
Currently, Pakistan is not able to completely not able to adopt the industrial revolution along with the
modern automation as because the initial capital cost is way too much for which small industries can’t
invest in it. The other major reason is that most of the robots can paint only one part variant at a time,
thus industries not producing large lot sizes of same part variant are unable to get automatic painting
being carried out in their industry. Another problem caused by this is the human health issues, as painting
process contains release of harmful chemical fumes which ultimately aects human health. Also human
painted parts are sometimes not up to the mark as the paint coating are uneven, thus the parts are not
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passed from quality check departments which results in reducing the productivity as well as eciency of
the parts produced by the industry. Thus, all these reasons aect the productivity and eciency of the
industrial produced goods (Amin & Saeed, 2018).
Our idea is to introduce a Smart Painting Machine which will be capable of painting various geometry
parts at a time. By this our aim is to introduce the concept of automatic painting in small scale industries
who cannot aord costly automatic painting machines within their vicinity. We basically derived the
idea of automatic painting from the automobile industries where still small parts such as mud aps, door
handles, spoilers, fog lamps etc. are painted by labors.
The key feature of this machine is basically its programming part which waves o the requirement to
burn/run dierent program for dierent geometrical part. The programming embedded with the smart
painting machine is basically based on image processing. A camera is mounted in the workspace of the
painting machine which takes the real-time image of the part and then the image is processed. After
processing the image, its geometry is detected by applying edge detection and contour detection. This
results in identifying the object geometry by which the object coordinated are detected. Thus the part is
painted as per its geometry. This features allows small lots of various geometrical parts to be painted with
a single machine and single program. Thus, it’s very benecial for industries as it saves a lot of capital
investment.
As far as human health is concerned, this machine follows all the safety protocols. The painting workspace
is enclosed by a glass/acrylic frame house to eliminate the chances of spilling out paint particles as well
as escape of any painting chemical fumes. Thus a lot health issues like coughing, sneezing, nausea and
breathing issues are eradicated.
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2. LITERATURE REVIEW
Authors, in this paper, plans to introduce a process for advance mechanize spray painting of unknown
parts. The machine made by this experiment will be very useful for painting of unknown shape. The time
consumed by this machine is very less as compared to manually, (hand) painting. It will, save expenditure
such as labor cost and the total cost of painting any jobs (Swarakar et al., 2018).
Thakar and Vora (2014) in his paper gives essential knowledge about mini and large scaled industries
manufacturing parts are painted for protecting from rust, so the spray method consumes large amount
of time and paint which required the workers which are skilled emerged with the application. Robotic
painting techniques is not applicable for large eciency so the rise in such method have to be made
which is aordable, have accuracy and precision, consumes minimum time for the coating of the part so
objective has to developed in such a manner that the mechanism which coat the part with the dipping
and baking process having semi-automated techniques which is up to the required mark and which can
be valuable for mini and large scale factories (Thakar & Vora, 2014).
Author in this research highlights some key features through the system test, it is fact that the design
of intelligent robot have many advantage not only has good painting eect but also has high eciency
which can only at least 2-6 minutes to draw the simple cartoon images and also take no more than 15
minutes to draw complex portrait images. We also provided an illustrative example to show our required
results (Feng et al., 2017).
Abdellatif (2012) in his research describes the design, construction and working of an Automatic wall
painting robotic machine. This visionary and remarkable design of a robot which is movable to be used
for painting interior walls of residential building or oces has been described. Robot has a roller that is
fed with liquid paint and keeps contact with the wall surfaces. The robot has advance option that helps
the roller to scan vertically as well as horizontally to the painted walls. The robot has advance technology
that can adjust itself in front of the wall (Abdellatif, 2012).
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Naticchia et al. (2007) in his research, shows that mechanical painting can be not only be done to upgrade
production and allows quality checking. The robotic arm application with high precision and accuracy is
required. An automatic system to convert to the normal coordinates of the liquid colors to be reproduce
the moveable speed of the robot’s end tool and valve opening and closing end of the mixing board. The
maximum work shall be probably required to get high resolution (Naticchia et al., 2007) hence also the
productivity of the construction industry must be improved, while preserving its labour from hazardous
job sites. Such requirements can be accomplished by the adoption of robotized products, which, however,
need to be quickly developed and marketed. In this paper, rst the issue of a new miniature laboratory
for developing lightweight and well-coordinated robotized systems is pursued, then a novel robot device
for high quality multi-colour interior wall painting carried by a robot arm is developed and successfully
tested. Thanks to the new 1:6 scaled down laboratory and its six degree of freedom robot arm on an
hexapod for horizontal moves, we tested the opportunity to introduce also in the building sector miniature
robots that can change the ergonomics standardly adopted by construction workers. It is analyzed how
and why switching from full size to miniature robots is convenient in construction. In addition, a new
system adding further features to robotized painting has been conceived. Our new multi-colour spraying
end-tool was developed and xed on the robot arm, in order to be able to reproduce coloured artworks.
Finally, a methodology to reproduce colours from digital format of artzoorks is presented, showing
how accurate and ecient is this new robotized spraying device. miniature painting robot, scaled down
laboratory, multi-colour spraying end tool. Ata and Eleyan (2017) in their research present his work on
articulated robots like these robots are widely re-known by basically automobile company commercials
and robot dance application. SCARA (Selective-Compliance-Articulated-Robot-Arm) robots are also
re-known for their usage and proliferate in industries from 1970’s. Two kind of robot articulated and
SCARA robot’s combination to gather linear and rotary motion accomplishing in formation for complex
tasks (Ata & Eleyan, 2017).
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In this research paper goal was to learn the system for coating and painting tasks carried out in automobile
repair and then change manual painting by robot painting. So the most important study, was for skilled
spray gun handling for automobile repair painting which were observed and compared with those with
little or no experience. The spray gun movements of the experts were characterized by longer length,
longer time, higher speed, and narrower swing range, compared with the non-experts. The results were
collected and accordingly the spray gun movement was set (Ikemoto et al., 2015).
Authors in this paper presents a research on Image Processing that can be directed to Machine Learning
and the process of computing can identify pattern of high diverse parts. Machine learning is very close
and like computing statistics that consist of spam lter optical character identication searching engines
and computer vision. Their extensive arrays of knowledge observed (algorithms) to reduce destruction
noise such linear lter of Gaussian-based algorithm. Algorithms can remove certain kind of grain noise
destruction from a picture. Because every pixel of picture in setting to mean values in its environment
the normal variations tested by the grain are reduced (Wiley & Lucas, 2018).
Authors in this project through his studies, successfully identied the part from the background picture
used for color process is required to remove the background by 1st ler grayscale ltering is the second
step and nally by Circular Hough Transform (CHT) and binary testing for part that is in circular object
detection. Using of color processing is used as it is powerful process to identify the part as it is in normal
color process it has a lot of information as human eyes can do. For the grayscale lter it lters the (pixel
and smoothness) the picture to the edge clear. In last CHT is required to detect the parts which are
circular and total number is displayed (Hussin et al., 2012).
Authors in this research paper formulates that it is not possible to consider a single process for all type
of images, nor can all process perform well for types of image. The background subtraction process
identify parts with noise destruction and output is not accurate and precise. The object behind object
is not recognized. During identication of part when any other thing come before the part problem
occurs. The image cannot be recognized if the position of camera is not accurate and object in picture
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is not snapped properly (Jain & Chadokar, 2015)Object recognition is a work of searching a selected
object in an image or video sequence. Object detection plays a key role in image processing, It helps in
searching of any particular object Object recognition is use to detect a particular object from a series of
other objects, sometimes shadow and background images becomes problem in detection. Skull detection
technique is use resolving such kind of problems. Here we deals with dier sort of object detection
techniques and modes of multiple object detection for a image.
The authors, in this paper, through his knowledge and work proposes an algorithm that has been proved
to meet the requirement of object detection without using the color feature in an automatic robot. The
proposed algorithm specially relies on two main process that emphasize on shape identication and
feature extraction that follows.
The rst method is edge detection and line-oriented method to performing contour extraction, which
results in object detection in very less or no time. Next, the second method is a geometric moment that
captures and computes the global features of the objects. Both the process is well assured in image
processing, however, a mixture of both is a novel method in this study and has been proven to precisely
detect static and moving object under illumination variety (Dewi et al., 2019)such as the lengthy process
to calibrate color, color fading, and others. Nonetheless, the need of such application that does not
necessarily rely on color information has seen a hike due to the mentioned issues. In fact, some of the
desirable solutions are those that take less computation time, as well as those that provide higher accuracy
and scalability for a large number of objects in a scene. One application that requires such solution is in
a game playing by autonomous robot. This paper suggests a novel patch carried by autonomous robots
with relevant detection algorithm using contour detection and geometric moment without using the
color feature.
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3. METHODOLOGY
3.1. DESIGNING PHASE
3.1.1. HARDWARE DESIGNING
So initially, it is not recommended to go towards hardware fabrication directly. It is more desirable to
rst virtually design the hardware on a CADCAM Software, such as SolidWorks. Mostly, the thinking
and fabricating part does not go hand to hand simultaneously as it’s necessary that what we think can be
implemented and fabricated practically, this leads to loss of time and capital. So, in order to check our
design ideas and its practical fabrication feasibility, we do the designing work rst.
So, in the designing phase, we rst started with our conveyor. First the conveyor frame structure of
dimensions 70in x 20in x 3in was made. To understand it, it is basically like a table structure. Now,
in order to run make the conveyor bed, we attached 2 rollers at each end of the conveyor frame. By
attaching two rollers, it was observed that the conveyor belt be stable while moving as when the part
comes in the middle of the conveyor belt while travelling, the belt will sag downwards due to no roller in
the middle and this will cause irregular movement of the conveyor belt. Thus, we added a third roller in
the middle of the conveyor frame.
We, now, added a white rubber belt of 2mm thickness over the rollers to form a conveyor bed. Three
double slotted pulleys of were mounted on each on the three rollers in order to interconnect the rollers
with each other so that movement of the rollers are in sync. These pulleys are interconnected 2 rubber
V-Belt and the third belt of size relates to a pulley and with a D.C Geared Motor of 30Nm torque (24V-
3A) in order to drive the conveyor. The part to be painted will be placed on the conveyor which will
help in transporting the part to and from the painting work area. The conveyor design is given below in
Figure 1.
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Figure 1. Conveyor Design.
After the completion of the Conveyor Design or the Part Transporting Mechanism, we started to design
the CNC Mechanism which is the Painting Mechanism of our Machine. The overall size of the CNC
mechanism is 24in x 20in x 24in. Each of the 3 axes of the CNC machine is made of square shaped
2.5”x1” mild steel pipe. The main axis mechanism is formed of a ball screw of length 500mm and 8mm
size of double threads. Each of the two ends of the ball screw is connected in the 8mm bearing which
is mounted inside bearing housing.
Now, we will screw an 8mm double threaded nut over which an aluminum cube is xed which acts as
a traveler. All these things are xed to form a single axis structure. We replicate this structure four time
to form X, Y and Z axis individually (X axis is made from 2 of these structures). We mount individual
Stepper Motor on each axis in order to rotate the ball screw so that the aluminum cube mounted over
a nut move linearly back and forth. Each axis motion is limited/restricted by attaching a limit switch
at its both ends. This helps in restricting the axis motion in forward or backward direction, so all the
3-axis does not collide with each other. The painting spray gun is mounted on the Z-axis of the CNC
Mechanism. The Design of CNC Mechanism is given below in Figure 2.
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Figure 2. CNC Mechanism Design.
This CNC Mechanism is mounted on the conveyor in the middle, thus the area under the CNC
mechanism is the painting working area. Ball screws are used to move the 3-axis of the CNC mechanism.
These ball screws are rotated with the help stepper motor and stepper drives are also used. The painting
spray gun is mounted on the Z-axis of the CNC Mechanism.
Figure 3. Smart Painting Machine Complete Hardware Design.
3.1.2. ELECTRONIC CIRCUITRY DESIGNING
Apart from the hardware of the machine, the Brain which will help in driving the functionality of this
machine is the Electronic Circuitry. Basically, the electronic Circuit of this machine needs to be designed
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exclusively for itself. The readily available circuits can’t be integrated with one another to drive this
painting machine, instead its circuit needs to be designed. The main task required by the circuitry is to:
1. Drive and Control the motion of the Conveyor.
2. Drive and Control the motion of the Painting Mechanism (i.e. 3-axis CNC Mechanism).
3. Assist the Image Processing Program in execution so that the part Geometry can be identied, and
it’s coordinated can be extracted in order to move the painting mechanism to perform the painting
task.
Thus, in order to accomplish this task we chose Raspberry Pi Microcontroller which will control the
entire circuitry. Raspberry Pi will be powered by a 5V supply input which is fed from a 24V Power
Supply after connected a buck converter in series in order to step-down the voltage. Also, the conveyor
motor will be powered by this power supply and its programmable controlling will be handled by the
switching of a relay which is connected to the raspberry pi microcontroller. The Raspberry Pi Camera
Module will be connected to the microcontroller which through its assistance will capture the image
of the part which will enter the workspace to be painted. Also the Image Processing Software, which
is developed on OpenCV to detect the part, identify it and calculate its geometrical coordinates will
also be executed by this microcontroller. Also, after the extraction of the parts center coordinates, these
coordinates will be via Encoder and TTL IC will be fed to Arduino.
The Arduino Microcontroller will take in the centroid coordinates of the part (X, Y, Z) and then will
drive the painting mechanism motors in order to paint the part. The motion of the axis is limited by
Limit Switches.
The Designed Circuit for Smart Painting Machine is given in Figure 4 and Figure 5 below.
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Figure 4. Design of Circuit 1.
Figure 5. Design of Circuit 2.
3.1.3. SOFTWARE DESIGNING
The heart of this Smart Painting Machine is its Software. The software is basically termed as heart
because the sole purpose which makes this machine smart is the image processing program. We thought
of applying image processing in this machine as to get rid of uploading new programing from every
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new part and forbid the idea of keeping/placing the part to be painted in a xed place or to be xed
in its respective jigs. Image processing will help in determining the part orientation on the conveyor
bed and will calculate the part coordinates and will command the motor to move the axis respectively
in order to paint it. To implement this idea, we had to rst check that whether his idea is working or is
practically feasible to implement on a machine to calculate the part coordinates on real-time basis. Thus,
for developing, testing and nal implementation of this program, we chose to do this task using Python.
The camera which will be taking the part image will be mounted over the workspace. Once the part
enters the workspace, IR sensor will indicate the microcontroller to stop the conveyor and then the part
image will be taken and processed and then the part will get painted and then the conveyor will move,
and the part will depart the workstation. So, to implement the software idea, we made program which
works as follows:
First the part image is read by the program. After reading the image, lters of Erosion (process which
removes pixel from boundary of the object in an image) and Dilation (process which adds pixel to
boundary of the object in an image) are implemented. Then the object in the image is subtracted from
its background and then thresholding is applied on the image. After this Canny Edge Algorithm (which
detects edges of the object with noises suppressed at the same time) is applied and then the Counter
detection is applied (which joins the curve of all the continuous points along with boundaries of same
pixel intensity).
This enable the program to calculate the center of the object and its dimension. After this the coordinated
of the image is found. Then the motor steps are calculated, and this is passed on to the XYZ Algorithm
which then controls the motor movement of the CNC axis. The below Figure 6 shows the Software
design owchart.
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Figure 6. Software Flowchart.
3.2. IMPLEMENTATION VIA VIRTUAL SIMULATION OF THE PAINTING MACHINE
3.2.1. SOLIDWORKS DESIGN SIMULATION AND ANALYSIS OF THE HARDWARE
As the Hardware was not able to get complete due to the pandemic situation, what we did that we
designed and made a complete CAD Model of our hardware (which was to be fabricated) with exact
congurations so that the hardware can be tested with respect to its structural properties and working
principle.
SolidWorks Software was used to make the CAD Model of the Hardware and its Tools were used to
obtain graphical results of the Structural Rigidity Tests which includes Stress and Strain graphs of the
critical hardware element. Also, Motion Analysis was performed of the working hardware and respective
graphical results were calculated and portrayed in order to conrm the smooth working of the hardware
and its motor while on full loading conditions.
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This will not only conrm the proper hardware working but will also help in analyzing the motor
selection done in our project based on the interrupted working of the motors under loading conditions.
Also the velocity of the CNC mechanism, i.e. the speed with which its axis moves can also be obtained.
3.2.2. IMAGE PROCESSING PROGRAMMING SIMULATION USING JUPYTER
As briefed before, the Image Processing Program is used to detect the part geometry (i.e. the part which
will be placed on a conveyor and enter the workspace) so that part can be painted as per its geometrical
gure. This image processing programming was done on Python.
This task was to be performed on real-time basis that as the part would enter the workspace, the camera
mounted on the workspace would capture the image of the part placed on the conveyor and then image
processing program would process this image and compare it with original part image in the directory
and would classify the part and detect its geometry and center coordinates so that the part could be
painted as per its geometry. However, due to unavailability of the hardware of this project, the testing of
this image processing programming was performed on Jupyter.
The testing results were perfect (as predicted) and the part was classied, its geometry was identied, and
its center coordinates were perfectly calculated. This data found by Image Processing Program is further
useful to paint the part as per its geometry.
3.2.3. SIMULATION OF ELECTRONIC CIRCUITS AND PAINTING MECHANISM USING ARDUINO AND
PROTEUS
At rst, Raspberry Pi was to be used as a Controller in order to run the entire Painting Machine and
its Electronics. As we moved towards Simulation, due to unavailability of the raspberry pi simulator,
we used Proteus and Arduino in order to simulate the painting mechanism and other electronics of
our project. The Part Coordinates obtained from the Image Processing is now fed into the Arduino
Programming (used to drive the Painting Mechanism as per the part geometry in order to perform
Painting). This Arduino coding was interfaced to Proteus on which we had made the entire Electronic
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Circuitry of the Painting Machine.
As we ran the Arduino coding, so the part coordinates interpreted by the coding was used in the
simulation of the circuitry in Proteus. The Smart Painting Machine Circuitry in the Proteus Simulation
worked sequentially. As the part is placed on the conveyor, Sensor 1 detects the part presence and the
Conveyor Motor starts.
Now as the part enters workspace, Sensor 2 detects the part and stops the Conveyor Motor and after
getting the part coordinates via image processing the Painting Mechanism start moving as per the
geometry and the part is painted. After the painting process is completed, the conveyor starts again
and the part starts to move along the conveyor until it reaches the end of the conveyor where Sensor 3
detects the parts and stops the conveyor motor so that the painted part can be picked up by the human
operator/labor.
3.3. SMART PAINTING MACHINE WORKING PRINCIPLE
Initially, conveyor will be stationary i.e. it won’t be moving. There is an IR sensor mounted on the input
side of the conveyor frame. The task of this IR sensor is to signal the conveyor’s motor driver circuit that
the part is placed at the input side of the conveyor. As the part is placed the conveyor, motor starts, and
the belt begins to rotate over the conveyor rollers and the part moves forward towards the workspace i.e.
Painting Mechanism.
Now as the part moves inside the workspace, I.R sensor mounted inside the workspace signals the
conveyor motor driver circuit to stop its motion and simultaneously it also informs the Main Controller
of the Painting Machine (i.e. Raspberry Pi) that the part is now present inside the workspace. As now the
part is stationary inside the workspace, the camera mounted in the workspace captures the image of the
part and sends it to the main controller where further the part geometry is calculated by the program.
As soon as the part geometry is calculated the main controller dispatches X Y Z Algorithm to the motor
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driving circuit of CNC mechanism.
The CNC mechanism has a Painting Spray gun mounted on its z-axis. CNC mechanism or the painting
mechanism moves as per the X Y Z Algorithm and the paint gun paints the part as per its geometry by
moving about the coordinates of the part edges. Here the Limit Switches which is connected to each and
every axis of the CNC machine restricts the extra axis motion and helps in avoiding axis collision, thus
there is no chance of distortion occurrence during the painting procedure. Also, the Encoder Sensors
mounted on the motors shaft keeps the stepper motor control drive updated about motors direction of
rotation, position and speed. After the completion of part painting or we can say that after the complete
execution of the X Y Z Algorithm, the painting mechanism moves at its home position and the camera
captures a photo of the part and sends it to the main controller to check the painting work. After this
machine controller sends a signal to the motor driver circuit of the conveyor motor to start its motion
which in turn takes the path outside of the workspace and the part keeps on moving and until it reaches
the end of the conveyor bed where IR sensor detects the part arrival and inform the motor driver circuit
of the conveyor to stop its motion so that the part can be picked up by the user. As the part is picked up,
the sensor signals the motor driver circuit of the conveyor that it can start its motion and thus the cycle
of painting the next part continues. Also, for Safety purpose, Human/Obstacle Detection Sensors are
mounted outside the workspace which signal the main controller to stop all the operations at once if any
human detection is made near the workspace. This promotes human safety.
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Figure 7. Standard Operating Procedure of Smart Painting Machine.
4. RESULTS
4.1. HARDWARE SIMULATION RESULTS
Smart Painting Machine’s Hardware was designed and simulated on SolidWorks. The hardware was
fabricated asper the designed model. During the designing phase the material used for fabrications of
the machine, ball-screw material and design congurations, driving motors, conveyor belt material and
other things were all kept the same which we were going to use for the real hardware fabrications. This
was done so to check the proper working of hardware during the simulation phase and rectify and error/
problem (if any) so that it can be tackled during the designing phase only and no problems are caused
during fabrications. To further ensure the hardware structural rigidity reliability, the critical element
of the hardware (the component which bears maximum load during operation) was checked for its
maximum stress it can handle and its factor of safety (FOS) was checked. It was found out that the Yield
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Stress of ball screw is 350MPa and due to the load exertion, the Stress caused on ball screw is not more
than 66.04MPa. Also, the Factor of Safety is 2.7 which means that the ball screw is very far away from
fracture.
Figure 8. Ball Screw Stress Analysis.
Figure 9. Ball Screw Factor of Safety.
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4.2. IMAGE PROCESSING PROGRAM SIMULATION
After successfully making the Image Processing Program of Object Detection and Classication and
Simulating the Program on Jupyter, the desired results were obtained. The Resulting Images of the Parts
shows perfect geometry detection of the part which is to be painted and its center coordinates are given.
Almost 11 dierent parts were tested, result of some parts are given below.
Figure 10a. Indicator Back cover- Object Detection.
Figure 10b. Indicator Back cover- Object Classication.
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Figure 10c. Indicator Back cover- Object Center Coordinates.
5. CONCLUSION
By analyzing and observing the simulated results we can conclude that the Smart Painting Machine is
working as per the requirement and is performing the desired job eciently. The Simulated Results of
the hardware the shows feasibility of functionality and robustness of the machine itself. The designing
part helps us determine whether the components that are to be incorporated in the machine structure
will work as per the requirement and how the maximum loading conditions will aect the working of the
painting mechanism. The results obtained from the testing of the Hardware CAD Model further proves
that the Hardware Design is up-to the mark in all aspects of robustness and functionality.
Also, by observing the simulation results of the Image Processing Program, we can conclude that the
objects which will be placed on the conveyor will be correctly identied by the Developed Program using
Image Processing. We have developed this program using Python OpenCV. The results obtained are
very much accurate to that of the objects in the sample/saved images of the parts in the directory. We
have also identied that whatever the orientation of the part on the conveyor, still the program will able
to identify the part correctly. Also, we during testing of this program also observed that the size of the
real-time captured image of the part (zoomed-in or zoomed-out photograph) but still the program will
detect and classify the part. However, there is a limitation that the angle of capturing the image of the
sample and test image should be same.
The simulation of the Electronic Circuitry of the Smart Painting Machine was executed very well. This
is because the Designed Circuitry of the Painting Machine fullls all the requirements of which assists in
smooth operation of the painting machine.
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REFERENCES
Abdellatif, M. (2012). Design of An Autonomous Wall Painting Robot Design of An Autonomous Wall
Painting Robot. In First Interna1onal Symposium on Socially and Technically Symbio1c Systems. https://
www.researchgate.net/publication/236659040_Design_of_An_Autonomous_Wall_Painting_
Robot
Amin, I., & Saeed, A. (2018). 5.10 Wireless Technologies in Energy Management. Comprehensive Energy
Systems, 5, 389–422. https://doi.org/10.1016/B978-0-12-809597-3.00524-1
Ata, A. A., & Eleyan, A. (2017). An Autonomous Robotic Cell for Painting Applications. Acta Press. https://
doi.org/10.2316/P.2017.848-014
Dewi, D. A., Sundararajan, E., Prabuwono, A. S., & Cheng, L. M. (2019). Object detection
without color feature: Case study Autonomous Robot. International Journal of Mechanical Engineering
and Robotics Research, 8(4), 646–650. https://doi.org/10.18178/ijmerr.8.4.646-650
Feng, X., Chen, L., Zhou, W., & Huang, Z. (2017). Research on the Design of Smart Paint Robot.
DEStech Transactions on Materials Science and Engineering, c(smne), 1–5. https://doi.org/10.12783/
dtmse/smne2016/10590
Hussin, R., Juhari, M. R., Kang, N. W., Ismail, R. C., & Kamarudin, A. (2012). Digital image
processing techniques for object detection from complex background image. Procedia Engineering,
41, 340–344. https://doi.org/10.1016/j.proeng.2012.07.182
Ikemoto, S., Liao, M., Takai, Y., Goto, A., Nishimoto, H., & Hamada, H. (2015). Impact of
Operator Experience on Spray Gun Handling for Automobile Repair. Procedia Manufacturing, 3,
488–494. https://doi.org/10.1016/j.promfg.2015.07.212
3C Tecnología. Glosas de innovación aplicadas a la pyme. ISSN: 2254 – 4143 Ed. 36 Vol. 9 N.º 4 Diciembre 2020 - Marzo 2021
118
https://doi.org/10.17993/3ctecno/2020.v9n4e36.95-119
Jain, S., & Chadokar, S. (2015). A Object Detection in Image Processing: A Review. International Journal
of Electrical, Electronics and Computer Engineering, 4(2), 26-29. https://www.researchtrend.net/ijeece/
ijet21/ijetnew/4%20SHRISHTEE%20JAIN.pdf
Naticchia, B., Giretti, A., & Carbonari, A. (2007). Set up of an automated multi-colour system for
interior wall painting. International Journal of Advanced Robotic Systems, 4(4), 407–416. https://doi.
org/10.5772/5666
Saeed, A., Haroon, K. M., Talha, M., & Thebo, T. M. (2019). Frictional Analysis of dierent coatings
on MS material in order to increase the life of machine element. In 3rd International Symposium
on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 1–6. https://doi.org/10.1109/
ISMSIT.2019.8932769
Swarakar, J. R., Belkhade, R. D., Dalal, V. G., Ghode, C. D., Maskar, S. L., Fulmali, S. M., &
Shelki, S. B. (2018). Design and Fabrication of Automatic Spray Painting Machine. International
Journal of Advance Research and Innovative Ideas in Education, 4(2), 1388–1394. http://www.ijariie.
com/AdminUploadPdf/DESIGN_AND_FABRICATION_OF_AUTOMATIC_SPRAY_
PAINTING_MACHINE_ijariie7676.pdf
Thakar, D., & Vora, C. P. (2014). A Review on Design & Development of Semi-Automated Colour
Painting Machine. Journal of Engineering Research and Applications, 4(4), 58–61. https://www.
academia.edu/7548109/A_Review_on_Design_and_Development_of_Semi_Automated_
Colour_Painting_Machine
Wiley, V., & Lucas, T. (2018). Computer Vision and Image Processing: A Paper Review. International
Journal of Articial Intelligence Research, 2(1), 22. https://doi.org/10.29099/ijair.v2i1.42
